CN112786199A

CN112786199A - Interface for displaying patient data

Info

Publication number: CN112786199A
Application number: CN202011207812.5A
Authority: CN
Inventors: M·F·海蒂格; J·霍尔丹; K·布朗
Original assignee: Hill Rom Services Inc
Current assignee: Hill Rom Services Inc
Priority date: 2019-11-05
Filing date: 2020-11-02
Publication date: 2021-05-11

Abstract

An exemplary mobile device may include: an engine programmed to receive one or more sources of patient data providing patient identification information, vital sign information, alarm information, and task information; and a display of the mobile device, the display providing a screen having: a first window having a list of patients assigned to a caregiver; and a second window having a plurality of vital signs and early warning scores associated with a caregiver's patient.

Description

Interface for displaying patient data

Background

The present disclosure relates to assessing patient risk in a medical facility, and more particularly to assessing patient risk based on data obtained from a medical device. More particularly, the present disclosure relates to assessing multiple risks for a patient in a medical facility and notifying caregivers of the multiple risks for the patient.

Patients in a medical facility are exposed to a variety of risks during hospitalization. For example, there is a risk of sepsis, a risk of pressure injuries such as pressure sores or bedsores, and a risk of falling when or after leaving the bed. Risk assessments of patients are often sporadic with long intervals between assessments. For example, vital signs may not be recorded to the patient's Electronic Medical Record (EMR) once or twice per shift, and thus there may be a 4 to 8 hour or more interval between vital sign recordings. Furthermore, sometimes the results of a risk assessment are only available at a limited number of locations in a medical facility, for example on an EMR computer or a computer at a main nurse station. Therefore, there is a need in the medical field to obtain more timely information about a patient's risk assessment, and to make the risk assessment information more readily available to caregivers.

Disclosure of Invention

An apparatus, system or method may include one or more features recited in the claims appended hereto and/or the following features, which may individually or in any combination comprise patentable subject matter.

According to a first aspect of the present disclosure, a system for a medical facility may be provided. The system may include an analysis engine and a plurality of devices that may provide data to the analysis engine. The data may relate to a patient in a medical facility. The plurality of devices may include at least one of: a patient support device, a nurse call computer, a physiological monitor, a patient lift, a positioning computer of a positioning system, and an incontinence detection pad. The analysis engine may analyze data from the plurality of devices to determine, substantially in real-time, at least one of: a first score relating to a patient's risk of sepsis, a second score relating to a patient's risk of falling, and a third score relating to a patient's risk of developing a stress injury. The system may further include a computer that may be coupled to the analysis engine and that may coordinate a caregiver check-out interval during which at least one caregiver assigned to the patient is required to check the patient. The computer may automatically decrease the caregiver check-out interval in response to at least one of the first, second, or third scores increasing from a first value to a second value, and the computer may automatically increase the caregiver check-out interval in response to at least one of the first, second, or third scores decreasing from the second value to the first value.

In some embodiments, the system of the first aspect may further comprise a plurality of displays, which may be communicatively coupled to the analysis engine and operable to display at least two of the first, second, and third scores. For example, the plurality of displays may include at least two of: a status panel display that may be located at a main nurse station, an in-room display that may be provided by a room station of the nurse call system, an Electronic Medical Record (EMR) display of an EMR computer, and a mobile device display of a mobile device that may be assigned to a caregiver of the patient.

The plurality of devices of the first aspect may comprise at least three of: a patient support device, a nurse call computer, a physiological monitor, a patient lift, a positioning computer, and an incontinence detection pad. Alternatively, the plurality of devices of the first aspect may comprise at least four of: a patient support device, a nurse call computer, a physiological monitor, a patient lift, a positioning computer, and an incontinence detection pad. Further alternatively, the plurality of devices of the first aspect may comprise at least five of: a patient support device, a nurse call computer, a physiological monitor, a patient lift, a positioning computer, and an incontinence detection pad. Still further optionally, the plurality of devices of the first aspect may comprise all six of: a patient support device, a nurse call computer, a physiological monitor, a patient lift, a positioning computer, and an incontinence detection pad.

Optionally, each of the first, second and third scores of the first aspect may be normalized by the analysis engine to have a minimum and maximum value common to each of the other first, second and third scores. For example, the minimum value may be 0 for each of the first, second, and third scores. Alternatively, the minimum value may be 1 for each of the first, second and third scores. Further, the maximum value may be 5 for each of the first, second, and third scores. It is also within the scope of the present disclosure to use other minimum values for the first, second, and third scores that are less than 0 (e.g., a negative number) and greater than 5.

In some embodiments of the first aspect, the analysis engine may also receive additional data for the patient from an international pressure sore prevalence (IPUP) survey, and analyze the additional data for determining at least one of the first, second, and second scores. The analysis engine may transmit at least two of the first score, the second score, and the third score to at least one of the plurality of devices. Optionally, at least one of the plurality of devices may include a device display, and the step of lowering at least one of the first, second and third scores may be displayed on the device display if desired.

According to the system of the first aspect, the data from the patient support apparatus may comprise at least one patient vital sign, which may be sensed by at least one vital sign sensor that may be integrated into the patient support apparatus. For example, the at least one patient vital sign that may be sensed by the at least one vital sign sensor may include a heart rate or a respiration rate. The data from the patient support device may also include a patient weight. Alternatively or additionally, the data from the patient support device may include the patient's weight and the patient's position on the patient support device. Further alternatively or additionally, the data from the patient support device may include data indicative of an amount of motion of the patient while the patient is supported on the patient support device.

In some embodiments of the first aspect, the data from the physiological monitor may include one or more of: heart rate data, Electrocardiograph (EKG) data, respiratory rate data, patient temperature data, pulse oximetry data, and blood pressure data. The system of the first aspect may be configured such that the first score may be at or near a maximum value if the following criteria are present: i) the patient's body temperature is greater than about 38.3 degrees celsius (C) (about 101 degrees fahrenheit (F)) or less than about 35.6 ℃ (about 96 ° F); ii) the heart rate of the patient is greater than 90 beats per minute; iii) the patient has a breathing rate greater than 20 breaths per minute.

If desired, the analysis engine of the first aspect may initiate a message to a mobile device assigned to at least one caregiver of the patient if the first, second, or third score increases from a previous value. Alternatively or additionally, the analysis engine of the first aspect may initiate a message to a mobile device assigned to at least one caregiver of the patient if the first, second, or third score reaches a threshold. Optionally, the analysis engine may also receive additional data relating to at least one wound of the patient, and may analyze the additional data for determining at least one of the first, second, and third scores. For example, the additional data relating to the at least one wound may include an image of the at least one wound.

In some embodiments, the patient support device of the first aspect may comprise a patient bed or a stretcher. The analysis engine may also receive additional data relating to at least one of: fluid input and output, cardiac output, comorbidities, and blood tests, and wherein the analysis engine may analyze the additional data for determining at least one of the first, second, and third scores. The physiological monitor of the first aspect may comprise at least one of: a wireless patch sensor, a mobile heart monitor, an electrocardiogram, a respiration rate monitor, a blood pressure monitor, a pulse oximeter, and a thermometer attachable to a patient. The plurality of apparatuses of the first aspect may further comprise a chair monitor to monitor the movement of the patient while the patient is seated on the chair. Alternatively or additionally, the plurality of apparatuses of the first aspect may further comprise a toilet monitor to monitor the movement of the patient while the patient is seated on the toilet.

According to a second aspect of the present disclosure, an apparatus for assessing a medical risk of a patient may include an analysis engine and a plurality of devices that may provide data to the analysis engine. The plurality of devices may include at least two of: a patient support device, a nurse call computer, a physiological monitor, a patient lift, a positioning computer of a positioning system, and an incontinence detection pad. The analysis engine may analyze data from the plurality of devices to determine at least two of: a first score that may relate to a patient's risk of sepsis, a second score that may relate to a patient's risk of falling, and a third score that may relate to a patient's risk of pressure damage. The apparatus may further include a plurality of displays that may be communicatively coupled to the analysis engine and operable to display at least two of the first, second, and third scores. The plurality of displays may include at least two of: a status panel display that may be located at a main nurse station, an in-room display that may be provided by a room station of a nurse call system, an Electronic Medical Record (EMR) display of an EMR computer, and a mobile device display of a mobile device that may be assigned to a caregiver of a patient.

In some embodiments, the plurality of devices may include at least three of a patient support device, a nurse call computer, a physiological monitor, a patient lift, a positioning computer, and an incontinence detection pad. In further embodiments, the plurality of devices may include at least four of a patient support apparatus, a nurse call computer, a physiological monitor, a patient lift, a positioning computer, and an incontinence detection pad. In further embodiments, the plurality of devices may include at least five of a patient support apparatus, a nurse call computer, a physiological monitor, a patient lift, a positioning computer, and an incontinence detection pad. In other embodiments, the plurality of devices includes all six of a patient support apparatus, a nurse call computer, a physiological monitor, a patient lift, a positioning computer, and an incontinence detection pad.

Optionally, each of the first, second and third scores may be normalized to have a minimum value and a maximum value that are common to each of the other first, second and third scores. For example, the minimum value may be 0 for each of the first, second, and third scores. Alternatively, the minimum value may be 1 for each of the first, second and third scores. Likewise, the maximum value may be 5 for each of the first, second, and third scores. It is also within the scope of the present disclosure to use other minimum values for the first, second, and third scores that are less than 0 (e.g., a negative number) and greater than 5.

The present disclosure contemplates that a ward round protocol related to a caregiver's ward round may be adjusted based on at least one of the first, second, and third scores. For example, the ward visit protocol that may be adjusted includes a ward visit interval that relates to when a caregiver may be required to check the patient.

If desired, the analysis engine may also receive other data for the patient from an international pressure sore prevalence (IPUP) survey, and may analyze the other data for determining at least one of the first, second, and third scores.

In some embodiments, the analysis engine may transmit at least two of the first, second, and third scores to the plurality of devices. At least one of the plurality of devices may include a device display, and the step of lowering at least one of the first, second, and third scores may be displayed on the device display.

The data from the patient support apparatus can include at least one patient vital sign that can be sensed by at least one vital sign sensor that can be integrated into the patient support apparatus. For example, the at least one patient vital sign that may be sensed by the at least one vital sign sensor may include a heart rate or a respiration rate. Alternatively or additionally, the data from the patient support device may include a patient weight. Further alternatively or additionally, the data from the patient support device may include a patient weight and a position of the patient on the patient support device. Optionally, the data from the patient support device may include data indicative of an amount of motion of the patient while the patient is supported on the patient support device.

The analysis engine may analyze data from the plurality of devices in substantially real-time and may update at least two of the first, second, and third scores in substantially real-time. The present disclosure contemplates that the data from the physiological monitor may include one or more of: heart rate data, Electrocardiograph (EKG) data, respiratory rate data, patient temperature data, pulse oximetry data, and blood pressure data.

In some embodiments, the first score may be at or near a maximum value if the following criteria exist: i) the patient's body temperature is greater than about 38.3 degrees celsius (C) (about 101 degrees fahrenheit (F)) or less than about 35.6 ℃ (about 96 ° F); ii) the heart rate of the patient is greater than 90 beats per minute; iii) the patient has a breathing rate greater than 20 breaths per minute.

Alternatively, if the first, second or third score increases above a previous value, the analysis engine may initiate a message to a mobile device assigned to the caregiver of the patient. Alternatively or additionally, the analysis engine may initiate a message to a mobile device assigned to a caregiver of the patient if the first, second, or third score reaches a threshold.

In some embodiments, the analysis engine may also receive additional data related to at least one wound of the patient, and may analyze the additional data for determining at least one of the first, second, and third scores. For example, the additional data relating to the at least one wound may include an image of the at least one wound.

The patient support device may comprise, for example, a patient bed or a stretcher. If desired, the analysis engine may also receive additional data relating to at least one of: fluid input and output, cardiac output, complications and blood tests. The analysis engine may analyze the additional data for determining at least one of the first, second, and third scores.

In some embodiments, the physiological monitor may include at least one of: a wireless patch sensor attachable to a patient, a mobile heart monitor, an EKG, a respiration rate monitor, a blood pressure monitor, a pulse oximeter, and a thermometer. Alternatively or additionally, the plurality of devices may further comprise a chair monitor to monitor the patient's movement while the patient is seated on the chair. Further alternatively or additionally, the plurality of devices may also include a toilet monitor to monitor the movement of the patient while the patient is seated on the toilet.

According to a third aspect of the present disclosure, an apparatus for assessing a medical risk of a patient may include an analysis engine and a plurality of devices that may provide data to the analysis engine. The plurality of devices may include at least two of: a patient support device, a nurse call computer, a physiological monitor, a patient lift, a positioning computer of a positioning system, and an incontinence detection pad. The analysis engine may analyze data from the plurality of devices to determine each of: a first score that may relate to a patient's risk of sepsis, a second score that may relate to a patient's risk of falling, and a third score that may relate to a patient's risk of pressure damage. The apparatus may further include a plurality of displays that may be communicatively coupled to the analysis engine. At least one display of the plurality of displays is operable to display the first, second, and third scores.

In some embodiments, the at least one display may comprise at least one of: a status panel display that may be located at a main nurse station, an in-room display that may be provided by a room station of the nurse call system, an Electronic Medical Record (EMR) display of an EMR computer, and a mobile device display of a mobile device assigned to a caregiver of the patient. In further embodiments, the at least one display may include at least two of: a status panel display that may be located at a main nurse station, an in-room display that may be provided by a room station of the nurse call system, an Electronic Medical Record (EMR) display of an EMR computer, and a mobile device display of a mobile device assigned to a caregiver of the patient. In other embodiments, the at least one display may include at least three of: a status panel display that may be located at a main nurse station, an in-room display that may be provided by a room station of the nurse call system, an Electronic Medical Record (EMR) display of an EMR computer, and a mobile device display of a mobile device assigned to a caregiver of the patient. In other embodiments, the at least one display may include all four of: a status panel display that may be located at a main nurse station, an in-room display that may be provided by a room station of the nurse call system, an Electronic Medical Record (EMR) display of an EMR computer, and a mobile device display of a mobile device assigned to a caregiver of the patient.

In some embodiments, the apparatus of the third aspect set forth above may be provided in combination with any one or more features set forth above in the second aspect.

According to a fourth aspect of the present disclosure, a method for assessing a medical risk of a patient may include receiving data from a plurality of devices at an analysis engine. The plurality of devices may include at least two of: a patient support device, a nurse call computer, a physiological monitor, a patient lift, a positioning computer of a positioning system, and an incontinence detection pad. The method may further include analyzing data from the plurality of devices with an analysis engine to determine at least two of: a first score that may relate to a patient's risk of sepsis, a second score that may relate to a patient's risk of falling, and a third score that may relate to a patient's risk of pressure damage. The method may further include displaying at least two of the first, second, and third scores on a plurality of displays, which may be communicatively coupled to the analysis engine. The plurality of displays may include at least two of: a status panel display that may be located at a main nurse station, an in-room display that may be provided by a room station of the nurse call system, an Electronic Medical Record (EMR) display of an EMR computer, and a mobile device display of a mobile device assigned to a caregiver of the patient.

In some embodiments, the plurality of devices may include at least three of a patient support device, a nurse call computer, a physiological monitor, a patient lift, a positioning computer, and an incontinence detection pad. In further embodiments, the plurality of devices may include at least four of a patient support apparatus, a nurse call computer, a physiological monitor, a patient lift, a positioning computer, and an incontinence detection pad. In further embodiments, the plurality of devices may include at least five of a patient support apparatus, a nurse call computer, a physiological monitor, a patient lift, a positioning computer, and an incontinence detection pad. In other embodiments, the plurality of devices may include all six of a patient support apparatus, a nurse call computer, a physiological monitor, a patient lift, a positioning computer, and an incontinence detection pad.

Optionally, the method may further comprise: each of the first, second and third scores is normalized by the analysis engine to have a minimum and maximum value that is common to each of the other first, second and third scores. For example, the minimum value may be 0 for each of the first, second, and third scores. Alternatively, the minimum value may be 1 for each of the first, second and third scores. If desired, the maximum value may be 5 for each of the first, second and third scores. It is also within the scope of the present disclosure to use other minimum values for the first, second, and third scores that are less than 0 (e.g., a negative number) and greater than 5.

In some embodiments, the method may further include adjusting a ward round related to the caregiver's ward round based on at least one of the first, second, and third scores. For example, the ward visit protocol that may be adjusted includes a ward visit interval that relates to when a caregiver may be required to check the patient.

If desired, the method may further include receiving additional data for the patient from an international pressure sore prevalence (IPUP) survey at the analysis engine and analyzing the additional data with the analysis engine for determining at least one of the first, second, and third scores. The method may also include communicating at least two of the first, second, and third scores from the analysis engine to the plurality of devices. At least one of the plurality of devices may include a device display, and the method may further include the step of displaying on the device for lowering at least one of the first, second, and third scores.

In some embodiments of the method, the data from the patient support device may include at least one patient vital sign that may be sensed by at least one vital sign sensor that may be integrated into the patient support device. For example, the at least one patient vital sign that may be sensed by the at least one vital sign sensor may include a heart rate or a respiration rate. Alternatively or additionally, the data from the patient support device may also include the patient weight. Further alternatively or additionally, the data from the patient support device may include a patient weight and a position of the patient on the patient support device. Still further alternatively or additionally, the data from the patient support device may include data indicative of an amount of motion of the patient while the patient is supported on the patient support device.

In some embodiments, analyzing the data with the analysis engine may include analyzing the data in substantially real-time, and the method may further include updating at least two of the first, second, and third scores in substantially real-time. The data from the physiological monitor may include one or more of: heart rate data, Electrocardiograph (EKG) data, respiration rate data, patient temperature data, pulse oximetry data, and blood pressure data. The present disclosure contemplates that the first score may be at or near maximum if the following criteria exist: i) the patient's body temperature is greater than about 38.3 degrees celsius (C) (about 101 degrees fahrenheit (F)) or less than about 35.6 ℃ (about 96 ° F); ii) the heart rate of the patient is greater than 90 beats per minute; iii) the patient's breathing rate is greater than 20 breaths per minute.

Optionally, the method may further comprise: if the first, second or third score increases above a previous value, a message is initiated to a mobile device assigned to a caregiver of the patient using the analysis engine. Alternatively or additionally, the method may further comprise: if the first, second, or third score reaches a threshold, a message is initiated with the analysis engine to a mobile device assigned to a caregiver of the patient.

If desired, the method may further include receiving additional data relating to at least one wound of the patient at the analysis engine and analyzing the additional data with the analysis engine for determining at least one of the first, second, and third scores. For example, the additional data that may be related to the at least one wound may include an image of the at least one wound.

The patient support device may comprise a patient bed or a stretcher. Optionally, the method may further comprise receiving, at the analysis engine, additional data relating to at least one of: fluid input and output, cardiac output, comorbidities and blood tests, and analyzing the additional data with an analysis engine for determining at least one of the first, second and third scores.

In some embodiments of the method, the physiological monitor may include at least one of: a wireless patch sensor attachable to a patient, a mobile heart monitor, an EKG, a respiration rate monitor, a blood pressure monitor, a pulse oximeter, and a thermometer. Alternatively or additionally, the plurality of devices of the method may further comprise a chair monitor to monitor the patient's movement while the patient is seated on the chair. Further alternatively or additionally, the apparatus of the method may further comprise a toilet monitor to monitor the movement of the patient while the patient is seated on the toilet.

According to a fifth aspect of the present disclosure, a method for assessing a medical risk of a patient may include receiving data from a plurality of devices at an analysis engine. The plurality of devices may include at least two of: a patient support device, a nurse call computer, a physiological monitor, a patient lift, a positioning computer of a positioning system, and an incontinence detection pad. The method may further comprise: analyzing data from the plurality of devices with an analysis engine to determine each of: a first score that may relate to a patient's risk of sepsis, a second score that may relate to a patient's risk of falling, and a third score that may relate to a patient's risk of pressure damage. The method may further include displaying the first, second, and third scores on at least one display of a plurality of displays communicatively coupled to the analysis engine.

In some embodiments, the at least one display may comprise at least one of: a status panel display that may be located at a main nurse station, an in-room display that may be provided by a room station of the nurse call system, an Electronic Medical Record (EMR) display of an EMR computer, and a mobile device display of a mobile device assigned to a caregiver of the patient. In further embodiments, the at least one display may include at least two of: a status panel display that may be located at a main nurse station, an in-room display that may be provided by a room station of the nurse call system, an Electronic Medical Record (EMR) display of an EMR computer, and a mobile device display of a mobile device assigned to a caregiver of the patient. In other embodiments, the at least one display may include at least three of: a status panel display that may be located at a main nurse station, an in-room display that may be provided by a room station of the nurse call system, an Electronic Medical Record (EMR) display of an EMR computer, and a mobile device display of a mobile device assigned to a caregiver of the patient. In still other embodiments, the at least one display may include all four of: a status panel display that may be located at a main nurse station, an in-room display that may be provided by a room station of the nurse call system, an Electronic Medical Record (EMR) display of an EMR computer, and a mobile device display of a mobile device assigned to a caregiver of the patient.

In some embodiments, the method of the fifth aspect set forth above may be provided in combination with any one or more features set forth above in the fourth aspect.

According to a sixth aspect of the present disclosure, a method of assessing a medical risk of a patient may include receiving, at an analysis engine, demographic data of the patient, the demographic data including at least one of age, race, and weight. The method of the sixth aspect may further comprise: receiving, at an analysis engine, complication data for a patient, the complication data comprising data indicative of the patient having at least one of the following medical conditions: acquired immunodeficiency syndrome (AIDS), anemia, chronic congestive heart failure, asthma, cancer, Chronic Obstructive Pulmonary Disease (COPD), coronary artery disease, cystic fibrosis, dementia, emphysema, alcohol or drug abuse, stroke, pulmonary embolism, a history of sepsis, type 1 diabetes, morbid obesity, neuromuscular disease, past intubation, scoliosis, smoker, delirium, splenomess, bone marrow transplantation, cirrhosis, dialysis, diverticular disease, heart valve disease, inflammatory bowel disease, joint replacement, leukopenia, malignancy, tumor, organ transplantation, peripheral vascular disease, kidney disease, pressure injury, recent abortion, recent childbirth, epilepsy, sickle cell anemia, or end stage disease. The method of the sixth aspect may further include receiving, at the analysis engine, physiological data, which may be measured by a physiological monitor, which may have at least one sensor coupled to or in communication with the patient. The physiological data may be dynamic and change over time as the patient is monitored by the physiological monitor. Still further, the method of the sixth aspect may comprise calculating a risk score for the patient in substantially real time using an analysis engine based on the patient demographic data, the comorbidity data, and the physiological data.

In some embodiments, the method of the sixth aspect may further comprise: laboratory data of the patient is received at the analysis engine and used to calculate a risk score. Alternatively, the laboratory data may include data that may be related to one or more of the following: albumin, arterial blood oxygen partial pressure (arterial PaO2), arterial blood carbon dioxide partial pressure (PCO2), arterial blood pH, acidosis, brain natriuretic peptide, blood urea nitrogen, cardiac ejection fraction, creatinine, hemoglobin, hematocrit, lactate, pulmonary function tests, troponin, bilirubin, C-reactive protein, D-dimer, glucose, bicarbonate (HCO3), hyperlactatemia, international coagulation standard quantitation (INR), normal white blood cell count (WBC) with neutrophils greater than 10%, arterial blood carbon dioxide partial pressure (PaCO2), fluid overload, pH value, platelets, procalcitonin, urine protein, Partial Thromboplastin Time (PTT), or white blood cell count.

Alternatively or additionally, the method of the sixth aspect may further comprise: patient symptom data for the patient is received at the analysis engine and a risk score is calculated using the patient symptom data. Optionally, the patient symptom data may include data that may be related to one or more of: paramuscular use, mental state changes, confusion, anxiety, chest pain, cough, cyanosis, sweating, dyspnea, hemoptysis, fatigue, dysphoria, sputum production, tachycardia, tachypnea or lethargy.

Further alternatively or additionally, the method of the sixth aspect may further comprise: the clinical exam data is received at an analysis engine and used to calculate a risk score. Optionally, the clinical examination data may include data relating to one or more of: abdominal breathing, abnormal lung sounds, accessory muscle use, capillary refilling, chest distress or chest pain, electrocardiographic (ECG or EKG) abnormalities, cough, cyanosis, reduced consciousness Level (LOC), irritability, encephalopathy, color spots, Activities of Daily Living (ADL) requiring assistance, orthopnea, peripheral edema, sputum secretion, delirium, excess body fluid, cardiac output, early skin warm red, late skin pale and color spots, fever, headache, neck stiffness, hypothermia, intestinal obstruction, jaundice, meningitis, oliguria, peripheral cyanosis, pityriasis, fluid homeostasis, epilepsy, coma or insufficient blood volume.

Further alternatively or additionally, the method of the sixth aspect may further comprise: the recorded order data is received at the analysis engine and used to calculate a risk score. Optionally, the recorded order data may include data that may be related to one or more of: delivery of breathing air other than with a cannula (including with a venturi, ventilator, non-rebreather, Continuous Positive Airway Pressure (CPAP) machine, bi-phase positive airway pressure (bi-PAP) machine); testing arterial blood gas; brain natriuretic peptide testing; respiratory therapy; chest x-ray film; a Doppler echocardiogram; high flow rate or high capacity (input output (I & O)); lung consultation; testing lung function; ventilation perfusion (VQ) scan; or a chest Computed Tomography (CT) scan.

In some embodiments, the method of the sixth aspect may further comprise: admission data for the patient is received at the analysis engine and used to calculate a risk score. Optionally, the admission data may include data that may be related to one or more of: abdominal aortic aneurysm surgery, acute myocardial ischemia, acute pancreatitis, aspiration, asthma, bronchiectasis, atelectasis, bronchitis, burns, cancer, cardiac or thoracic surgery, heart valve disease or valve insufficiency, chemotherapy, congestive heart failure, chronic obstructive pulmonary disease progression, deep vein thrombosis, drug overdose, dyspnea at rest, emergency surgery, hemoptysis, interstitial lung disease, lung abscess, neck surgery, neurosurgery, epigastric surgery, peripheral vascular surgery, pneumonia, pneumothorax, pulmonary embolism, pulmonary hypertension, pulmonary renal syndrome, renal failure, sepsis, shock, sleep apnea, smoke inhalation injury, surgery, thoracentesis, trauma, lethargy, delirium, abscess, abdominal pain, abdominal tenderness, acute lung injury, appendicitis, bacteremia, cellulitis, cholangitis, acute lung injury, appendicitis, and/or chronic obstructive pulmonary disease, Colitis, cystitis, dehydration, diverticulitis, encephalitis, encephalopathy, endocarditis, unexplained fever, gastroenteritis, gastrointestinal bleeding, gastrointestinal infection, hypotension, infectious process, discomfort, osteomyelitis, ostomy, pelvic pain, kidney disease, pyelonephritis, respiratory infection, suppurative arthritis, soft tissue infection, surgical hospital admission, wound or acute respiratory distress syndrome.

Alternatively or additionally, the method of the sixth aspect may further comprise: medication data for the patient is received at the analysis engine and used to calculate a risk score. Optionally, the medication data may include data relating to one or more of: anticoagulants including heparin or enoxaparin (levenox), bronchodilators, corticosteroids, diuretic use, high flow or high volume or hypertonic fluids, opioids, sedatives, hypnotics, muscle relaxants, fluid overload, antibiotics or immunosuppressive agents that may be delivered Intravenously (IV) or Subcutaneously (SC).

In some embodiments, the method of the sixth aspect may further comprise: if a patient is 70 years old or older and has Chronic Obstructive Pulmonary Disease (COPD), an analysis engine is utilized to determine that the patient is likely to be at risk for respiratory distress. Alternatively or additionally, the method of the sixth aspect may further comprise: if the patient has COPD and has taken opioids, the analysis engine is used to determine that the patient is at risk of developing respiratory distress. Further alternatively or additionally, the method of the sixth aspect may further comprise: if the patient is 70 years old or older and has taken opioids, the analysis engine is used to determine that the patient is likely to be at risk for respiratory distress. Still further alternatively or additionally, the method of the sixth aspect may further comprise: if the patient is 70 years old or older, has asthma, and has urea nitrogen (BUN) in blood greater than or equal to 30 milligrams per 100 milliliters (ml) (mg), then the analysis engine is used to determine that the patient is at risk for respiratory distress.

The method of the sixth aspect may further comprise, if desired: if the patient is 65 years old or older and has cancer, the analysis engine is used to determine that the patient is likely at risk for sepsis. Alternatively or additionally, the method of the sixth aspect may further comprise: if the patient has a history of sepsis, the analysis engine is used to determine that the patient is likely to be at risk of sepsis. Further alternatively or additionally, the physiological data of the method of the sixth aspect may comprise one or more of: heart rate, respiration rate, body temperature, mean arterial pressure, systolic pressure, or pulse oximetry data including peripheral capillary oxygen saturation (SpO 2).

According to a seventh aspect of the present disclosure, a method implemented on at least one computer may include receiving dynamic clinical variables and vital sign information of a patient, developing a previous vital sign mode and a current vital sign mode using the vital sign information, and comparing the previous vital sign mode to the current vital sign mode. The method of the seventh aspect may further comprise receiving one or more of: a static variable of the patient, a complaint of the patient, a previous healthcare utilization pattern of the patient, or a social determinant of health data of the patient. The method of the seventh aspect may further comprise using the dynamic clinical variables, the vital sign information, the comparison of the previous vital sign pattern to the current vital sign pattern, and one or more of the social determinants of the static variables, the chief complaints, the healthcare utilization pattern, or the health data in an algorithm to detect or predict that the patient has sepsis or is likely to have sepsis.

In some embodiments of the methods of the seventh aspect, the dynamic clinical variables may comprise point of care laboratory data. Alternatively, the static variable may include complications. Alternatively or additionally, the static variables may include whether the patient's care settings are pre-emergency care settings, or post-emergency care settings. The method of the seventh aspect may further include receiving historical data of the patient, if desired.

It is within the scope of the present disclosure that the method of the seventh aspect may further include outputting one or more suggested actions to one or more clinicians of the patient. For example, the one or more suggested actions may include sending the patient to an emergency room (ED). Alternatively or additionally, the one or more suggested actions may include enhancing monitoring of the patient by one or more clinicians. Further alternatively or additionally, the one or more suggested actions may include ordering a series of laboratory tests for the patient.

In some embodiments, the method of the seventh aspect may further comprise ranking clinicians of the medical institution. For example, ranking clinicians for a medical facility may include empirically ranking clinicians. Alternatively or additionally, ranking clinicians for a medical facility may include ranking clinicians according to previously taken actions. Further alternatively or additionally, ranking clinicians for a medical facility may include ranking clinicians according to previous patient treatment results. Thus, ranking clinicians for a medical facility may include ranking clinicians based on experience, based on previously taken actions, and based on previous patient treatment results, if desired. Optionally, the at least one computer may use the measure having the greatest impact on the treatment outcome to inform the novice clinician or less experienced clinician how the experienced clinician is dealing with the patient.

In some embodiments of the system of the first aspect, the risk determination or calculation of one or more of the first, second or third risk scores may be made based on one or more data elements listed in table 11 below.

In some embodiments of the apparatus of the second or third aspect, the risk determination or calculation of one or more of the first, second or third risk scores may be made based on one or more data elements listed in table 11 below.

In some embodiments of the method of the fourth or fifth aspect, the method may further comprise making a risk determination or calculating one or more of the first, second or third risk scores based on one or more data elements listed in table 11 below.

In some embodiments of the method of the sixth aspect, the method may further comprise calculating a risk score or making a risk determination based on one or more data elements listed in table 11 below.

In some embodiments of the method of the seventh aspect, the method may further comprise calculating a risk score or making a risk determination based on one or more data elements listed in table 11 below.

Additional features, alone or in combination with any other features (such as those listed above and those listed in the claims), may include patentable subject matter and will become apparent to those skilled in the art upon consideration of the detailed description of various embodiments exemplifying the best mode of carrying out the presently known embodiments.

Drawings

The detailed description makes reference, in particular, to the accompanying drawings, in which:

FIG. 1 is a schematic diagram of a system showing patient bed data, incontinence detection system data, vital sign data, and data from an international pressure sore prevalence (IPUP) survey being provided to an analysis engine, and showing the analysis engine initiating real-time clinical communication with a caregiver based on analysis of the received data;

FIG. 2 is a schematic diagram of a system similar to FIG. 1 showing a patient supported on a patient bed, an analysis engine (labeled "DSN platform" in FIG. 2) receiving data from the bed, in the top row, from left to right, with the analysis engine transmitting risk assessment messages back to the bed and to the vital signs monitor, and in the second row, from right to left, showing the patient bed monitoring the patient's position and a caregiver taking a picture of the patient's pressure injury;

FIG. 3 is a schematic diagram of a system similar to FIGS. 1 and 2 showing a router located in the center of view receiving data from a plurality of data source devices located on the left side of the router, including patient beds, graphical room stations of a nurse call system, vital signs monitors, patient lifts, a positioning system, and an incontinence detection system, and communicating with a plurality of data receiving devices located on the right side of the router, including a status board, an in-room display, an analysis engine, an Electronic Medical Record (EMR) or Health Information System (HIS) server, and a set of mobile devices;

4A-4C form a flow chart illustrating an example of a patient's routine through an emergency room (ED), Intensive Care Unit (ICU), and medical/surgical (MED/SURG) ward, and then home or to a Long Term Care (LTC) facility, and illustrating the location of the patient's routine where an analysis engine operates to determine the patient's risk of developing sepsis or having sepsis;

fig. 5A and 5B form a flow chart showing an example of a patient being admitted to and hospitalized in a medical facility (including moving the patient to a chair or toilet using equipment in the patient's room), and showing the location in the patient flow where the analysis engine operates to perform risk assessment on the patient;

FIG. 6 is a schematic diagram of an alternative system similar to FIG. 3, showing: the hospital local equipment positioned on the left side of the page comprises indoor equipment, an equipment gateway and a status board; a cloud device located in the center of the page, comprising an enterprise gateway (HL7), a clinical data repository, a risk engine and an analysis Artificial Intelligence (AI) platform; and other local devices located on the right side of the page, including mobile devices and third party solutions including EMRs, ADTs and Labs servers;

FIG. 7 is an example of a screenshot of a patient screen of a mobile application of the mobile device of FIGS. 3 and 6 showing a patient screen including a list of patient names assigned to caregivers carrying the mobile device, a room number to the left of each patient name, and a risk score (including, as applicable, a Systemic Inflammatory Response Syndrome (SIRS) value and a Modified Early Warning Score (MEWS) value) below each patient name;

fig. 8 is an example of a screen shot of a risk detail screen, wherein the risk detail screen includes, below the patient's name, an mems window with additional information related to the mems value, a SOFA window with additional information related to a sepsis related organ failure assessment (SOFA) score, and a MORSE window with additional information related to a MORSE Fall Scale (MFS) value, and the risk detail screen further includes a pair of risk influencing factor windows including a respiratory distress window and a sepsis window, wherein the respiratory distress window lists factors influencing the patient's risk of experiencing respiratory distress and the sepsis window lists factors influencing the patient's risk of developing sepsis;

FIG. 9 is an example of a screen shot of an alternative risk detail screen, where the risk detail screen includes MEWS, SIRS and SOFA windows under the patient's name with sub-score information (as applicable) that affects the total score, and the risk detail screen also includes a pair of risk influencing factor windows similar to FIG. 8;

FIG. 10 is an example of a screen shot of an MEWS detail screen providing more detailed information regarding MEWS values, including displaying which vital signs or other information corresponds to each sub-score value affecting the overall MEWS value, wherein the MEWS detail screen appears on a caregiver's mobile device in response to selecting the MEWS window on the risk detail screen of FIG. 8 or 9;

FIG. 11 is an exemplary patient screen including a list of patient names assigned to caregivers within a medical facility;

FIG. 12 is an exemplary risk details screen for a patient selected from the exemplary patient screen of FIG. 11;

FIG. 13 is another exemplary risk details screen for a patient selected from the exemplary patient screen of FIG. 11;

FIG. 14 is another exemplary risk details screen for a patient selected from the exemplary patient screen of FIG. 11;

FIG. 15 is another exemplary risk details screen for a patient selected from the exemplary patient screen of FIG. 11;

FIG. 16 is another exemplary risk details screen for a patient selected from the exemplary patient screen of FIG. 11;

FIG. 17 is another exemplary risk details screen for a patient selected from the exemplary patient screen of FIG. 11;

FIG. 18 is another exemplary risk details screen for a patient selected from the exemplary patient screen of FIG. 11;

FIG. 19 is an exemplary SIRS screen generated when a SIRS window is selected from the risk details screen of FIG. 16;

FIG. 20 is an exemplary qSOFA screen generated when a qSOFA window is selected from the risk details screen of FIG. 16;

FIG. 21 is an exemplary MORSE screen generated when the MORSE window is selected from the risk details screen of FIG. 16;

FIG. 22 is another exemplary MORSE screen;

fig. 23 is an exemplary sepsis risk screen generated when the sepsis risk box is selected from the risk detail screen of fig. 18;

fig. 24 is an exemplary fall risk screen generated when a fall risk box is selected from the risk details screen of fig. 18;

fig. 25 is another exemplary fall risk screen;

FIG. 26 is a case, background, evaluation, advice (SBAR) screen generated when the SBAR icon is selected from the risk details screen;

FIG. 27 is an exemplary vital signs screen for displaying a trend of vital signs measurements over time;

FIG. 28 is another exemplary vital signs screen;

FIG. 29 is another exemplary vital signs screen;

FIG. 30 is another exemplary patient screen including a list of patient names assigned to caregivers within a medical facility;

FIG. 31 is an exemplary chat screen including messages regarding a patient assigned to the caregiver of FIG. 30;

FIG. 32 is a main patient view screen providing information regarding one of the patients assigned to the caregiver of FIG. 30;

FIG. 33 is a secondary patient view screen providing information regarding one of the patients assigned to the caregiver of FIG. 30;

FIG. 34 is another sub-patient view screen that provides information regarding one of the patients assigned to the caregiver of FIG. 30; and

FIG. 35 is an alert view associated with a patient assigned to the caregiver of FIG. 30.

Detailed Description

The device or system 10 includes a patient data source 12, the patient data source 12 in substantially real-time communication with an analysis engine 20 for real-time clinical data aggregation, as shown in FIG. 1. In the illustrative example of fig. 1, the patient data sources 12 include a patient bed 14, an incontinence detection system 16, a vital signs monitor 18, and an international pressure sore prevalence (IPUP) survey 22. The bed data from the patient bed 14 includes, for example, data indicating whether the bed side rails are raised or lowered, data indicating whether caster brakes are set, data indicating the angle at which the head section of the mattress support panel is raised, data indicating whether the upper frame of the patient bed 14 is at its lowest elevation relative to the undercarriage of the bed 14, and other bed data known to those skilled in the art. For further examples of hospital bed data, particularly with respect to table 1, see U.S. patent application publication No. 2012/0316892a1, which is incorporated herein by reference.

Some embodiments of the patient bed 14 have a weighing system that senses the weight of the patient and, in some embodiments, also monitors the position of the patient while supported on the bed 14. See, for example, U.S. patent No. 7,253,366, the entire contents of which are incorporated herein by reference without conflict with the present disclosure, to the extent any conflict arises. Some embodiments of the patient bed 14 also include integrated vital sign sensors to sense the heart rate or respiration rate of the patient. See, for example, U.S. patent application publication No. 2018/0184984a1, the entire contents of which are incorporated herein by reference to the extent not inconsistent with the present disclosure, to which the present disclosure pertains. Thus, in some embodiments, patient weight data, patient position data, and vital sign data sensed by one or more in-bed sensors are also among the data transmitted by the patient bed 14 to the analysis engine 20.

In some embodiments, incontinence detection system 16 is WATCHCARE available from Hill-Rom Company, Inc^TMAn incontinence detection system. Additional details of suitable incontinence detection systems 16 can be found in U.S. patent application publication nos. 2017/0065464a1, 2017/0246063a1, 2018/0021184a1, 2018/0325744a1, and 2019/0060137a1, the entire contents of which are incorporated herein by reference to the extent not inconsistent with the present disclosure, to which the present disclosure controls if any conflict arises. Incontinence detection system 16 communicates data to analysis engine 20 indicating whether the incontinence detection pad of system 16, placed under the patient, is wet or dry.

In some embodiments, the incontinence detection pad of system 16 has a passive RFID tag. The passive RFID tag is activated by energy emitted by one or more antennas located below the mattress of the patient bed 14 and on top of the mattress support panel of the patient bed 14. The backscatter data from the passive RFID tag is read by one or more of these same antennas. The reader is arranged to control which of the plurality of antennas is the transmit antenna and the remaining antennas are the receive antennas in any given situation. The backscatter data received by the reader via the receive antenna is communicated to the analysis engine 20 via the reader, for example, via wireless transmission from the reader to a wireless access point of an ethernet network of the medical facility, or in those embodiments in which the reader is communicatively coupled to the patient bed circuitry, for example by a wired connection, to the analysis engine 20 via the circuitry of the patient bed 14.

Vital signs monitor 18 includes, for example, an electrocardiograph (ECG or EKG), an electroencephalograph (EEG), a heart rate monitor, a respiration rate monitor, a body temperature monitor, a pulse oximeter, a blood pressure monitor, and the like. In some embodiments, the monitor 18 is a separate device from the patient bed 14. In some embodiments, at least one of vital signs detectors 18 is a field monitor available from Welch Allyn, inc. As described above, in some embodiments, the patient bed 14 includes its own integrated vital signs sensor. Thus, vital sign data provided to analysis engine 20 from vital signs monitor 18 or patient bed 14 includes any one or more of: heart rate data, respiratory rate data, body temperature data, pulse oximetry data, blood pressure data, and the like.

The IPUP survey 22 includes information such as: 1) the patient's ward where the patient is located, 2) the patient's age, 3) the patient's gender, 4) whether the patient is incontinent, 5) whether the patient has incontinent-related dermatitis, 6) whether the incontinence detection pad of the system 16 is being used, 7) the length of the patient's stay since the hospitalization facility, 8) the type of surface (e.g., mattress) on the patient's bed 14, 9) the number of layers of fabric (including diapers and underpants) between the patient and the support surface, 10) the type of fabric used, 11) the patient's activity (e.g., completely motionless, making a slight weight transfer but unable to roll sideways, turning oneself sideways but needing assistance to stand up, or stand alone), 12) the observed position (e.g., lying flat, lying on side, lying prone, sitting on a chair, or standing), 13) whether the patient's elevator was used during the patient's stay, 14) whether the patient's heel was lifted while in bed, 15) Patient height (OR infant length), 16) patient weight, 17) neonatal weight (in grams), 18) time spent in Emergency Room (ER), 19) time spent in Operating Room (OR), 20) whether patient skin was assessed within 24 hours after admission, 21) whether a pressure injury assessment was recorded within 24 hours after admission, 22) a risk method used at admission, 23) a risk score determined during admission, 24) a most recently OR currently used risk method, 25) a most recent OR current risk score, 26) a record of a most recent risk assessment (e.g., time since last pressure sore/pressure injury risk assessment prior to current investigation and whether a most recent risk assessment was recorded, 27) whether a patient's risk of pressure injury has been determined, 28) whether a pressure injury prevention regimen for a high risk patient has been implemented within the past 24 hours, a method of determining a risk of pressure injury for a patient, 29) Whether a skin assessment was recorded over the past 24 hours, 30) whether a pressure redistribution surface was used over the past 24 hours, 31) whether the patient was repositioned as ordered over the past 24 hours, 32) whether the patient had nutritional support over the past 24 hours, 33) humidity management was used for the patient over the past 24 hours (e.g., using a low wind pressure loss feature or a microclimate management feature of the surface), 34) whether patient constraints were used, 35) the type of constraints used, 36) the category of constraints used, 37) the reason for the use of constraints, 38) whether continuous venous-hemofiltration (CVVH)/continuous venous-hemodiafiltration (CVHD)/femoral line is being used on the patient, 39) whether the patient has diabetes, 40) whether adventitia extracorporeal membrane (ECMO) is being used on the patient, 41) Whether the patient has sepsis, 42) whether the patient has vascular disease, 43) whether vasopressor is being administered to the patient or the patient's Mean Arterial Pressure (MAP) is low, 44) whether the patient is ventilated, 45) whether the patient has pressure injury, 46) details of the pressure injury (e.g., the location of the wound, such as the right or left heel, sacrum, scapula, etc.; stage of each wound; whether each wound was present at the time of admission; whether each wound is present upon arrival at the ward; and wound record), 47) whether a pressure injury is associated with the device, 48) the type of device (if the answer to 47 is yes), and 49) the number of days from admission to recording of the pressure injury (if the pressure injury was caused by the device). Data from the IPUP survey is among the data transmitted to the analysis engine 20. It should be understood that IPUP survey data is entered by a caregiver using a PC or tablet computer or some other computer device.

In accordance with the present disclosure, the analysis engine 20 processes data received from the source 12 and performs a risk assessment for the relevant patient. As discussed in further detail below, the risk assessment includes determining a patient's risk of developing sepsis, a patient's risk of developing a pressure injury (e.g., pressure sores or bedsores), and a patient's risk of potentially falling. These are referred to herein as sepsis risk assessment, stress injury risk assessment, and fall risk assessment. The present disclosure contemplates that analysis engine 20 can perform other risk assessments of the patient based on data received from source 12. These risk assessments depend on the type of source 12 providing the data, as well as the identification of relatively close correlations between data from multiple sources 12 and a particular patient risk.

Still referring to FIG. 1, the risk assessment is provided to a caregiver or clinician who may adjust or override the risk assessment based on clinical insight 24. The terms "caregiver" and "clinician" are used interchangeably herein. Adjusting or overriding the risk assessment based on the clinical insight 24 is accomplished using a computer (not shown), such as a personal computer at a workstation, a main nurse computer at a main nurse station, a mobile device carried by a caregiver, such as a smart phone or tablet, or the like. In some embodiments, each risk assessment produces a score within a numerical range that is between and includes an upper limit and a lower limit. Thus, the caregiver can alter the risk assessment score output from the analysis engine 20, if such adjustment is necessary or desirable based on the caregiver's information about the patient and the caregiver's experience.

Based on the risk assessment made by the analysis engine 20 and adjustments made by the caregiver based on the clinical insight 24 (if any), the risk assessment is used to determine clinical services and measures 26 as indicated in FIG. 1. The ultimate goal of the risk assessment made by the analysis engine 20 and the clinical services and measures 26 implemented is to improve the treatment outcome of the patient as indicated by the breakthrough treatment outcome box 28 of fig. 1. For example, if the patient has sepsis or has a high risk assessment of sepsis, the clinician may implement one or more of the following services and measures 26 (also referred to as a sepsis regimen): providing a high flow of oxygen to a patient; blood is drawn for laboratory testing, such as testing lactate and hemoglobin levels; providing an Intravenous (IV) antibiotic; providing an IV fluid; and urine output measurements were taken every hour.

If the patient has stress injuries or has a high risk assessment of stress injuries, the clinician may implement one or more of the following services and measures 26 (also known as stress injury regimens): patient support surface therapy, such as continuous lateral transfer therapy (CLRT) or alternating pressure therapy; applying a vacuum wound bandage to any pressure sore or wound of the patient; capturing wound images for individual wound assessment; and monitoring the patient's activities to ensure that the patient repositions himself on the patient bed 14 appropriately and frequently.

If the patient has a fall risk or has a high risk assessment of a fall, the clinician can implement one or more of the following services and measures 26 (a.k.a. fall scenario): enabling a fall risk profile on the patient bed 14, such that the patient bed circuitry and/or a remote computer (e.g., a bed state computer or a nurse call computer) monitors the patient's position on the patient bed 14, monitors the side fence positions to confirm that the designated side fence is in its raised position, monitors the caster brake status to confirm that the casters have been braked, and monitors the position of the upper frame of the patient bed 14 to confirm that it is in a lower position relative to the undercarriage of the patient bed 14; providing an incontinence detection pad of an incontinence detection system 16 between the patient and a mattress of the patient bed 14; providing a walker beside a patient bed; and providing sufficient food and/or water in the vicinity of the patient.

Referring now to fig. 2, a schematic diagram illustrates various activities occurring around a patient bed 14, and further discloses aspects of a Digital Safety Net (DSN) platform 30 based on these activities, wherein the DSN platform includes an analysis engine 20. The DSN platform also includes a power over ethernet (PoE) switch, router, or gateway 32 (these terms are used interchangeably herein) that receives data from a plurality of sources 12, including the patient bed 14, and routes risk assessment information to a plurality of output devices 34, the plurality of output devices 34 including a graphical display 36 and an indicator 38 (also referred to as a dome light) of a nurse call system that provides visual information regarding the risk assessment performed by the analysis engine 20.

Below the top left image of fig. 2, a bulletin indicates that there is a hospitalized patient on the patient bed 14 and that a preliminary evaluation has been made for that patient. In conjunction with the initial assessment, the patient's medical history is recorded, initial vital signs and weight of the patient are obtained, baseline pressure injury risk is assessed, and camera 40 (e.g., wondvue available from LBT Innovations ltd. of adelaid, australia) is used^TMCamera 40) takes a picture of a suspected pressure injury and uploads it to analysis engine 20 for wound assessment. The arrow 42 located between the top left image and the top center image of fig. 2 indicates that the data associated with the bullet below the top right image is transferred to the analysis engine of the DSN platform 30 of the top center image.

Below the upper central image of fig. 2, the bullets indicate: the analysis engine 20 of the DSN platform 30 is involved in a sepsis scenario associated with assessing a patient's risk of sepsis; patients have been graded or normalized for sepsis risk to a score range of 1 to 5 points; the condition of the patient is being monitored, including monitoring the body temperature of the patient, the movement of the patient, and the surface condition of the patient support surface (also referred to as a mattress) of the patient bed 14. According to the present disclosure, the DSN platform 30 is also involved in a fall regime related to assessing the risk of falling for a patient, as well as in a pressure injury regime related to assessing the risk of pressure injury for a patient. In the illustrative example, the fall risk and the stress injury risk are also ranked or normalized by the analysis engine 20 to a score range of 1 to 5. In other embodiments, the risk range for each of sepsis, fall, and pressure injury risk is 0 to 5. Thus, each of the sepsis, fall, and pressure injury risks has the same maximum value (e.g., 5 in the illustrative example) and the same minimum value (0 or 1 in the illustrative example). In other embodiments, different risk ranges are used, such as those ranges having an upper limit greater than 5 (including 10, 20, 25, 30, etc.).

Also below the upper central image of fig. 2, the bullets indicate: the risk level or score determined by the analysis engine 20 of the DSN platform 30 is displayed on the output device 34 of the entire DSN platform 30 (i.e., at multiple locations throughout the medical facility), and the ward visit is adjusted based on the risk score determined for one or more of the patient's sepsis, fall, and stress injury risks. For the graphical display 36, the actual value of the score is displayed in some embodiments; while for the dome light 38, a portion of the dome light is lit in a particular manner based on the risk score. For example, if any risk score is 4 or 5, a red light may be illuminated on the dome light 38, but if each risk score is only 2 or 3, a yellow or amber light may be illuminated on the dome light 38. If the risk scores are all at a lower level (e.g., 0 or 1 as appropriate), the portion of the dome light associated with patient risk remains unlit. This lighting scheme of the dome light 38 is given as one illustrative example, other lighting schemes are within the scope of the present disclosure, including assigning a portion or segment of the dome light 38 to each risk score, such that the dome light 38 has three risk light zones corresponding to sepsis, fall, and stress injury risks, each risk light zone being lit red, yellow/amber, or unlit for different risk level scores of the associated risk. Other areas on the dome light indicate: for example, whether the caregiver is in the room, whether the patient in the room has placed a nurse call, or whether the device alarm in the room is on, and including for a semi-private room which of the two patients has placed a nurse call, or which patient is associated with the device that is being alerted. Dome lamps having colors other than red and yellow/amber (e.g., white, green, blue, purple, etc.) are within the scope of the invention.

For adjusting the rounds, in some embodiments, if one or more risk scores are high (e.g., level 4 or level 5), or if the risk score increases from one level to the next (e.g., from level 2 to level 3), the time between rounds of the caregiver (i.e., the time interval during which the assigned caregiver is required to view the patient) is shortened. The present disclosure contemplates that the higher the risk score, the shorter the ward visit interval will be. The correlation between the time between rounds and the risk score ratings, including adding two or three risk scores together to determine the rounds interval, is determined by the system programmer or administrator. The arrow 44 located between the upper center image and the upper right image of fig. 2 indicates that after the DSN platform 30 has performed activity related to the bullets below the upper center image, the patient bed 14 and vital signs device 18 (and other devices disclosed herein) continue to provide data to the analysis engine 20 for dynamic, real-time risk assessment.

In some embodiments, the adjustment of the ward visit interval occurs dynamically, automatically, and substantially in real time as the risk score increases and decreases. Thus, if the risk score increases, for example, from level 3 to level 4, the ward-visit interval will automatically decrease from 4 hours to 2 hours; for example, if the risk score decreases from level 4 to level 3, the ward-round interval may increase from 2 hours to 4 hours, giving only an arbitrary example to illustrate this concept. In some embodiments, the ward visit interval is tracked and changed by an EMR computer or server or a nurse calling a computer or server. In some embodiments, the ward-visit interval adjustment is performed on a computer or server that controls the ward-visit interval without manual input or involvement. In other embodiments, a caregiver or clinician or other administrator at the ward's computer provides input to approve the ward interval change. In either case, in some embodiments, a room-visit interval change notification is sent to one or more mobile devices of the affected caregivers.

The phrase "substantially real-time" as used herein refers to the amount of time that a data measurement or value affecting a risk score is received and processed to recalculate the risk score. Some devices 12 may provide only one reading per minute or second, while other devices may provide 100 readings per second, to give just some arbitrary examples. The present invention contemplates that the analysis engine 20 recalculates the risk score each time a new data point is received, and in accordance with the present invention, this situation is considered "substantially real-time". The present disclosure also contemplates that analysis engine 20 recalculates the risk score only when the received measurement or value is changed from the previous measurement or value. Thus, if a constant value is repeatedly transmitted, the analysis engine does not recalculate the risk score until a change in one of the influential measurements or values occurs, and this is also considered "substantially real-time" in accordance with this disclosure.

Below the upper right image of fig. 2, the bullets indicate: dynamic patient risk assessment by the analysis engine 20 includes continuously monitoring whether the patient support surface condition is consistent with a reduced risk of pressure damage, or whether the patient support surface condition has changed in a manner that creates an increased risk of pressure damage. For example, if the air cells of the mattress of the patient bed 14 leak and a sufficient amount of air is lost, the air cell pressure may drop sufficiently to bottom out the patient through the mattress to be supported on the underlying mattress support panel rather than by the air cells. This situation increases the risk that the patient may suffer pressure injury. In accordance with the present disclosure, dynamic risk assessment by analysis engine 20 also includes monitoring whether patient vital signs sensed by monitor 18 or vital signs sensors on the patient bed are consistent and within a desired range, or whether the vital signs are changing in a manner indicative of a decline in patient health. If the latter condition is detected, the sepsis risk score for the patient may be increased. Further in accordance with the present disclosure, the dynamic risk assessment by the analysis engine 20 also includes determining whether the patient is sleeping in the room, in which case the patient's fall risk score decreases, or whether the patient is moving, fidgeting, or in pain, in which case the patient's fall risk score increases. As the patient risk score increases or decreases, the patient's clinical regimen is adjusted in a commensurate manner to match the changing risk level.

The arrow 46 located between the top right image and the bottom right image of fig. 2 indicates: after a period of time, other conditions of the patient on the patient bed 14 may be detected. As indicated by the legend below the lower right hand diagram of fig. 2, if a patient change is detected by the patient bed 14, e.g., no patient motion for an extended period of time or patient motion below a threshold, and/or if a problematic surface change is detected, the pressure impairment algorithm executed by the analysis engine 20 determines that the risk of pressure impairment is increased and the pressure impairment score of the patient is increased. Further, in response to the increased stress injury score, the analysis engine 20 issues one or more alerts to one or more caregivers regarding an increased risk of stress injury, and in some embodiments automatically activates a stress injury prevention scheme, such as automatically reducing the time to ward visit and/or implementing a surface treatment scheme, such as sending a reminder message to the caregivers to turn the patient, periodically (e.g., every hour or every two hours) activate a turn assist function of the patient bed 14, activate alternating pressure therapy of the mattress of the patient bed 14, or activate CLRT therapy of the mattress of the patient bed 14.

DSN platform 30 responds in a similar manner to alert caregivers of the score increase if analysis engine 20 receives data from patient bed 14 or vital signs detector 18, thereby causing a fall risk score or sepsis risk score to increase. For example, an increased patient heart rate with increased patient motion may indicate that the patient is preparing to leave the bed 14, and the fall risk score may increase accordingly. As another example, if the patient's heart rate or respiration increases, but there is no patient motion or the patient motion is below a threshold, thereby indicating that the patient is asleep, this may indicate an increased risk of sepsis and the sepsis risk score may increase accordingly.

In each instance that these risk scores are increased, in some embodiments, the analysis engine 20 initiates an alert to one or more caregivers assigned to the patient. Such alerts may be sent to mobile devices (e.g., pagers, Personal Digital Assistants (PDAs), smart phones, or tablet computers) carried by the respective one or more caregivers. Such alarms may also be displayed on the graphical display 36 and dome lights 38 of the system 10. As with the increase in the stress-impairment score, the analysis engine 20 may automatically initiate a fall risk protocol or a sepsis protocol in response to an increase in the fall risk score or an increase in the sepsis risk score, respectively.

In accordance with the present disclosure, the analysis engine 20 also provides risk score data or messages to the source 12, such as the patient bed 14 and monitor 18, which is equipped with communication circuitry configured for bidirectional communication with the analysis engine 20. Thus, in some embodiments, messages received by one or more sources 12 from analysis engine 20 may cause a risk reduction scheme or function of source 12 to be automatically activated (e.g., an alternating pressure function of a mattress is automatically turned on or an infusion pump for injecting IV antibiotics is automatically turned on, or a bed exit/patient position monitoring function of a bed is automatically turned on). In some embodiments, the graphical display of the source 12 (e.g., the patient bed 14 and the detector 18) receiving such messages from the analysis engine 20 displays a message indicating that one or more of the stress injury, fall, and sepsis risk scores has increased, and, where appropriate, that the risk reduction protocol or function of the source 12 has been automatically turned on or activated.

An arrow 48 located between the bottom right and bottom left images of fig. 2 indicates that the caregiver has been assigned to the room of the patient with the increased risk score. Thus, as indicated by the bullet below the bottom left image of fig. 2, in response to an increase in the stress injury score, fall risk score, or sepsis risk score, the analysis engine 20 issues an alert or notification to one or more assigned caregivers to go immediately to the patient's room and attend to the patient. When the caregiver arrives at the patient's room, some of the risk factors that result in an increase in the risk score may be resolved at this time. For example, in response to an increase in the fall risk score, the caregiver may assist the patient in going to the toilet, or the caregiver may turn on a mattress roll assist or treatment function for the patient with the increased stress injury risk score, or the caregiver may initiate an IV antibiotic injection for the patient with the increased sepsis risk score.

After the caregiver addresses the patient's fall risk, stress injury, and/or sepsis needs, in some cases, the data provided to the analysis engine 20 will result in an automatic reduction in the corresponding risk score. However, in some cases, after the caregiver has addressed the patient's needs, the caregiver provides the clinical insight 24 to the analysis engine 20 that results in a reduction in the risk score. In the event that the stress injury score increases, in some embodiments, a caregiver assigned to the patient's room may be required to take a picture of any stress injury of the patient using camera 40 to upload to analysis engine 20 in order to use the latest stress injury data to determine the stress injury score of the patient.

Referring now to fig. 3, there is shown the other source 12 of the system 10 providing data to the analysis engine 20 through the router or PoE switch 32. Other sources 12 of fig. 3 include a graphics room station 50, a patient lift 52, and a positioning system 54. The graphical room station 50 is included as part of a nurse call system, such as that available from Hill-Rom Company, inc

The nurse calls the system. Additional details of suitable nurse call systems including room stations 50 may be found in U.S. patent nos. 7,746,218; 7,538,659 No; 7,319,386 No; 7,242,308 No; 6,897,780 No; 6,362,725 No; 6,147,592 No; 5,838,223 No; 5,699,038 and 5,561,412 and U.S. patent application publication No. 2009/0217080a 1; 2009/0214009A 1; 2009/0212956A 1; and 2009/0212925A1, the entire contents of which are incorporated by reference herein without any conflict with the present disclosure to the extent that any conflict arises. The room station 50 is one of the sources 12 that the caregiver uses to provide the clinical insight 24 to the system 10 for analysis by the analysis engine 20.

The patient lift 52 provides data to the analysis engine 20 through the router 32 in response to being used to lift a patient from the patient bed 12 for transfer to, for example, a stretcher, chair, or wheelchair. The fact that the patient lift 52 is required to move the patient into or out of the bed 14 indicates that the patient is at risk of falling because the patient cannot leave the bed 14 and walk or return to the bed 14 on his or her own. Thus, the analysis engine 20 increases the fall risk score in response to the patient hoist 52 being used to move the patient. In addition, using the patient lift 52 to move a patient into or out of the patient bed 14 may also indicate that the patient is at a higher risk of pressure injury than an ambulatory patient. For example, the elevator 52 is typically used to transfer paraplegic or quadriplegic patients who have limited ability to transfer their weight while in bed to reduce the chances of pressure injury. Furthermore, slings used with patient lifts sometimes create high interface pressures in certain parts of the patient (e.g., the hip or sacral regions of the patient), which may also increase the risk of pressure injury. Thus, in some embodiments, the use of the elevator 52 results in an increase not only in the fall risk score of the patient, but also in the stress-injury score of the patient.

An illustrative image of the patient lift 52 in fig. 3 is an overhead lift 52 attached to a frame mounted in a patient room. Other types of patient lifts 52 include a mobile patient lift that is pushed into the patient room for use. Included in fig. 3 is a set of wireless communication icons 56 for indicating that some of the sources 12 of the network 10 are in wireless communication with the gateway 32, for example, through one or more wireless access points (not shown). In particular, icon 56 of fig. 3 indicates that patient bed 14, monitor 18, patient lift 52, components of positioning system 56, and components of incontinence detection system 16 are in wireless communication with gateway 32. The lines in fig. 3 extending from source 12 to gateway 32 indicate that the source may communicate with gateway 32 through a wired connection in addition to or instead of wireless communication.

In some embodiments, the wireless communication enabled source 12 has dedicated circuitry for this purpose. Alternatively or additionally, the positioning tags of positioning system 54 are attached to source 12, such as the components of patient bed 14, monitor 18, patient lift 52, and incontinence detection system 16. In some embodiments, the location tag of system 54 is also attached to the caregiver and/or the patient. The location tags include transmitters for transmitting wireless signals to receivers or transceivers mounted at various fixed locations throughout the medical facility. In some embodiments, the tag has a receiver or transceiver that receives wireless signals from a fixed transceiver. For example, to conserve battery power, a location tag may only transmit information, including tag Identification (ID) data, in response to receiving a wireless signal from one of the fixed transceivers. The stationary receivers or transceivers communicate the location ID (or the stationary receiver/transceiver ID associated with the location of the medical facility) to a location server remote from the respective stationary transceivers. Based on the tag ID and location ID received by the location server, the location server determines the location of the various tagged devices, tagged caregivers, and tagged patients of the source 12.

In view of the foregoing discussion, in some embodiments, if the positioning system 54 determines that the mobile patient lift 52 is located within the patient's room, the analysis engine increases the stress injury risk score and/or fall risk score for the patient. If location system 54 determines that a device is in the patient's room, analysis engine 20 may similarly increase the sepsis risk score. For example, in some embodiments, if the heart rate monitor, the respiratory rate monitor, and the blood pressure monitor are all placed in the patient's room for a threshold period of time, the sepsis risk score is increased by the analysis engine 20. In some embodiments, if a bag or vial of IV antibiotics in the patient's room is tagged with a location tag, the sepsis risk score is increased by the analysis engine 20.

If the incontinence detection pad of the incontinence detection system 16 is determined to be located in the patient's room, either as a result of detection of a location tag attached to the pad by the location system 54, or as a result of detection of the incontinence detection pad by circuitry of the hospital bed 14, or in some embodiments, as a result of a reader of the incontinence detection system 16 providing data to the analysis engine 20, possibly through a nurse call system, then in some embodiments the fall risk score of the patient and/or the stress injury score of the patient are increased by the analysis engine 20. The use of an incontinence detection pad on the patient indicates that the patient is not sufficiently mobile to have taken up from the bed 14 to a restroom and, therefore, is among the fall-risk patients. Furthermore, the use of an incontinence detection pad on the patient indicates that the patient may be confined to the hospital bed 14, which increases the risk of pressure injuries occurring. In some embodiments, in response to the incontinence detection system 16 detecting that the patient has soiled the incontinence detection pad and that the pad thereafter remains below the patient for a threshold amount of time before being replaced with an unsoiled pad, the pressure injury risk score is increased by the analysis engine because prolonged exposure to moisture or humidity increases the likelihood of pressure injury to the patient.

In some embodiments, the positioning system 54 operates as a high precision positioning system 54, the high precision positioning system 54 being capable of determining the position of each positioning tag in communication with at least three fixed transceivers within one foot (30.48 centimeters) or less of the actual position of the tag. One example of a high-precision positioning system 54 contemplated by the present disclosure is an ultra-wideband (UWB) positioning system. UWB positioning systems operate in the frequency range of 3.1GHz to 10.6 GHz. Suitable fixed transceivers in this regard include WISER mesh antenna nodes (WISER mesh antenna nodes), and suitable location tags in this regard include micro-tracker tags, all of which are available from WISER Systems, inc^TMAnd (5) selling the system. Other manufacturer-supplied UWB location systems may also be used. In some embodiments, high precision positioning system 54 uses two-way ranging, clock synchronization, and time difference of arrival (TDoA) techniques to determine the position of the positioning tag. For a detailed discussion of the use of these techniques in UWB positioning systems, see, for example, international publication No. WO2017/083353a1, the entire contents of the teachings of which are incorporated herein by reference without conflict with the present disclosure, to the extent that any conflict arises, the present disclosure controls.

In those embodiments in which positioning system 54 is a high precision positioning system 54, a more elaborate set of rules for determining whether to increase or decrease a particular risk score may be implemented by analysis engine 20. For example, rather than increasing the fall risk score and/or the stress injury score in response to detecting that the patient lift 52 is in the room or detecting that the incontinence detection pad is in the room, the particular risk score may only increase when the relative position between the lift 52 or incontinence detection pad and the patient bed 14 meets a particular criterion. For example, the fall risk and/or stress injury risk score does not grow until the motor-elevator housing and/or boom of the overhead hoist 52 is determined to be above the footprint of the hospital bed 14. This may prevent the risk score from increasing or growing when the overhead hoist 52 is not used for a particular patient, but is merely stored alongside the patient bed 14 or in a corner of a room. Similarly, the fall risk and/or stress injury risk score does not increase until the mobile lift 52 is determined to be within a threshold distance, such as 1 or 2 feet from the patient bed 14 or patient (to give just some arbitrary examples). Further similarly, the fall risk and/or stress injury risk score does not increase until the incontinence detection pad is determined to be within the coverage area of the hospital bed 14.

Still referring to FIG. 3, the graphical display 36 of the output device 34 includes a status panel 58, a graphical room station 50, and a caregiver's mobile device 60. The exemplary mobile device 60 of fig. 3 is a smart phone, but as noted above, the mobile device 60 also includes a pager, a Personal Digital Assistant (PDA), a tablet computer, and the like. The status board 58 is typically located at the main nurse's station in the medical facility, but may be located elsewhere, such as staff rest rooms, corridors, etc., if desired. In some embodiments, the status board 58 is included as part of a nurse call system. In this regard, see, for example, U.S. patent No. 8,779,924, the entire contents of which are incorporated herein by reference without conflict with the present disclosure, to the extent that any conflict arises, the present disclosure controls. The present disclosure contemplates that the status panel has additional fields for displaying on the status panel a fall risk, a stress injury risk, and a sepsis risk score for each listed patient.

As shown in FIG. 3, the graphical room station 50 serves as both a source 12 for providing data to the analysis engine 20 and an output device 34 for displaying data from the analysis engine 20. Thus, the graphical room station 50 also has a display screen with fields for displaying fall risk, stress injury risk and sepsis risk scores for patients located in the room with the room station 50. In some embodiments, the station 50 may be operable to obtain and display risk scores for patients located in other rooms. Thus, a caregiver using the room station 50 in one room may communicate with another caregiver (e.g., a nurse at the primary nurse station) about a patient located in another room, and may extract information related to the other patient in question, including a risk score.

The mobile device 60 also has a screen with a column for displaying a patient risk score. In some embodiments, the caregiver's mobile device 60 is equipped with a mobile software application that operates to limit the caregiver's ability to access information, such as being able to view only the risk scores of patients assigned thereto, but not those assigned to other caregivers. Further, the present disclosure contemplates that a pop-up window appears on the caregiver's mobile device whenever the risk score for any patient assigned to the caregiver changes. Examples of screens that appear on the mobile device 60 in some embodiments are discussed below in conjunction with fig. 7-10.

An Electronic Medical Record (EMR) or Health Information System (HIS) server 62 is also communicatively coupled to the analysis engine 20 through the PoE switch 32, as shown in the illustrative example of fig. 3. The server 62 is connected to one or more EMR or HIS computers (not shown) having display screens for displaying risk scores for individual patients in the medical facility. In some embodiments, the server 62 is also the data source 12 for use by the analysis engine 20 in determining the risk score for each patient. As shown in fig. 3, the analytics engine 20 is also communicatively coupled to an internet of things (IoT) network or platform 64 through the gateway 32. Platform 64 receives information from a plurality of medical institutions and operates to analyze the input information to identify best practices for risk reduction programs that may, in turn, be shared with other medical institutions that may subscribe to receive such best practice information. Best practice information may include, for example, relevant thresholds used in risk assessment algorithms, steps implemented in the standard of care to minimize patient risk, and corrective actions taken in response to an increase in the patient risk score. Platform 64 may also, for example, perform analysis for predicting patient treatment outcomes and communicate the predicted outcomes to a subscribing medical facility.

As shown in FIG. 3, the analysis engine 20 is in bi-directional communication with some or all of the sources 12, output devices 34, servers 62 and platforms 64. The analysis engine 20 includes one or more servers or other computers that implement analysis software configured according to the various algorithms and rules discussed above. It should be understood that fig. 1-3 are schematic in nature and that other network infrastructures communicatively interconnect each of the devices of the system 10 discussed above in each of the medical institutions in which the system or apparatus 10 is implemented. Another illustrative example of a network infrastructure is discussed below in conjunction with fig. 6.

Referring now to fig. 4A-4C, a flow chart 70 shows an example of a patient's course that begins with an Emergency Department (ED) indicated at block 72 or a surgical room indicated at block 74, then passes to an Intensive Care Unit (ICU) or medical/surgical (MED/SURG) room indicated at block 76, and then returns home or to a Long Term Care (LTC) facility or a professional care (SNF) facility as indicated at block 78. Flow chart 70 shows the operation of the analysis engine 20 of the DSN platform 30 in a patient procedure to determine the location of a patient at risk of having or developing sepsis. DSN platform block 80 is shown regardless of where in flowchart 70 DSN platform 30 is invoked for patient risk assessment of sepsis.

Referring now to fig. 4A, the patient arrives at the hospital at ED 72, as shown at block 82, and is classified and sepsis screened, as shown at block 84. The purpose of this initial screening was to discover sepsis early, as shown by early detection cloud 86 above ED 72. Information from the screening at block 84 is provided to the DSN platform 30 as shown in related block 80, and a determination is then made as shown at block 88 whether the patient is suspected of having sepsis. As shown by the communication cloud 90 above block 88, the analysis engine 20 makes the determination at block 88 based on information communicated from the DSN 30.

If it is determined at block 88 that sepsis is suspected, the patient is tested for prescribed Lactic Acid Culture (LAC) and Complete Blood Count (CBC) as indicated at block 92. Lactic acid in blood of more than 2 millimoles per liter (mmol/L) is one of the indicators that patients have sepsis. According to certain sepsis determination protocols, this lactate level in the blood is considered along with other sepsis risk factors including one or more of the following: i) systolic blood pressure below 90 millimeters of mercury (mmHg) or mean arterial blood pressure below 65 mmHg; ii) heart rate greater than 130 beats per minute; iii) a respiration rate greater than 25 breaths per minute; iv) oxygen saturation (e.g., SpO2) less than 91%; v) the patient does not respond or responds only to sound or pain; and/or vi) the appearance of purpuric rash. According to other sepsis determination protocols, sepsis is determined to be likely if the following criteria are met: i) the patient's body temperature is above about 38.3 degrees celsius (° c) (about 101 degrees fahrenheit (° F)) or below about 35.6 ℃ (about 96 ° F); ii) the heart rate of the patient is greater than 90 beats per minute; iii) the patient has a breathing rate greater than 20 breaths per minute. Thus, different medical institutions have different sepsis determination protocols, all of which are within the scope of the present disclosure.

Following the blood test at block 92, it is determined whether the patient has sepsis as indicated at block 94. If the patient has sepsis as determined at block 94, a 3 hour (Hr) protocol package (3 hrunble) is initiated as indicated at block 96. The 3Hr regimen includes, for example, administration of a broad spectrum antibiotic and administration of 30 milliliters per kilogram (mL/kg) crystals for hypotension or lactic acid greater than or equal to 4 mmol/L. In some medical facilities, the 3Hr protocol package may also include measuring lactate levels and obtaining blood cultures, but in fig. 4A, these operations are completed at block 92 before the 3Hr protocol package is initiated at block 96. Above block 96 is a correct billing code cloud 97 and a protocol package compliance cloud 98, which may, in some embodiments, invoke monitoring results and feedback to the caregiver via the DSN platform 30 or HIS server 62.

Block 100 at the top of FIG. 4A includes bullet symbols indicating devices and systems for use with portions of the flowchart 70 shown in FIG. 4A. In particular, block 100 lists a multi-parameter vital signs device, a physical assessment device, a patient bed, an ECG cart, and a clinical workflow (nurse call) system. In some embodiments, these systems and devices are the sources 12 of the analytics engines 20 of the DSN platform 30. Block 102 at the bottom of fig. 4A includes bullets indicating aspects of the DSN platform 30 used with the portion of the flow diagram 70 shown in fig. 4A. In particular, block 102 lists advanced analysis (e.g., analysis engine 20) for enhancing clinical decision and early detection of conditions, smart sensing beds or stretchers (e.g., bed 14 with vital sign sensors or integrated incontinence detection system 16), wearable or contactless parameter sensing (e.g., some embodiments of monitor 18), integration of parameters from multiple company sources (e.g., vital sign monitors 18 of various companies), and a mobile communication platform (e.g., mobile device 60 of a caregiver) for optimizing workflow.

If sepsis is not suspected at block 88 of fig. 4A or if it is determined at block 94 of fig. 4A that the patient does not have sepsis, the patient is admitted to a medical facility and sent to a medical/surgical room as indicated at block 76 of fig. 4B (next). In some embodiments, information regarding unsuspecting sepsis or determining not to have sepsis at blocks 88, 94 may be communicated to the analysis engine 20 of the DSN platform 30 associated with the patient being sent to the medical/surgical room. Thus, as shown in block 76 of fig. 4B (continuation), two of the three flow paths exiting from the right hand side of fig. 4A result in the patient being admitted and taken to the medical/surgical room. As shown in fig. 4B, assume that the patient arrives at the hospital's surgical room 74 for surgery, rather than arriving at an emergency room, as indicated by block 104 within the surgical room 74. Thereafter, the patient is operated on, as indicated at block 106 of fig. 4B. As shown in block 108 of fig. 4B, during or after surgery, the patient's vital signs are measured in the surgical room 74 and the patient is screened for sepsis. In this regard, the early detection cloud 86 is also shown above the surgical room 74 in fig. 4B.

After surgery, the patient's vital sign information and sepsis screening information from block 108 is provided to the analysis engine 20 of the DSN platform 80, and the patient is admitted to the medical facility and sent to the medical/surgical ward as shown in block 76 of fig. 4B (continuation). After the patient is brought into the medical/surgical ward at block 76, Q4 vital signs and Best Practices Alerts (BPA) for sepsis are implemented as shown at block 110 and associated data is provided to the analysis engine 20 of the DSN platform as shown at block 80 adjacent to block 110. Q4 vital signs are vital signs acquired at 4 hour intervals, such as 8 am, noon, 4 pm, 8 pm, midnight, 4 am, etc. Early detection cloud 86 and data frequency cloud 112 are shown above box 110 in fig. 4B (continuation). Thus, the cloud 112 above the box 110 indicates that the caregiver can change the frequency of acquiring patient vital signs to Q1, Q2, or Q8 (i.e., one, two, or eight hours apart, respectively, rather than four hours apart) based on the clinical insight 24.

Based on the data obtained with respect to block 110, a determination is made as to whether the patient is suspected of having sepsis as indicated in block 114. If it is determined at block 114 that it is not suspected of having sepsis, the workflow 70 returns to block 110 and continues from block 110. If at block 114 it is determined that sepsis is suspected, the patient is subjected to ordered LAC and CBC tests as indicated at block 116. The LAC and CBC tests are discussed above in connection with block 92 of fig. 4A, with the same discussion applying to block 116 of fig. 4B (next). The results of the LAC and CBC are passed to the analytics engine 20 of the DSN platform 30 as indicated by block 80 above block 116 in fig. 4B (continuation).

Based on the results of the LAC and CBS tests at block 116, it is determined whether the patient has sepsis as shown at block 118. If it is determined at block 118 that the patient does not have sepsis, the workflow 70 returns to block 110 and continues from block 110. If the patient has sepsis as determined at block 118, a 3Hr regimen package is initiated as shown at block 120. The 3Hr scenario package is discussed above in connection with block 96 of fig. 4A, and the same description applies to block 120 of fig. 4B (continuation). Above block 120 is the correct billing code cloud 97 and the protocol package compliance cloud 98, which in some embodiments may invoke monitoring results and feedback to the caregiver through the DSN platform 30 as shown in block 80 to the right of block 120 or through the HIS server 62. After the 3Hr protocol package is initiated at block 120 of fig. 4B (continue), the patient is evaluated as shown at block 122 of fig. 4B (continue).

Block 124 at the top of FIG. 4B includes a bullet indicating a device and system for use with the portion of the flowchart 70 shown in FIGS. 4B and 4B (continuation). In particular, block 124 lists a multi-parameter vital signs device, a physical assessment device, a patient bed, a clinical workflow (nurse call) system, a real-time location plan (RTLS), a patient monitoring plan, a clinical consultation service, an ECG cart, and a patient movement plan. In some embodiments, the systems (or schemes) and devices of block 124 are the sources 12 of the analytics engine 20 of the DSN platform 30. Block 126 at the bottom of fig. 4B (continuation) includes bullet symbols indicating aspects of DSN platform 30 for use with the portions of flow chart 70 shown in fig. 4B and 4B (continuation). In particular, block 126 lists advanced analysis (e.g., analysis engine 20) for enhancing clinical decision and early detection of patient deterioration, wearable or contactless parameter sensing (e.g., some embodiments of monitor 18), smart sensing beds (e.g., bed 14 with vital sign sensors or integrated incontinence detection system 16), integration of parameters from multiple company sources (e.g., vital sign monitors 18 of various companies that output vital signs including cardiac output), and mobile communication platforms (e.g., mobile device 60 of a caregiver).

After launching the 3Hr protocol package of block 96 of fig. 4A, the patient is evaluated as shown in block 128 of fig. 4B, and data regarding the 3Hr protocol package is provided to the analysis engine 20 of the DSN platform 30 as shown in block 80 to the left of block 128 in fig. 4B. The data obtained during the patient assessment at block 128 is provided to the analysis engine 20 of the DSN platform as shown at block 80 to the right of block 128. In the illustrative example, after the analysis engine 20 of the DSN platform has analyzed the data from the patient assessment of block 128, the 6Hr protocol package is launched as shown in block 130. In some embodiments, the 6Hr scheme package comprises: administering a vasopressor to maintain MAP greater than or equal to 65 mmHg; measuring Central Venous Pressure (CVP); measuring central venous blood oxygen saturation (S)_CVO2) (ii) a And re-measuring the lactic acid if the initial lactic acid level increases. The 6Hr protocol package may vary from institution to institution. Following the 6Hr protocol package of block 130, the patient is again evaluated as shown in block 132, and the data from the evaluation (including information about the steps of the 6Hr protocol package of block 130) is provided to the analysis engine 20 of the DSN platform 30 as shown in block 80 to the right of block 132 in fig. 4B.

If the patient assessment at block 122 or block 132 (as the case may be) indicates that the patient is no longer septic (as is the case in the illustrative example of flowchart 70), the patient is discharged home or transferred to the LTC facility or SNF facility, as shown at block 78 of fig. 4C. A home monitoring readmission cloud 134 is located above block 78 for indicating that it is contemplated to continue monitoring the patient's condition at home. In this regard, block 136 at the top of FIG. 4C includes bullets that indicate devices and systems used with portions of the flowchart 70 shown in FIG. 4C. In particular, block 136 lists home health monitoring (blood pressure and weight scale), mobile cardiac monitoring (including vital signs monitoring devices 18, such as mobile blood pressure monitors (ABPM), Holter monitors, and/or TAGecg devices), and airway clearance devices. In some embodiments, these in-home devices of block 136 are also the source 12 of the analytics engine 20 of the DSN platform 30. Thus, in some embodiments, such a source 12 for use in the home communicates with the analysis engine 20 over the internet.

Block 138 at the bottom of fig. 4C includes bullets indicating various aspects of the DSN platform 30 for use with the portion of the flow diagram 70 shown in fig. 4C. In particular, block 138 lists advanced analysis (e.g., analysis engine 20) for early detection of patient conditions at home, multi-parameter remote patient monitoring and related communication platforms, wearable or contactless parameter sensing (e.g., some embodiments of monitor 18), smart sensing beds (e.g., bed 14 with vital sign sensors or integrated incontinence detection system 16), and integration of parameters from multiple company sources (e.g., vital sign monitor 18 outputting vital signs from various companies).

Referring now to fig. 5A and 5B, a flow chart 140 is provided that illustrates an example of a patient admitted to and hospitalized in a medical facility (including using equipment in the patient's room to move the patient), and illustrates the location in the patient flow where the analysis engine 20 operates to perform risk assessment on the patient. At block 142 of fig. 5A of the flowchart 140, the patient is sent to the patient room with a stretcher. Thereafter, as shown in block 144, the patient is transferred from the stretcher to the patient bed 14 in the room. At this point, the patient is admitted to the medical facility, as indicated at block 146. In some embodiments, the patient is admitted to the hospital prior to being sent to the patient room.

After arriving at the room, the nurse evaluates the patient, as shown in block 148 of fig. 5A. If the Real Time Location System (RTLS) determines that the caregiver is located in the patient's room, the information on the display panel, the display of the mobile device 60, the display 50 of the nurse call system, and the status panel 58 is updated to indicate that the caregiver is located in the room, as shown in block 148. Block 148 also instructs the nurse to assess the patient bed condition (e.g., side rails in place, caster brakes set, etc.), assess the patient, make an assessment of the monitor 18, check the patient temperature, record the patient anxiety level associated with the heart rate assessment, activate the Patient Safety Application (PSA) (e.g., activate or enable a patient exit/Patient Position Monitoring (PPM) system), and enable the patient bed rails (e.g., indicate which of the side rails associated with the patient bed exit/PPM system should be in an elevated position).

As shown in block 150 to the right of block 148, the healthcare facility's nurse call system receives a feed from an admit/discharge/transfer (ADT) system, and if the ADT feed indicates that the patient is at risk of falling, the nurse call system sends a message to the patient's associated bed 14 to enable the systems on the bed 14 (e.g., enable the bed exit/PPM system and monitor the bedside fence position, caster brake status, etc.), as shown in block 152. In the illustrative example of fig. 5A, a bed pressure sensor is used to monitor the patient's motion, as shown in block 154 to the right of block 152. Alternatively or additionally, the load cells of the weighing system of the patient bed 14 monitor the patient's movement.

As shown in block 156 below block 154 of FIG. 5A, some or all of the information obtained in the nurse assessment of block 148 is displayed on one or more display devices, such as output device 34 discussed above. In addition, as shown in box 158 at the bottom left of box 156, the patient bed 14 sends patient safety status information to a display, such as a display at the trailing end of the bed, a display panel (e.g., status panel 58), one or more patient monitoring devices 18, and the mobile device 60 (the "Clarion application" listed in box 158 is the software used by the mobile device 60 for careCommunication between personnel and caregivers, and transmission of alerts (also known as warnings) and device data). In some embodiments, the "Clarion application" is LINQ available from Hill-Rom Company, Inc^TMAnd (4) moving the application program.

As shown at block 160 to the left of block 158, data associated with

blocks

148, 150, 152, 154, 156, 158 is also captured by the analytics engine 20 of the DSN platform for predictive analysis. In this regard, the analysis engine 20 receives patient motion data monitored by the load cells of the patient bed 14 as shown at block 162 to the left of block 160, and then transmits a message indicating a likelihood of the patient getting out of bed and informs one or more clinicians of the likelihood as shown at block 164. As shown at block 166 below block 164 of fig. 5A, if the clinician enters the patient's room, the PSA disables any alarms associated with the features monitored by the PSA.

In the illustrative example of the flow chart 140 of fig. 5A, the clinician uses the patient lift to move the patient from the patient bed 14 to the wheelchair, as shown in block 168. Thereafter, as shown at block 170, the clinician, for example, brings the patient to a toilet, such as a toilet in a restroom that is part of the patient's room. Block 170 also indicates that the toilet seat recognizes the presence of the patient (e.g., sits on the toilet seat), which causes the status on one or more displays of the output device 34 to change to the patient's toileting status, and also indicates on the display that the caregiver is in the room.

After the patient has used the toilet, the clinician uses the wheelchair to transport the patient to a chair in the room, as shown in block 172 of fig. 5B. Block 172 also indicates that the chair recognizes the presence of the patient (e.g., sits on the chair), which causes the state on one or more displays of the output device 34 to change to the state of the patient on the chair, and one or more of these displays also continue to indicate that the caregiver is in the room. Block 172 further indicates that the chair senses the patient's motion. Accordingly, the present invention contemplates that the chair has load cells, pressure sensors, Force Sensitive Resistors (FSRs), etc. and associated circuitry to sense the patient's position on the chair and communicate the patient's position on the chair to the analysis engine 20. As shown in block 174 to the left of block 172, in the illustrative example of flowchart 140, the clinician provides the patient with a nurse call communication device (e.g., a pillow speaker unit) that the patient can use to make a nurse call if the patient needs help while sitting in a chair after the caregiver leaves the patient's room.

As shown in block 176 to the left of block 174 in fig. 5B, while the patient is seated in the chair, the analysis engine 20 of the DSN platform 30 obtains data from the chair for predictive analysis of the exit from the chair. In the given example, the patient's motion is monitored by a chair cushion pressure sensor, as shown at block 178 to the left of block 176. As indicated by block 180 below

blocks

176, 178 in the illustrative flowchart 140, the clinician leaves the room and updates the status of the caregiver no longer in the room on the display of the patient bed 14, the monitor 18, the

display panels

50, 58 of the output device 34, and the display of the mobile device 60, but the status of the patient on the chair is still displayed on these displays.

As shown in block 182 on the right side of block 180 and below block 174 in fig. 5B, the system 10 indicates a likelihood of the patient leaving the chair and notifies one or more clinicians of the likelihood. Thereafter, the nurse enters the room, as shown in block 184. In response to the caregiver entering the room, the PSA receives the caregiver's in-room information from the positioning system, stops sounding the alarm on the patient bed 14, and sends a message causing one or more displays of the patient bed 14, the monitor 18, the

display panels

50, 58 of the output device 34, and the display of the mobile device 60 to update to indicate that the caregiver is in the room.

In the illustrative example of the flow diagram 140, after the caregiver enters the room at block 184, the caregiver returns the patient to the patient bed 14 as shown at block 186. Thereafter, as shown in block 188, the bedside rug is raised and the caregiver leaves the room. Also shown at block 188, the PSA receives information from the positioning system that the caregiver has left the room and sends a message to cause one or more of the display of the patient bed 14, the monitor 18, the

display panels

50, 58 of the output device 34, and the display of the mobile device 60 to be updated to indicate that the caregiver is out of the room and that the patient is in the patient bed. Thereafter, as shown in block 190 of fig. 5B, data relating to patient movement is captured from the bed 14 and predictive analysis of the exit of the bed is again commenced at the analysis engine 20 of the DSN platform 30.

Based on the foregoing, it is apparent that data is generated by the plurality of

devices

14, 16, 18 and other sources 12 as described above and sent to the analytics engine 20 of the DSN platform 30. The algorithms of the analysis engine establish a risk profile (e.g., a risk score) for each patient based on the protocol established by the given medical facility. Some or all of the

devices

14, 16, 18 and other sources 12 are updated with risk profile information. In some embodiments, the source 12 has a display that provides guidance steps to the caregiver, who may be taken at the point-of-care to mitigate or mitigate the risk profile. The analysis engine updates the risk profile for each patient in substantially real time as the input data changes. In some embodiments, the analytics engine 20 also sends the data to other systems, such as the IoT platform 64, for further analysis.

Referring now to fig. 6, a schematic diagram of another system 10 similar to that of fig. 3 is provided and shows hospital local equipment, including the indoor equipment 12, the equipment gateway 32 and the status board 58, on the left side of the page. The illustrative room arrangement 12 of fig. 6 includes a patient bed 14, an incontinence detection system 16, a vital signs monitor 18, and a room station 50. However, the devices 12 of the system 10 of fig. 6 may include any other type of device 12 discussed herein. In some embodiments, system 10 of fig. 6 also includes a cloud appliance 200 located at the center of the page, which includes an enterprise gateway (HL7)202, a clinical data repository 204, a risk engine 206, and an analysis platform 20 that implements Artificial Intelligence (AI) to process the data. Other local devices of the system 10 of fig. 6 are shown on the right side of the page, including one or more mobile devices 60 and third party solutions 208 including EMR server 62, ADT server 210, and laboratory server 212.

As shown in fig. 6, messages and/or data transmitted from device 12 to third party solutions 208 via gateway 32 and from clinical data repository 204, risk engine 206, and analysis platform 20 pass through enterprise gateway (HL7) 202. Thus, the gateway 202 converts the various messages and data into a health level 7(HL7) format for subsequent transmission to third party devices 208, such as EMRs, ADTs, and

laboratory servers

62, 210, 212. In the embodiment of system 10 in fig. 6, risk engine 206 manages risk levels for the stress injury risk score, fall risk score, and sepsis risk score based on input data from device 12, and analysis platform (also referred to as analysis engine) 20 analyzes input data from device 12 to determine correlations with various patient risk scores.

In accordance with the present invention, the various devices 12 provide various types of data (e.g., patient data, vital sign data, physiological data, device data, etc.) to the analysis engine 20, which the analysis engine 20 processes and determines one or more risk scores based on the data. The risk score is adjusted in substantially real time as new data is received by the analysis engine 20. In the discussion above, risk scores related to stress injuries, falls, and sepsis are given as examples of risk scores. However, the present invention contemplates that other risk scores associated with other patient risks may be determined at the discretion of the designer or programmer of system 10. In this regard, the following table lists the types of data (referred to as "risk factors") that may affect the risk scores (including those related to stress injury, fall, and sepsis) according to the present invention:

TABLE 1

It should be noted that some of the risk factors in table 1 occur twice, but are designated in separate columns as risk factor identification (rfid) type (rfid _ type) 1 or rfid _ type 2, and the other risk factor is rfid _ type 0. These two different types of risk factors mean that the risk factors may be obtained from multiple sources, for example, or in some cases, based on gender (e.g., male or female). One or more of the risk factors in table 1 may be selected in a spreadsheet to set the risk rules implemented by the analysis engine 20 in the system 10. Examples of such risk rules that may be established include: determining with the analysis engine 20 that the patient is at risk for respiratory distress if either of the following conditions is met: (1) the patient is 70 years of age or older and has Chronic Obstructive Pulmonary Disease (COPD); (2) the patient has COPD and has taken opioids; (3) the patient is 70 years old or older and has taken opioid; (4) the patient is 70 years old or older, has asthma, and has a Blood Urea Nitrogen (BUN) of greater than or equal to 30 milligrams per 100 milliliters (ml) (mg); or (5) there are any four patient conditions listed in table 1. Other examples of such risk rules that may be established include: the analysis engine 20 is used to determine that the patient is at risk for sepsis if any of the following conditions are met: (1) the patient is 65 years old or older and has cancer; or (2) the patient has a history of sepsis.

It is within the scope of the present invention to formulate a risk rule based on any number of risk factors listed in table 1, and for those risk factors related to dynamically measurable parameters such as patient physiological parameters (e.g., those physiological parameters indicated by "vital signs" in the "type" column of table 1), the risk rule may be based on specific measurable parameters above or below a threshold criterion. Accordingly, the present invention contemplates that assessing a patient's medical risk includes receiving patient demographic data for the patient, including, for example, at least one of age, race, and weight as shown in table 1, at the analysis engine 20. In some embodiments, the analysis engine 20 also receives patient comorbidity data, including data indicating that the patient has at least one of the following medical conditions or characteristics: acquired immunodeficiency syndrome (AIDS), anemia, chronic congestive heart failure, asthma, cancer, Chronic Obstructive Pulmonary Disease (COPD), coronary artery disease, cystic fibrosis, dementia, emphysema, alcohol or drug abuse, stroke, pulmonary embolism, history of sepsis, type 1 diabetes mellitus, morbid obesity, neuromuscular disease, past intubation, scoliosis, smoker's, delirium, splenomess, bone marrow transplantation, cirrhosis, dialysis, diverticular disease, heart valve disease, inflammatory bowel disease, joint replacement, leukopenia, malignancy, tumor, organ transplantation, peripheral vascular disease, kidney disease, pressure injury, recent abortion, recent childbirth, epilepsy, sickle cell anemia, or end stage disease.

In some embodiments, the analysis engine 20 also receives physiological data that may be measured by a physiological monitor, which may have at least one sensor coupled to or in communication with the patient. The physiological data includes data that is dynamic and changes over time as the patient is monitored by the physiological monitor. For example, the physiological data includes one or more of: heart rate, respiration rate, body temperature, mean arterial pressure, systolic pressure, or pulse oximetry data including peripheral capillary oximetry (SpO 2). In some embodiments, the analysis engine 20 calculates a risk score or performs a patient risk assessment in substantially real time based on one or more of patient demographic data, comorbidity data, and physiological data.

In some embodiments, the analysis engine 20 also receives laboratory data of the patient and uses the laboratory data to calculate a risk score. As shown in table 1, examples of laboratory data include data relating to one or more of the following: albumin, arterial blood oxygen partial pressure (arterial PaO2), arterial blood carbon dioxide partial pressure (PCO2), arterial blood pH, acidosis, brain natriuretic peptide, blood urea nitrogen, cardiac ejection fraction, creatinine, hemoglobin, hematocrit, lactate, pulmonary function tests, troponin, bilirubin, C-reactive protein, D-dimer, glucose, bicarbonate (HCO3), hyperlactatemia, international coagulation standard quantitation (INR), normal white blood cell count (WBC) with neutrophils greater than 10%, arterial blood carbon dioxide partial pressure (PaCO2), fluid overload, pH value, platelets, procalcitonin, urine protein, Partial Thromboplastin Time (PTT), or white blood cell count. Alternatively or additionally, the analysis engine 20 receives patient symptom data for the patient and uses the patient symptom data to calculate a risk score. As shown in table 1, examples of patient symptom data include data relating to one or more of: paramuscular use, mental state changes, confusion, anxiety, chest pain, cough, cyanosis, sweating, dyspnea, hemoptysis, fatigue, dysphoria, sputum production, tachycardia, tachypnea or lethargy.

Further, alternatively or additionally, the analysis engine 20 receives clinical exam data and uses the clinical exam data to calculate a risk score. As shown in table 1, examples of clinical examination data include data relating to one or more of the following: abdominal breathing, abnormal lung sounds, accessory muscle use, capillary refilling, chest distress or chest pain, electrocardiographic (ECG or EKG) abnormalities, cough, cyanosis, reduced consciousness Level (LOC), irritability, encephalopathy, color spots, Activities of Daily Living (ADL) requiring assistance, orthopnea, peripheral edema, sputum secretion, delirium, excess body fluid, cardiac output, early skin warm red, late skin pale and color spots, fever, headache, neck stiffness, hypothermia, intestinal obstruction, jaundice, meningitis, oliguria, peripheral cyanosis, ecchymosis, fluid positive balance, epilepsy, coma, or insufficient blood volume.

Further, alternatively or additionally, the analysis engine 20 receives the recorded order data and uses the recorded order data to calculate a risk score. As shown in table 1, examples of recorded order data include data relating to one or more of: delivery of breathing air other than with a cannula (including with a venturi, ventilator, non-rebreather, Continuous Positive Airway Pressure (CPAP) machine, bi-phase positive airway pressure (bi-PAP) machine); testing arterial blood gas; brain natriuretic peptide testing; respiratory therapy; chest x-ray film; a Doppler echocardiogram; high flow rate or high capacity (input output (I & O)); lung consultation; testing lung function; ventilation perfusion (VQ) scan; or a chest Computed Tomography (CT) scan.

In some embodiments, the analysis engine 20 also receives admission data for the patient and uses the admission data to calculate a risk score. As shown in table 1, examples of admission data include data relating to one or more of the following: abdominal aortic aneurysm surgery, acute myocardial ischemia, acute pancreatitis, aspiration, asthma, bronchiectasis, atelectasis, bronchitis, burns, cancer, cardiac or thoracic surgery, heart valve disease or valve insufficiency, chemotherapy, congestive heart failure, chronic obstructive pulmonary disease progression, deep vein thrombosis, drug overdose, dyspnea at rest, emergency surgery, hemoptysis, interstitial lung disease, lung abscess, neck surgery, neurosurgery, epigastric surgery, peripheral vascular surgery, pneumonia, pneumothorax, pulmonary embolism, pulmonary hypertension, pulmonary renal syndrome, renal failure, sepsis, shock, sleep apnea, smoke inhalation injury, surgery, thoracentesis, trauma, lethargy, delirium, abscess, abdominal pain, abdominal tenderness, acute lung injury, appendicitis, bacteremia, cellulitis, cholangitis, acute lung injury, appendicitis, and/or chronic obstructive pulmonary disease, Colitis, cystitis, dehydration, diverticulitis, encephalitis, encephalopathy, endocarditis, unexplained fever, gastroenteritis, gastrointestinal bleeding, gastrointestinal infection, hypotension, infectious process, discomfort, osteomyelitis, ostomy, pelvic pain, kidney disease, pyelonephritis, respiratory infection, suppurative arthritis, soft tissue infection, surgical hospital admission, wound, or acute respiratory distress syndrome.

Alternatively or additionally, the analysis engine 20 receives the patient's medication data and uses the medication data to calculate a risk score. As shown in table 1, examples of drug data include data relating to one or more of the following: anticoagulants including heparin or enoxaparin (levenox), bronchodilators, corticosteroids, diuretic use, high flow or high volume or hypertonic fluids, opioids, sedatives, hypnotics, muscle relaxants, fluid overload, antibiotics or immunosuppressive agents that may be delivered Intravenously (IV) or Subcutaneously (SC).

Based on the foregoing, it should be appreciated that the present invention contemplates a method being implemented on at least one computer (e.g., one or more of the analysis engines 20) and other servers (e.g.,

servers

62, 210, 212, 206, etc.). In the following discussion, it will be assumed that the analysis engine 20 implements various algorithms and functions. According to the method, the analysis engine 20 receives dynamic clinical variables and vital sign information for a patient. The analysis engine 20 uses the vital sign information to generate a previous vital sign mode and a current vital sign mode, and then compares the previous vital sign mode with the current vital sign mode. The analysis engine 20 also receives one or more of: a static variable of the patient, a complaint of the patient, a previous healthcare utilization pattern of the patient, or a social determinant of health data of the patient. The analysis engine 20 uses the dynamic clinical variables, vital sign information, the comparison of previous vital sign patterns to current vital sign patterns, and one or more of the social determinants of static variables, chief complaints, healthcare utilization patterns, or health data in an algorithm to detect or predict whether a patient has sepsis or is likely to have sepsis.

In some embodiments, the dynamic clinical variables received by the analysis engine 20 include point-of-care laboratory data. Optionally, the static variables received by the analysis engine 20 include comorbidities. Alternatively or additionally, the static variables received by the analysis engine 20 include whether the patient's care settings are pre-emergency care settings, or post-emergency care settings. The analysis engine 20 also receives historical data of the patient, if desired.

It is within the scope of the present disclosure for the analysis engine 20 to output one or more suggested actions to one or more clinicians of each patient being monitored. Examples of one or more suggested actions include, for example, sending the patient to an emergency room (ED), enhancing monitoring of the patient by one or more clinicians, or ordering a series of laboratory tests for the patient.

In some embodiments, the analysis engine 20 ranks clinicians for a medical facility. For example, the analysis engine 20 ranks clinicians for a medical facility based on one or more of experience, previously taken actions, and previous patient treatment outcomes. Alternatively, the analysis engine 20 may use the measure with the greatest impact on the treatment outcome to inform a novice clinician or a less experienced clinician how the experienced clinician is dealing with the patient.

The present invention contemplates that analysis engine 20 uses Artificial Intelligence (AI) and machine learning to analyze risk factor data of the types listed in table 1 and determine correlations between one or more risk factors and specific risks such as stress injury, fall and sepsis, as well as other risks for the patient. Risk rules based on two or more highly correlated risk factors are then established using the risk factors highly correlated to the particular risk.

As discussed above in connection with fig. 3 and 6, the caregiver's mobile device 60 pertains to the output device 34 on which the risk score and risk data are displayed. Fig. 7-10 show example screenshots of the type of information displayed on a caregiver's mobile device 60. In some embodiments, it is contemplated that the examples of FIGS. 7-10 are available from Hill-Rom Company, IncObtained LINQ^TMAdditional software functionality of the mobile application is provided. LINQ^TMAdditional details of mobile applications may be found in U.S. application No. 16/143,971 entitled "caredriver and Staff Information System," filed on 27.9.2018, which is published as U.S. patent application publication No. 2019/0108908 a1, and which is incorporated herein by reference.

Referring now to fig. 7, examples of a patient screen 220 of the mobile application displayed on the touch screen display of the mobile device 60 of fig. 3 and 6 include a My Patients (My properties) button or icon 222 and a My wards (My Unit)224 button or icon near the top of the screen 220. In the illustrative example, my patients icon 222 has been selected, whereby screen 222 includes a list 226 of patients assigned to the caregiver of mobile device 60 displaying screen 220. Each patient assigned to a caregiver is displayed in a separate row of the list 224, including the patient's name and the room in the medical facility assigned to the patient. One or more risk scores and related information (as applicable) are displayed under each patient's room number and name. If my room button 224 is selected, similar information is displayed on the display screen of the mobile device 60 for all patients in the ward of the medical facility to which the caregiver is assigned, including the patients of the ward assigned to other caregivers.

In the illustrative example of screen 220 in fig. 7, below the text "2160 HILL, LARRY" in the first line of list 226, a first risk score box 228 shows a Systemic Inflammatory Response Syndrome (SIRS) score having a value of 4, and a second risk score box 230 shows a Modified Early Warning Score (MEWS) having a value of 5. Also in the illustrative example, an up arrow icon 232 is shown to the left of each of the

boxes

228, 230 in the first row of the list 226 to indicate that both the SIRS and mems scores have increased relative to their previous readings. In the illustrative example, "@ 9: 20 "appears to the right of the text" mems "in the first line of the list to indicate when the mems score was most recently updated. In the second through fourth rows of the illustrative example of the list 226, only boxes 230 having the MEWS scores of the respective patients are shown. The fifth line of the list 226 has text "2159 NO PATIENT" to indicate that room 2159 is not currently assigned any PATIENT, but if a PATIENT is assigned to room 2159, that PATIENT will be one of the PATIENTs assigned to the caregiver of the mobile device 60 on which the screen 220 is displayed. The screen 220 also has an icon or button (these terms are used interchangeably herein) menu 234. The menu 234 is below the list 226 and includes a Home (Home) icon 236, Contacts (Contacts) icon 238, Messages (Messages) icon 240, Patients (properties) icon 242, and Phone (Phone) icon 244. Additional details of the screens and functions associated with

icons

236, 238, 240, 242, 244 may be found in U.S. patent application No. 16/143,971, filed on 27.9.2018, which is published as U.S. patent application publication No. 2019/0108908 a1, and which is incorporated herein by reference.

Referring now to FIG. 8, an example of a risk details screen 250 is shown, which screen 250 appears on the touch screen display of the caregiver's mobile device 60 in response to selection of one of the right arrow icons 252 of the screen 220 to the right of each row of the list 226. In the illustrative example of fig. 8, as shown at the top of screen 250, screen 250 displays the risk details of patient Larry Hill. To the left of the text "PATIENTS 2160HILL, L." at the top of the screen 250 is provided a left arrow icon 254, and the icon 254 is selectable to return the caregiver to the screen 220. In the illustrative example of screen 250, phone icon 244 no longer appears in menu 234, but rather appears in the upper right corner of screen 250. The

other icons

236, 238, 240, 242 remain in the menu 234 at the bottom of the screen 250.

Still near the top of the screen 250, the patient's Medical Record Number (MRN) is displayed in column 256 and the patient's age is displayed in column 258. In the illustrative example, the patient's MRN is 176290 and the patient is 76 years old. Under column 256 of screen 250, three status icons are shown. In particular, a fall risk icon 260, a lung risk icon 262, and a pressure injury icon 264 are shown. If it is determined that the patient is at risk of falling, the icon 260 is highlighted. Icon 262 is highlighted if it is determined that the patient is at risk of respiratory distress. If it is determined that the patient is at risk of developing a pressure injury, the icon 264 is highlighted. If it is determined that the corresponding patient has no associated risk, the

icons

260, 262, 264 are grayed out or not present.

With continued reference to fig. 8, an mems window 266 is displayed below the

icons

260, 262, 264 and has additional information related to the mems score appearing in the box 230. Box 230 and up arrow icon 232 appear on the left side of window 266. To the right of box 230 and icon 232 of window 266, various vital sign information related to or affecting the MEWS score is shown. In the example of screen 250, the body temperature of the patient Larry Hill is 100.6 degrees fahrenheit (F), the SPO2 is 92%, the non-invasive blood pressure (NIBP) is 200/96 mmhg, the Heart Rate (HR) is 118 Beats Per Minute (BPM), and the Respiratory Rate (RR) is 26 Beats Per Minute (BPM). An up arrow icon 267 appears in window 266 to the right of any vital signs that have increased since the previous reading.

In accordance with the present disclosure, the data required to calculate the MEWS is obtained from sensors included as part of medical device 12 (e.g., patient bed 14 and vital signs monitor 18), and/or received as manual user input based on clinical findings 24 of the caregiver, and/or obtained from the patient EMR of EMR server 62. MEWS is a known score calculated according to the following table:

TABLE 2

Score of	3	2	1	0	1	2	3
								Systolic pressure	＜70	71-80	81-100	101-199	-	＞200	-
Heart rate (BPM)	-	＜40	41-50	51-100	101-110	111-129	＞130
								Respiration Rate (RPM)	-	＜9	-	9-14	15-20	21-29	＞30
Body temperature (. degree. C.)	-	＜35	-	35.0-38.4	-	＞38.5	-
								AVPU	-	-	-	A	V	P	U

In table 2, the various integers in the column headings are added together based on the various patient readings of the data corresponding to the rows of the table. A score of 5 or higher indicates the likelihood of death. With respect to the systolic pressure, heart rate, respiratory rate, and body temperature portions of the MEWS, this information is obtained using sensors of the patient bed 14 and/or using other means of obtaining patient physiological data as discussed above. The AVPU portion of the MEWS indicates whether the patient is awake (a), responsive to sound (V), responsive to pain (P), or unresponsive (U). The caregiver selects the appropriate AVPU letter for each patient and then enters it into a computer, such as the room station 50, the caregiver's mobile device 60, or other computer of the system 10 (e.g., nurse call computer, EMR computer, ADT computer, etc.).

Still referring to screen 250 of fig. 8, a sepsis associated organ failure assessment (SOFA) window 268 is shown below window 266, window 268 having information related to the SOFA score. On the left side of window 268, a risk score box 270 shows the SOFA score value, 2 in the illustrative example, and an up arrow icon 272 indicates that the SOFA score has increased compared to the previous score. To the right of box 270 and icon 272 in window 268, patient physiological parameters that affect or are related to the SOFA score are shown. In an illustrative example, the patient has 145 microliters (μ L) of platelets, 800 milliliters of output/input per day, and a Cardiovascular (CV) of 58 Mean Arterial Pressure (MAP).

A MORSE window 274 having information related to a MORSE Fall Scale (MFS) score or value is shown on the screen 250 below the window 268 of fig. 8. To the left of the window 274, a risk score box 276 shows a MORSE or MFS score value, which in the illustrative example is 3. No up arrow icon or down arrow icon is displayed next to box 276 thereby indicating that the MORSE score has not changed since the last reading. To the right of box 276 are risk factors that affect or are associated with the MORSE score. In an illustrative example, the patient's activity risk factors include the patient's vision impairment and hip replacement, and the patient's drug risk factors include the patient's use of a sedative. In each of the

windows

266, 268, 274, the time at which the score in the respective

risk score box

230, 270, 276 was most recently updated is indicated below the

respective box

230, 270, 276.

As shown in fig. 8, screen 250 includes a pair of risk-affecting factor windows including a respiratory distress window 278 and a sepsis window 280. Respiratory distress window 278 lists factors that affect or are associated with the risk that the patient will experience respiratory distress, and sepsis window 280 lists factors that affect or are associated with the risk that the patient will develop sepsis. In the illustrative example, the risk factors in the respiratory distress window 278 include: patients with Chronic Obstructive Pulmonary Disease (COPD), patients over 65 years of age, and patients who are smokers, risk factors in sepsis window 280 include: patients suffer from Urinary Tract Infection (UTI) and patients are over 65 years of age. The example of fig. 8 demonstrates that patient risk factors can be used with multiple risk scores, or risk factors that have an impact on a risk score or risk determination.

With respect to

windows

266, 268, 274, in some embodiments, some or all of these windows are color coded to indicate the severity of a particular risk score or a particular risk factor related to a risk score or risk determination. For example, if the risk value in box 230 is 5 or greater, the area around box 230 of window 266 and the border of window 266 may be color coded with red to indicate that the patient is at a high risk level. Similarly, if the risk values in

blocks

270, 276 indicate moderate risk (as is the case in the illustrative example), the areas around

blocks

270, 276 of

windows

268, 274, respectively, may be color coded in yellow. In some embodiments, the

arrows

232, 267, 272 are also color coded, typically with a dark phase of red or yellow, as the case may be. If the risk score for any particular risk factor indicates a lower risk level, the relevant window on screen 250 is color coded in green or other color such as blue or black. In some embodiments, the risk influencing

factor windows

278, 280 are similarly color coded (e.g., red, yellow, green) depending on the number or severity of risk factors present for a particular patient. In some embodiments, the respective numerical data or risk factors in the

windows

266, 268, 274 are also color coded.

Referring now to FIG. 9, an example of an alternative "risk details" screen 250' is shown, where the screen 250' appears on the touch screen display of the caregiver's mobile device 60 in response to selection of one of the right arrow icons 252 of the screen 220 to the right of each row of the list 226 of FIG. 7. Portions of screen 250 'that are substantially identical to the same portions of screen 250 are identified with the same reference numerals, and the above description of these portions of screen 250 applies equally to screen 250'. In the illustrative example of fig. 9, screen 250 'displays details of the risk of patient LarryHill, as shown at the top of screen 250'. Below the MRN data 256 and age data 258 of the screen 250' is an mems window 282. To the right of window 282, the MEWS score box 230 and up arrow icon 232 are shown.

The window 282 includes a body temperature score box 284, a Respiration Rate (RR) score box 286, a level of consciousness (LOC) score box 288, a first custom score box 290, and a second custom score box 292, as shown in fig. 9. In the illustrative example, both

boxes

284, 286 score 2, and box 288 has the letter P from the AVPU score shown in table 2. The illustrative MEWS box 230 scores 5 in the illustrative example of screen 250' in FIG. 9, but in practice, assuming that P in box 288 corresponds to score 2 shown in Table 2, the score should be displayed as 6. In the illustrative example of screen 250', an up arrow icon 294 is shown below

boxes

284, 288 to indicate that the body temperature portion and the LOC portion of the mems are each increased from the previous values used to calculate the previous mems. A dash icon 296 is shown in window 282 below the 286 boxes to indicate that the RR portion of the patient's mems has not changed since the last mems calculation.

Custom score boxes

290, 292 of window 282 indicate that a revised MEWS or modified MEWS is within the scope of the present disclosure. Thus, the designer or programmer of the system 10 for any given medical facility may select other risk factors, such as those shown above in table 1, that have an impact on such revised or modified mems. For example, age may be a risk factor selected to correspond to one of

boxes

290, 292. The score value based on the age range is also decided by the system designer or programmer at his or her discretion. Thus, integers between 0 and 3 may be assigned to different age ranges, just to give one arbitrary example (e.g. 0 for 20 years or less, 1 for 21-40 years, 2 for 41-60 years, 3 for 61 years or more). Alternatively, negative numbers may be used for certain age ranges. For example, assuming that the patient associated with window 282 is 20 years of age or below, an age of 20 years of age or below may be assigned a score of-1, which would result in such a revised or modified MEWS being an illustrative score of 5 (i.e., the sum of

boxes

284, 286, 288 is 6, then the age score of-1, then the total modified MEWS is 5). Again, this is just an arbitrary example, and it should be understood that the risk factors present in Table 1 and the numerical scoring schema are virtually limitless possible, and may be selected in conjunction with the

custom boxes

290, 292 of the window 282 to create a revised or modified MEWS.

Still referring to screen 250' of FIG. 9, a Systemic Inflammatory Response Syndrome (SIRS) window 298 is shown below window 282. A SIRS score box 300 is shown on the right side of window 298 with a check mark 302 appearing in box 300 to indicate that the patient is SIRS positive. If the patient is SIRS negative, box 300 is blank. On the left side of window 298, risk factors and associated data that have an effect on or are associated with a determination that the patient is SIRS positive are shown. In the illustrative example of screen 250', window 298 includes Heart Rate (HR) data of 118 beats per minute and white blood cell count (WBC) of less than 4,000. In some embodiments, whether the patient is SIRS positive is determined based on the following table:

TABLE 3

In typical embodiments, a patient is considered to be SIRS positive if any two or more of the conditions indicated in the rows of table 3 are met. In other embodiments, two, three, or all four conditions indicated in table 3 need to be met before the patient is deemed to be SIRS positive, as determined by the system designer or programmer. The present disclosure also contemplates that other risk factors, such as those listed in table 1 above, are used to assess SIRS in a patient. It should be understood that the risk factors present in table 1 and the numerical scoring schema are virtually limitless possible, and these risk factors may be selected to add other rows in table 3 or replace one or more current rows in table 3 to create criteria for a revised or modified SIRS assessment.

Some other factors commonly used in SIRS assays include suspected or current sources of infection (SIRS + sources of infection), severe sepsis criteria (organ dysfunction, hypotension, or hypoperfusion criteria) indicated by lactic acidosis or SBP < 90 or SBP drop at normal levels ≧ 40mmHg, and ≧ 2 organ failure (multiple organ dysfunction syndrome criteria) (to name a few examples). In any case, the SIRS value is sometimes displayed on the mobile device 60 as a numeric score (which indicates the number of SIRS risk factors that are met), and sometimes as a check mark (which indicates that the patient is considered SIRS positive).

Continuing with reference to screen 250' of fig. 9, a sepsis associated organ failure assessment (SOFA) window 304 is shown below window 298. On the right side of the window 304, a SOFA score box 270 and an up arrow icon 272 are shown. These are substantially the same as those shown in window 268 of fig. 8 and therefore the same reference numerals have been used. However, unlike window 268 of screen 250, which shows numerical data for risk factors that affect the SOFA score, window 304 of screen 250' has a risk score box for each of the affecting risk factors. In the illustrative example, the platelet risk score box 306 and the cardiovascular disease risk score box 308 are shown in window 304, and the scores of

boxes

306, 308 are both 1, adding the scores of

boxes

306, 308 together results in the overall SOFA risk score of 2 shown in box 270 of window 304.

In some embodiments of the system 10, a fast sofa (qsofa) score is also determined and displayed on the caregiver's mobile device 60. The qsfa score may be displayed instead of, or in addition to, the SOFA score. In some embodiments, table 4 below is used to calculate the qsfa score:

TABLE 4

Evaluation of	qSOFA score
		Hypotension (SBP ≤ 100mmHg)	1
High respiratory rate (more than or equal to 22 breaths/min)	1
		Mental state change (GCS ≦ 14)	1

In some embodiments, one or more of the following tables are used to calculate the SOFA score:

TABLE 5 respiratory System

TABLE 6 nervous System

Index of coma	SOFA score
			15	0
13-14	+1
		10-12	+2
6-9	+3
		＜6	+4

TABLE 7 cardiovascular System

TABLE 8 liver

Bilirubin (mg/db) [ mu mol/L ]]	SOFA score
		＜1.2[＜20]	0
1.2-1.9[20-32]	+1
		2.0-5.9[33-101]	+2
6.0-11.9[102-204]	+3
		>12.0[＞204]	+4

TABLE 9 coagulation

Blood platelet ^x10³/μl	SOFA score
		≥150	0
＜150	+1
		＜100	+2
＜50	+3
		＜20	+4

TABLE 10 kidneys

Creatinine (mg/dl) [ μmol/L](or urine output)	SOFA score
		＜1.2[＜110]	0
1.2-1.9[110-170]	+1
		2.0-3.4[171-299]	+2
3.5-4.9[300-440](or < 500ml/d)	+3
		>5.0[>440](or < 200ml/d)	+4

To calculate the overall qSOFA score, the score values in the right column of Table 4 are added together, or in relation to the SOFA score, the SOFA-related score values in the right column of any of tables 5-10 are added together. In the illustrative example of window 304, an up arrow icon 310 is shown below block 306 for indicating that the patient's platelets have increased since a previous platelet reading; a dash icon 312 is shown below the box 308 to indicate that the patient's cardiovascular reading has not changed since the previous cardiovascular reading.

The screen 250' of fig. 9 also has a respiratory distress window 278 and a sepsis window 280 that are substantially the same as the

windows

278, 280 of the screen 250 of fig. 8, and therefore the same reference numerals are used. However, in addition to the text indicating that the patient has COPD, is older than 65 years, and is a smoker, the window 278 of fig. 9 also indicates that the patient has a respiration rate of less than 15 breaths per minute. Also, in addition to text indicating that the patient has UTI and is older than 65 years, the window 280 of fig. 9 also indicates that the patient's WBC is less than 4,000. In some embodiments, the

windows

278, 280, 282, 298, 304 of the screen 250' of FIG. 9 may be similarly color-coded similar to the color-coding discussed above in connection with the

windows

266, 268, 274, 278, 280 of the screen 250 of FIG. 8 and the information therein.

Referring now to fig. 10, an example of an mems details screen 320 is shown, the screen 320 providing more detailed information related to the mems of screens 250, 250' of fig. 8 and 9. Thus, if the caregiver touches, taps, or slides the MEWS window 230 of screen 250 or the MEWS window 282 of screen 250', screen 320 appears on the caregiver's mobile device 60 touchscreen display. Parts of the screen 320 that are substantially identical to the same parts of the screens 220, 250' of fig. 7-9, respectively, are denoted with the same reference numerals, and for the identical parts, the above description applies equally to the screen 320.

The screen 320 has an expanded MEWS data window 322 below the MRN data 256 and age data 258. In the illustrative example, the SIRS and

SOFA windows

298, 304 of the screen 250' of fig. 9 are minimized to smaller windows 298 ', 304 ', respectively, below the expanded MEWS data window 322. The windows 298 ', 304' omit risk factor data such as that shown in

windows

298, 304. However, windows 298 ', 304' still show

boxes

272, 300 with corresponding SOFA score and SIRS checkmark icons 302. The up arrow icon 272 is still shown in window 304'. The expanded MEWS data window 322 includes

boxes

230, 284, 286, 288 shown in window 282, but the positions of these boxes have been rearranged and several other boxes and numerical data are also shown in window 322. The up

arrow icons

232, 294 are also shown on the right side of the

frames

230, 284, respectively, in the window 322. In the illustrative example of screen 320, in window 322, up arrow icon 324 is shown to the right of box 286 and dash icon 326 is shown to the right of box 288.

The window 322 also includes a non-invasive blood pressure (NIBP) -systolic blood pressure risk score box 328, an SPO2 risk score box 330, a NIBP-diastolic blood pressure risk score box 332, and a pulse rate risk box 334. In the illustrative example, each of the

boxes

328, 330, 332 has an "X" indicating that the value of the associated patient physiological parameter has no effect on the patient's overall mems. In other embodiments, a "0" occurs in the corresponding box when the associated risk factor has no effect on the patient's MEWS. In the illustrative example, a risk score value of 2 occurs in block 334. A dash icon 326 is shown to the right of each of the

boxes

328, 339, 332, 334 to indicate that the respective reading has not changed since the previous reading. The values in

boxes

284, 286, 288, 328, 330, 332, 334 of window 322 are sub-scores that, when added together, provide the overall MEWS score for the patient. As described above, a revised or modified mems (also referred to as a customized mems) may be created using the risk factors in table 1, in which case the risk factor selected from table 1 has an associated risk score box and risk data in window 322. If the

windows

268, 264 of the screen 250 of FIG. 8 or the

windows

298, 304 of the screen 250' of FIG. 9 are selected on the caregiver's mobile device 60 instead of the window 266 of the screen 250 or the window 282 of the screen 250', the associated risk score boxes and data are also shown.

In accordance with the present disclosure, in some embodiments, an EMR plug-in the form of a software module is provided in the system 10. EMR plug-ins are used by hospital administrators and caregivers to view patient deterioration (e.g., the occurrence of sepsis, respiratory distress, stress injuries, and falls, etc.), thereby providing dynamic risk monitoring to the user so that patient risk can be identified earlier and more consistently. The plug-in provides additional context information beyond the traditional Early Warning Score (EWS) for review of the risk score and establishes caregiver trust by providing criteria and reasoning behind the risk score. The EMR plug-in may also continuously indicate whether parameters are missing from the patient's exacerbation risk score in order to inform the caregiver which risk parameters still need to be evaluated and entered.

In some embodiments, the EMR plug-ins are accessed through navigation in an EMR computer in communication with the EMR server 62. The EMR computer launches a web page provided by the EMR plug-in. The EMR plug-ins are configured to help reduce/eliminate delays and communication deficiencies between caregivers/teams during upgrade events or hand-offs. A situational, background, assessment, advice (SBAR) function is provided in the EMR plug-in that ensures that the patient's risk of deterioration is timely communicated to the appropriate caregiver upon the occurrence of a handover or upgrade event in order to effectively convey information of the patient's risk of deterioration.

In another embodiment, the EMR plug-in automatically calculates an early warning score for a patient in the medical facility in substantially real time. In an example, the EMR plug-in extracts data input from the EMR server 62 to automatically calculate the early warning score. In another example, the EMR plug-in extracts data input directly from one or more patient data sources 12 and automatically calculates an early warning score in substantially real time using the analysis engine 20. The early warning scores calculated by the EMR plug-in may include a Modified Early Warning Score (MEWS), a National Early Warning Score (NEWS), a Modified Early Obstetric Warning Score (MEOWS), a Pediatric Early Warning Score (PEWS), a Systemic Inflammatory Response Syndrome (SIRS), and the like.

The EMR plug-in indicates whether data input for calculating the early warning score is missing and how long ago the data input for calculating the early warning score was employed. In an example, the data input includes one or more vital sign measurements obtained from a patient data source 12 (see fig. 1) (e.g., a patient bed 14, an incontinence detection system 16, a vital sign monitor 18, and an international pressure sore prevalence (IPUP) survey 22).

The EMR plug-in provides caregiver default settings that indicate whether a subset of data entries are old (e.g., "outdated") according to a typical care plan. The expiration of the data input depends on the calculated early warning score, so a higher early warning score reduces the time at which the data input is determined to be expired. This is because a higher early warning score requires more frequent updating of information, and thus the default expiration time of the higher early warning score is less than the lower early warning score. Also, the EMR plug-in provides an indication as to whether there is a lack of data input for calculating the early warning score.

In some embodiments, when one or more data inputs (e.g., vital sign measurements) are missing, the EMR plug-in utilizes the available data inputs to calculate an early warning score and indicate which data inputs are missing. If all data input is missing, the EMR plug-in does not calculate an early warning score.

Additionally, in some embodiments, the EMR plug-in generates an intervention measure based on the calculated early warning score. For example, the EMR plug-in may recommend that a caregiver take a vital sign measurement every hour (rather than every four hours) for a National Early Warning Score (NEWS) of 5 or 6. The intervention measures generated by the EMR plug-in are configurable and may be adjusted according to the needs and/or goals of the medical facility in which the patient and caregiver are located.

In some embodiments, a default expiration time is provided based on clinical knowledge and study. For example, vital sign measurements are typically taken every four hours in a medical surgical field, so vital signs may become outdated after four hours. In some examples, some data entries do not have an expiration time.

As described above, the EMR plug-in may be accessed from an EMR computer through a graphical user interface, such as a web page. In some examples, the expiration time of certain data inputs is indicated on the graphical user interface with a time stamp that changes color, for example, from blue or green (indicating a recently obtained data input) to red or yellow (indicating an expired or stale data input). In other examples, certain data inputs are marked with an icon (e.g., a clock or arrow) on the graphical user interface to indicate that the data input has expired or expired.

In some embodiments, the expiration time is dependent on the early warning score threshold. For example, when the early warning score increases, the EMR plugin may alter the expiration time to reflect the newly suggested intervention rate. In an example, the EMR plug-in recommends vital sign measurements to be taken every four hours when the NEWS score is between 1 and 4. The expiration time of vital sign measurements is reduced from every 4 hours to 1 hour when the NEWS score increases from 4 to 5. As noted above, the expiration time may be configured according to the needs and/or goals of the medical facility, and thus, the foregoing examples are for illustrative purposes only.

In some embodiments, the EMR plug-in utilizes the time-to-failure to delete a subset of the data inputs from the calculated early warning score when updated data input values have not been recorded or obtained if the time-to-failure threshold is exceeded. For example, respiration contractions and the use of auxiliary muscles are input as data inputs to calculate a Pediatric Early Warning Score (PEWS). However, these symptoms can be treated with a nebulizer. Thus, the EMR plug-in may delete the data input from the calculation of the PEWS when it is determined that the data input value has not been recorded or obtained if the time to failure threshold is exceeded. Additionally, the EMR plug-in may indicate in a graphical user interface on the EMR computer that the data input has been deleted from the calculations of the PEWS.

In some embodiments, the EMR plug-in trends the calculated early warning score for the patient over time. In some examples, the trends are displayed in a graphical user interface on the EMR computer to facilitate efficient communication of information regarding patient deterioration risk when a handover or upgrade event occurs.

In another embodiment, the EMR plug-in generates as output on an EMR computer and/or mobile device 60 a plurality of graphical user interfaces of clinical data aggregated by the system 10 shown in fig. 1. The graphical user interface provides the caregiver with an overall view of the patient's condition, enabling the caregiver to be aware of potential patient exacerbation conditions, such as sepsis, as early as possible. For clarity, the graphical user interface generated by the EMR plug-in is referred to below as a "screen".

Fig. 11-29 are exemplary screens of clinical data aggregated by the system 10. These screens provide notification of potential patient deterioration risks. In addition, the screen displays and organizes patient clinical data to quickly communicate problematic data input to the caregiver as well as which actions should be taken to correct the problematic data input based on the protocol of the medical facility. In addition, the screen enables the caregiver to dynamically select the data set that they wish to compare as a trend monitored over time.

The screen is generated on an EMR computer in communication with the EMR server 62. Further, the screen may be part of a mobile application displayed on a touch screen display of the mobile device 60 of fig. 3 and 6. These screens have common features with the screens described above with reference to fig. 7 to 10.

Referring now to FIG. 11, an exemplary Patient screen 400 includes a My Patient (My Patient) icon 402 and a My ward (My Unit) icon 404. In the illustrative example, my patients icon 402 is selected, whereby the patient screen 400 includes a list 406 of patients assigned to the caregiver of the mobile device 60 on which the patient screen 400 is displayed. Each patient assigned to a caregiver is displayed in a separate row of the list 406 including the patient's name and the room in the medical facility assigned to the patient. A deterioration icon 408 is displayed next to the text "2160 HILL, LARRY" to indicate that the patient is at risk of deterioration.

When my room icon 404 is selected (instead of my patients icon 402), similar information is displayed on patient screen 400 for all patients in the room of the medical facility, including patients assigned to other caregivers for the room.

Referring now to fig. 12-18, a risk details screen 401 appears in response to selection of a right arrow icon 410 on the right side of each row in the patient screen 400 of fig. 11. In the illustrative example, the risk details screen 401 shows the risk details of the patient "Larry Hill," as shown at the top of the screen.

An arrow icon 412 is provided in the upper left corner of the risk details screen 401. The arrow icon 412 may be selected to return to the patient screen 400.

A phone icon 414 appears in the upper right hand corner of the risk details screen 401. The phone icon 414 may be selected to place a phone call using the mobile device 60.

In fig. 12-18, the risk details screen 401 includes patient data 416, such as the patient's Medical Record Number (MRN), date of birth, age, gender, etc. In the illustrative example, patient data 416 is displayed at the top of screen 401.

Next to the patient data 416 is a right arrow icon 418. In response to selecting right arrow icon 418, a screen is generated that displays a trend of the patient's vital sign measurements over time. The screen generated in response to selection of right arrow icon 418 will be described in more detail below.

Below the patient data 416, three status icons are shown. In particular, a fall risk icon 420, a lung risk icon 422, and a pressure injury icon 424 are shown. If the patient is determined to be at risk of falling, a fall risk icon 420 is highlighted. If it is determined that the patient is at risk of respiratory distress, a lung risk icon 422 is highlighted. If it is determined that the patient is at risk for pressure injury, the pressure injury icon 424 is highlighted. If it is determined that the corresponding patient does not have an associated risk, the

icons

420, 422, 424 are grayed out or not present.

Next to the

icons

420, 422, 424 is a case, background, evaluation, Suggestion (SBAR) icon 426. As described above, an SBAR function is provided in the EMR plug-in that ensures that the patient's risk of deterioration is timely communicated to the appropriate caregiver upon the occurrence of a handover or upgrade event, so as to effectively convey information of the patient's risk of deterioration. The screen generated in response to selection of the SBAR icon 426 will be described in more detail below.

Below the

icons

420, 422, 424 is a master diagnostic bar 428. In the illustrative example, the main diagnostic bar 428 displays "pneumonia".

Below the main diagnostic bar 428 is shown an EWS window 430. Although the following description describes the EWS window 430 in relation to a Modified Early Warning Score (MEWS), it is contemplated that the EWS window 430 may be configured for a variety of early warning scores other than MEWS, including, for example, National Early Warning Score (NEWS), Modified Early Obstetric Warning Score (MEOWS), Pediatric Early Warning Score (PEWS), and the like. Additionally, EWS window 430 may be configured to display early warning scores that are institution specific.

In the illustrated example, the EWS window 430 includes a scoring area 432, the scoring area 432 including the mems score displayed in box 434. As described above, various early warning scores such as NEWS, MEOWS, PEWS, etc. may be displayed in block 434. The score displayed in block 434 drives the patient deterioration icon 408 on the patient screen 400 (see fig. 11). The score determines whether a deterioration icon 408 exists and how the deterioration icon 408 is displayed. For example, the score determines whether the deterioration icon 408 is yellow (e.g., medium risk) or red (e.g., high risk). It is contemplated that the color used to display the aggravation icon 408 may be configurable.

An arrow icon 436 is included in scoring area 432 next to box 434 to indicate whether the score in box 434 has increased (e.g., an up arrow icon) or decreased (e.g., a down arrow icon) since the previous reading. Additionally, below box 434 in scoring area 432 is a time column 438, which indicates the time at which the score was last calculated. In some cases, if the last time the score was calculated is within a threshold time limit, such that the score is recent and/or current, time column 436 becomes gray or non-existent. In another example, if the time the score was last calculated exceeds a threshold time limit, such that the score is expired, time column 436 is bolded or colored.

In some examples, scoring area 432 is highlighted in a different color depending on the score displayed in block 434. In addition, the background color within the box 434 may also be highlighted in a different color depending on the score. For example, for MEWS scores of 1 through 4 (see FIGS. 12 and 13), scoring area 432 and box 434 are not highlighted; for a MEWS score of 5 or 6 (see FIGS. 14 and 15), scoring area 432 and box 434 are highlighted in yellow; for a mems score of 7 or higher, scoring area 432 and box 434 are highlighted in red (see fig. 16-18). In some examples, the hue in the highlighted box 434 is darker than the hue in the highlighted scoring area 432.

To the right of scoring area 432 in EWS window 430 are various vital sign information related to or having an effect on the early warning score displayed in box 434. In the example shown, non-invasive blood pressure (NIBP), SPO2, Respiration Rate (RR), Heart Rate (HR), body temperature, and level of consciousness (LOC) are included alongside scoring area 432; at scoring area 432, the mems score is displayed in box 434. In some exemplary embodiments, the arrow icon is displayed next to the vital sign that has increased since the previous reading.

In some embodiments, below EWS window 430 is a Systemic Inflammatory Response Syndrome (SIRS) window 440 (see fig. 12, 14, and 16). The SIRS window 440 includes a SIRS score 442 calculated using the risk factors and associated data described above (e.g., see table 3). In some examples, the SIRS score 442 is in the range of 0 to 4. In some examples, when the SIRS score 442 is greater than or equal to a threshold score (e.g., 2 or higher), the SIRS window 440 and SIRS score 442 are highlighted (e.g., in red), as shown in the illustrative example of fig. 16. When the SIRS score 442 is less than the threshold value, the SIRS window 440 and SIRS score 442 are not highlighted (see fig. 12).

In some embodiments, below EWS window 430 is a rapid sepsis associated organ failure assessment (qSOFA) window 444 (see fig. 12, 14, and 16). The qsfa window 444 includes a qsfa score 446. The qsfa score 446 is calculated using the risk factors and associated data described above (e.g., see table 4). In some exemplary embodiments, the qSOFA score 446 is in the range of 0 to 3.

In other embodiments, instead of the qsfa window 444, a sepsis risk box 460 is displayed below the EWS window 430. The sepsis risk box 460 does not display a score. In contrast, when the patient is determined to be at risk for sepsis, the sepsis risk box 460 displays a sepsis risk icon 462 (see fig. 17 and 18). In some examples, in addition to displaying icon 462, sepsis risk box 460 may be highlighted (e.g., in yellow or red) to further provide a visual display that the patient is at risk of sepsis.

In some embodiments, below the EWS window 430 is a fall risk window 448 (see fig. 12, 14, and 16). The fall risk window 448 includes an icon 450 that, when highlighted or colored, indicates that the patient is likely to fall. Whether the patient is likely to make a call is determined based on a MORSE fall class (MFS) score calculated using the risk factors and associated data described above.

In other embodiments, displayed below the EWS window 430 is a fall risk box 464 instead of the fall risk box 448. The fall risk box 464 does not display the score. Conversely, when the patient is determined to be at risk of falling, the fall risk box 464 displays an icon 466 (see fig. 18). In some examples, in addition to displaying icon 466, fall risk box 464 is highlighted (e.g., in yellow or red) to further provide a visual display that the patient is at risk of falling.

Still referring to fig. 12-18, the risk details screen 401 includes a care team box 452. In response to selection of the care team box 452, a screen is generated that displays a caregiver responsible for caring for the patient in the medical facility.

The risk details screen 401 includes a laboratory results box 454. In response to selecting the laboratory results box 454, a screen is generated that displays the patient's laboratory results. In some examples, laboratory results box 454 includes a column 455 indicating whether any new, previously unseen patient laboratory results have been received.

The risk details screen 401 also includes a reminder box 456. In response to selecting the reminder box 456, a screen is generated that displays reminders related to patient care (e.g., reminders to provide medications, make vital sign measurements, check for pressure sores, etc.).

The risk details screen 401 also includes an alarm box 458. In response to selecting the alarm box 458, a screen is generated that displays a patient alarm.

Fig. 19 is an exemplary SIRS screen 500 generated when the SIRS window 440 is selected from the risk details screen 401 (see, e.g., fig. 16). The SIRS screen 500 includes a return icon 502 that, when selected, returns to the risk details screen 401 of fig. 12-18. The SIRS screen also includes an SBAR icon 504, which when selected, generates an SBAR screen that will be described in more detail below.

The SIRS screen 500 also includes a score box 505 and a risk situation box 507. The scoring block 505 includes the SIRS score 506, and a subset 508 of the vital sign measurements that affect the calculation of the SIRS score 506. The score box 505 also includes a required action panel 510, the required action panel 510 including a message to the caregiver that causes the caregiver to perform one or more actions based on the severity of the SIRS score 506. In the illustrative example, required action block 510 includes the message "call MD for immediate evaluation at bedside".

The risk context block 507 provides more detailed information about the SIRS score 506, which provides an overall view of the patient's status, enabling the caregiver to be aware of the patient's potential susceptibility to sepsis. The risk context block 507 includes additional vital sign measurements 512 that may be problematic and thus should be more closely monitored by the caregiver. In addition, risk context block 507 includes complications 514 to provide additional situational awareness to the caregiver.

Fig. 20 is an exemplary qsfa screen 520 that is generated when a qsfa window 444 (see, e.g., fig. 16) is selected from the risk details screen 401. The qsfa screen 520 includes the return icon 502 and the SBAR icon 504 described above.

The qsfa screen 520 includes a qsfa box 522 that includes a qsfa score 524 and a subset 526 of the calculated vital sign measurements that affect the qsfa score 524. Additionally, qSOFA screen 520 includes a sepsis risk context box 528, where the sepsis risk context box 528 includes a message box 530, where the message box 530 includes a message related to a scenario of sepsis risk for a particular patient. In the illustrative example, sepsis risk scenario block 528 includes the message "no potential risk scenario detected". Additionally, sepsis risk context box 528 includes complications 532 to provide additional situational awareness to the caregiver.

Fig. 21 and 22 are exemplary fall risk screens 540 generated when a fall risk window 448 (see, e.g., fig. 16) is selected from the risk details screen 401. The fall risk screen 540 includes the return icon 502 and the SBAR icon 504 described above. The fall risk screen 540 also includes a risk context box 542, the risk context box 542 including a MORSE icon 544 and a MORSE score 546. The context block 542 also includes an activity block 548 and a medication block 550. The activity box 548 lists the patient's condition affecting the MORSE score 546, and the medication box 550 lists the medications the patient takes that affect the MORSE score 546. The fall risk screen 540 also includes a required action box 552, the required action box 552 including one or more actions performed by the caregiver based on the severity of the MORSE score 546.

In fig. 21, the MORSE score 546 is displayed as "45" and the MORSE icon 544 and required action box 552 highlights a color (e.g., yellow) to reflect the severity of the MORSE score 546. In the example of fig. 21, activity box 548 ranks visual impairment and hip replacement as factors that affect the severity of the calculated MORSE score 546. The one or more actions listed in the required action box 552 vary depending on the severity of the MORSE score 546. In the illustrative example, the required action box 552 lists actions such as "set bed alarm and chair alarm" and "schedule a visit for voiding every two hours.

In fig. 22, the MORSE score 546 is shown as "60" and accordingly the MORSE score 544 and the required action box 552 are highlighted in a different color (e.g., red) to reflect the increased severity of the MORSE score 546. In the illustrative example of fig. 22, activity box 548 lists vision impairment and hip replacement, and drug block 550 lists the sedative administered to the patient as a factor affecting the severity of the calculated MORSE score 546. For example, the required action box 552 lists actions such as "consider moving the patient closer to the nurse station", "consider the most sensitive bed alarm settings", and "medication check".

Fig. 23 is an exemplary sepsis risk screen 560 generated when a sepsis risk box 460 (see, for example, fig. 18) is selected from the risk details screen 401. Sepsis risk screen 560 includes return icon 502 and SBAR icon 504 described above. Sepsis risk screen 560 includes a required action box 562, which required action box 562 includes one or more required actions 564 to be performed by a caregiver based on the calculated severity of sepsis risk. In the illustrative example, the one or more required actions 564 include "call MD for immediate evaluation at bedside". The sepsis risk screen 560 includes a sepsis risk context box 566 that includes the sepsis risk icon 462, SIRS score 442, vital sign measurements 512, and comorbidities 514 described above.

Fig. 24 and 25 are exemplary fall risk screens 580 generated when the fall risk block 464 is selected from the risk details screen 401 (see, e.g., fig. 18). The fall risk screen 580 includes the return icon 502 and the SBAR icon 504 described above. In addition, the fall risk screen 580 includes a required action block 582, the required action block 582 including one or more required actions 584 to be performed by the caregiver based on the calculated severity of the fall risk. In the illustrative example of fig. 24, the required measures 584 include "set bed alarm and chair alarm" and "schedule a visit for voiding every two hours". In the illustrative example of FIG. 25, the required actions 584 include "consider moving the patient closer to the nurse station," consider the most sensitive bed alarm settings, "and" medication check. Other measures are also contemplated as desired.

The fall risk screen 580 also includes a MORSE risk context box 586 that includes a MORSE icon 544, a MORSE score 546, an activity box 548 listing the condition of the patient affecting the MORSE score 546, and a medication box 550 listing the medications taken by the patient that affect the MORSE score 546, as has been described above with reference to fig. 21 and 22.

FIG. 26 is a case, background, evaluation, advice (SBAR) screen 600 generated when the

SBAR icons

426, 504 are selected. As described above, the SBAR function ensures that the patient's risk of deterioration is timely communicated to the appropriate caregiver upon the occurrence of a hand-off or upgrade event, so as to effectively convey information of the patient's risk of deterioration.

Referring now to fig. 26, the SBAR screen 600 includes a return icon 502 that, when selected, returns to the risk details screen 401 of fig. 12-18. The SBAR screen 600 also includes a case box 602, a background box 604, an evaluation box 606, and a suggestion box 608. The caregiver may use the case block 602 to describe the previous patient event. Examples of previous patient events may include falls, injuries, diagnoses, exacerbations, and the like. In the illustrative example, the case 602 includes a date and time column 614 for indicating when the event occurred.

The caregiver may use the context box 604 to describe context information to explain the patient's medical history or condition prior to the event occurring. The caregiver may use evaluation box 606 to provide their evaluation of the event and the caregiver may use advice box 608 to provide their advice. Thus, when a hand-off event occurs (e.g., a shift of one caregiver ends and a shift of another caregiver begins), the SBAR screen 600 may facilitate efficient communication of information of patient condition and risk of deterioration.

SBAR screen 600 also includes a call icon 610 that the caregiver can select to call the caregiver completing SBAR screen 600 to follow up. In addition, SBAR screen 600 includes a call RRT icon 612 that a caregiver can select to call a quick response team (RRT), also known as the Medical Emergency Team (MET) and the High Acuity Response Team (HART), so that the team can respond to patients with early signs of deterioration to prevent respiratory or cardiac arrest.

Fig. 27-29 are exemplary vital signs screens 700 for displaying trends in vital signs measurements over time. As described above, in some examples, the vital signs screen 700 is generated in response to selection of the arrow icon 418 next to the patient data 416 on the risk details screen 401 of fig. 12-18. In other examples, the vital signs screen 700 is generated in response to selection of the arrow icon 410 on the patient screen 400 of fig. 11. The vital signs screen 700 includes an arrow icon 702 that, when selected, returns to the risk details screen 401 or the patient screen 400.

In fig. 27, the vital signs screen 700 includes a vital signs panel 704 that displays various vital signs measurements. An arrow icon 706 is included alongside some vital signs to indicate whether the vital sign is up (e.g., an up arrow icon) or down (e.g., a down arrow icon) compared to a previous reading. When this information is missing, dash icons 708 are displayed next to some vital signs; when this information expires, a timestamp icon 710 is displayed next to some vital signs. Furthermore, if this information is missing (heart rate in fig. 27) or outdated (body temperature in fig. 27), some vital signs will become gray.

In fig. 27, the vital signs screen 700 also includes a measurement panel 712 listing one or more vital signs 714. Each listed vital sign 714 includes a date and time column 716 that indicates when the last update time for the vital sign measurement was. In addition, some vital signs 714 include a graph 718 that displays vital sign trends monitored over time. In addition, each vital sign 714 includes an arrow icon 720 that can be selected to display the selected vital sign in more detail for visual presentation. For example, selecting arrow icon 720 may cause a trend of the vital sign over a longer time to be displayed. Other configurations are also contemplated.

In fig. 28, another vital signs screen 700 includes an arrow icon 702 and an SBAR icon 504. When arrow icon 702 is selected, return to risk details screen 401 or patient screen 400; when the SBAR icon 504 is selected, an SBAR screen 600 (see fig. 26) is generated. In fig. 28, a list of vital signs 714 is displayed. Each vital sign 714 includes a graph 718 that displays a trend of the vital sign monitored over time.

In fig. 29, another vital signs screen 700 includes the arrow icon 702 and the SBAR icon 504 described above. In fig. 29, a list of vital signs 714 is displayed. Each vital sign 714 includes a positive marker 722 and a negative marker 724. When the positive marker 722 is selected, it expands the vital sign to display the graph 718; when the negative marker 724 is selected, it contracts the vital sign to hide the graph 718 and displays the current measurement 726 of the vital sign. In the illustrative example of fig. 29, up to four graphs of vital signs 714 can be viewed at one time. Other configurations are also contemplated.

Referring now to fig. 30, another exemplary patient screen 750 is illustrated by the mobile application of the mobile device of fig. 3 and 6. The patient screen 750 includes a list 752 of patients assigned to caregivers logged into the mobile device 60 or otherwise associated with the mobile device 60. Each patient assigned to a caregiver is displayed in a separate row of the list 752, including the patient's name. The caregiver may select a particular patient from the list 752 to access further information, such as the screen 800 shown in fig. 31 or the main patient view 830 shown in fig. 32. An exacerbation icon 760 is displayed next to the patient "Robert, Laura" to indicate that the patient is at risk of exacerbation. The deterioration icon 760 can optionally include an indicator of the severity of the deterioration, such as a rating indicator (e.g., low, medium, high), a color indicating the severity (e.g., green, yellow, red), and/or a numerical value indicating the severity of the deterioration.

The patient screen 750 also includes an alarm indicator 756 and a task indicator 758 that list the number of alarms ("1") and tasks ("2"), respectively, associated with the patient. This provides the caregiver with an effective visual indication of the status of a particular patient in a summary format. The caregiver can further select the alert indicator 756 to access additional patient information associated with patient-specific Alerts (e.g., similar to but patient-specific Alerts shown in FIG. 35; patient-specific Alerts can also be accessed by selecting "Alerts" (Alerts) in the option selector 804), and can select the task indicator 758 to access further task information, as shown in FIG. 34.

Fig. 31 shows an exemplary screen 800 that may be accessed after a particular patient is selected from the patient list 752 on the patient screen 750. The screen 800 includes patient identification information 802 (in this case directory information such as name ("Roberts, Laura"), location, patient ID, and gender). In the illustrative example, "Chat" (Chat) is selected in option selector 804, whereby Chat thread 806 is shown by the mobile application of the mobile device of fig. 3 and 6.

In general, the chat thread 806 provides a chronological sequence of messages sent by various caregivers associated with a patient that are similar to messages provided in a text messaging application on a mobile device. In this example, message 808 is from a first caregiver and gives care information about the patient. A response message 810 from the caregiver on the mobile device is also shown.

Chat thread 806 also includes patient status information embedded in message 812. Such patient status information may take a variety of forms. In this example, the patient status information includes an early warning score status (e.g., MEWS) and related vital sign information such as respiratory rate and body temperature. Other vital signs may also be included in the message 812. The caregiver may select message 812 to access additional details about the patient, such as the details shown in fig. 32-34.

This configuration of the chat thread 806 is advantageous because it enables caregivers to efficiently and directly share relevant patient information with other caregivers (e.g., by selecting a simple "share" button). Other caregivers can easily view and use this information directly from chat thread 806 without additional control input from other caregivers.

Referring now to fig. 32, a main patient view 830 is provided. The main patient view 830 may be accessed, for example, by selecting "Details" on the options selector 804. In this main patient view 830, a caregiver can be provided with a summary of vital signs, early warning scores, sepsis risk, and other information (e.g., fall risk).

The main patient view 830 includes patient identification information 832 (e.g., catalog information such as patient name and gender, date of birth, and room assignment) and provides vital sign information such as NIBP, RR, body temperature, SpO2, heart rate, and level of consciousness. Other vital signs may also be provided. In addition, each vital sign can be color coded to allow the caregiver to easily determine where the problem is. For example, if the patient's breathing rate is elevated, the breathing rate may be displayed in a different color (e.g., red or yellow) or otherwise highlighted to indicate that the problem is present.

The main patient view 830 also includes early warning score information 836, such as MEWS. The early warning score information 836 may include numerical values, and may also be color-coded or otherwise highlighted to indicate that a problem is present. Finally, main patient view 830 includes other information, such as sepsis risk information 838. This example includes the SIRS score of the patient. Various icons may also be provided and encoded (e.g., color coded) to indicate a particular sepsis risk.

Fig. 33-34 illustrate a secondary patient view 840, which secondary patient view 840 may be accessed, for example, by selecting a message 812 from the chat thread 806. The secondary patient view 840 provides vital signs, early warning score information, and other patient information in a more crude manner for easier use. The secondary patient view 840 includes highlighted early warning score information 836 so that the caregiver can easily determine the overall health status of the patient. Specific vital sign information 834 is also provided, as well as relevant risk context information 846 (in this case, the risk factor is age-68 years). Other information may be provided.

The secondary patient view 840 shown in fig. 34 also includes task information 850 associated with the patient. Task information 850 includes one or more tasks associated with the patient or otherwise suggested, as well as controls 852 (call caregiver) or 854 (initiate transfer) for performing such tasks. For example, controls 852, 854 may be selected to indicate completion of a task. In other examples, if control 852 is selected, a primary care-giver associated with the patient may be called directly through a phone function associated with mobile device 60.

Referring now to FIG. 35, an alarm view 860 is shown, the alarm view 860 having information regarding one or more alarms associated with a caregiver. In this example, the alarm view 860 includes a chronological task list of the caregiver. The tasks may be arranged in other orders, such as in order of importance of the tasks.

The first alert 862 includes information identifying the task (e.g., time of task generation; type of task, e.g., clinical task; icon showing task importance, etc.), patient information (e.g., room number, name), and task topic. In this case, the task topic of the first task 862 is a change in early warning score (MEWS increase), which indicates that the patient is likely to metastasize.

Further, the first task 862 includes an operable control 864 that enables a caregiver to take action with respect to the first task 862. In this example, the measures include confirming the task, confirming the task and viewing the relevant information (e.g., MEWS), and denying the task (e.g., reassigning to other caregivers).

The second alert 866 is associated with a nurse call performed by the patient. The second task 866 includes similar information and includes an operational indicator 868 that enables the caregiver to confirm the call.

In this example, many different integrations would send notifications to the alert view 860, including possible tasks (as shown by the first task 862) and a nurse call (the second alert 866). It may also include other integrations such as pager or EMR notifications (e.g., critical laboratory value alerts). As previously described, by selecting the "Alerts" (Alerts) of the option selector 804, the patient-centric version of FIG. 35 will be shown in the "Alerts" tab of the screen 800 shown in FIG. 31. The entries in the alerts view 860 are depicted in chronological order, but other alternative ways of displaying and filtering alerts may be provided, such as by alert type and/or priority.

With respect to calculating a Fall risk score according to the present invention, further details may be found in U.S. provisional patent application No. 62/818,828 entitled "patent Fall likhood" filed on 3/15 of 2019 and U.S. provisional patent application No. 62/818,836 entitled "patent Fall likhood and safety", filed on 3/15 of 2019, the entire contents of which are incorporated herein by reference without conflict with the present disclosure, to the extent any conflict arises. According to both provisional patent applications, a fall risk score (or fall score only) is determined based on the following formula:

fall score-instant risk model score + attribute risk model score.

The immediate risk model score is based on the following formula:

instant risk model score-data 1 x weight 1+ data 2 x weight 2+ … data N x weight N,

where the data may include activity over a given period of time (e.g., a period of sleep like a toilet), medication changes, detected acute patient movement, and the like. Thus, the instant risk model score is a numerical quantification of the likelihood of an instant fall, where each relevant data is weighted and added to produce a score. For example, acute motion of a patient may be weighted more heavily than drug changes.

The attribute risk model score is based on the following formula:

attribute risk model score-data 1 × weight 1+ data 2 × weight 2+ … data N × weight N,

wherein the data may include directory/demographic information associated with the patient such as history of falls, age, frequency or urgency of urination, type of medication taken, progress of the patient's walking, gait analysis, etc. Thus, the attribute risk model score is a numerical quantification of the likelihood of a fall based on patient attributes collected over time, with each relevant data weighted and added to produce a score. For example, a patient's poor gait may be weighted more heavily than the patient's movement over time in the bed.

With respect to the particular apparatus for detecting and monitoring sepsis according to the present invention, more detailed information can be found in U.S. provisional patent application No. 62/825,844 entitled "PatientFallLikeliood" filed on 29.3.2019 ("the' 844 application"), the entire contents of which are incorporated herein by reference without conflict with the present disclosure, to which the present disclosure controls if any conflict arises. The device disclosed in the' 844 application provides further examples of the types of medical devices 14 of the system 10 that provide data to the analysis engine 20. For example, the' 844 application contemplates that an ECG or photoplethysmograph (PPG) or radar transmitter/receiver may detect heart rate variability of a patient and if the heart rate variability decreases, which is an indicator of sepsis onset, the rate at which vital sign data is acquired may increase. The' 844 application incorporates by reference the relevant disclosure in U.S. provisional patent application No. 62/798,124 filed 2019 on month 1 and 29 regarding monitoring devices using radar signals. Accordingly, U.S. provisional patent application No. 62/798,124, filed 2019, 1, 29, is hereby incorporated by reference in its entirety, also for the same purpose.

Further, according to the '844 application, a fundus imaging system including a camera is used to capture images of a patient's fundus (e.g., retina, optic nerve, macula, vitreous, choroid, and posterior pole) throughout a cardiac cycle. The images are analyzed to determine whether the patient has microvascular dysregulation (which is another indicator of the onset or presence of sepsis). The fundus imaging system may also be configured to measure a scintillation response of the patient by: the retinas of the patients were exposed to a flash lamp, and then the retinal vascular reactivity was measured (retinal vascular reactivity of the septic patients decreased due to neurovascular isolation). Still further, the fundus imaging system may also be configured to measure local oxygenation of the retina to determine whether the patient has sepsis. The fundus imaging system may also be configured to measure changes in blood flow velocity to detect that the patient has sepsis because the vessel walls become "sticky" and the blood cells become stiff, resulting in sluggish blood flow in septic patients. The fundus imaging system may also be configured to measure vessel diameter and lumen-wall thickness ratio as a function of the deregulation of the vasomotor response in septic patients. Thus, based on the foregoing, it should be appreciated that the present disclosure contemplates, in some embodiments, the analysis engine 20 processing and analyzing image data from the fundus imaging system for sepsis determination.

Further, according to the '844 application, screening a patient for sepsis includes using a PPG measurement, a bioimpedance measurement, a skin perfusion measurement, or a temperature measurement at the patient's skin. During the early onset of sepsis, vasodilation occurs in the endothelial layer and the application of stimuli to the patient's skin to produce these measurements results in a less differential vasodilation in septic patients than in non-septic patients. The ' 844 application discloses a temperature sensing device that applies a range of temperatures to a patient's skin using a Peltier heater and cooler that heat or cool the patient's skin, respectively, based on the direction of current flow therethrough (e.g., the polarity of the applied voltage). PPG sensors measure the response of a patient's microvasculature to temperature changes. In some embodiments, the PPG sensor comprises Infrared (IR) red and green Light Emitting Diodes (LEDs).

The ' 844 application also discloses an impedance sensor that includes a plurality of electrodes attached to a patient's skin surface through which a low voltage (up to 10 volts) sinusoidal signal is applied through the patient's skin. The impedance of the patient's skin between the electrodes is determined after heating and cooling the skin with the temperature sensing device. The measured electrical impedance is then used to determine microvascular response. In another aspect of the' 844 application, a portion of a patient support device (e.g., a hospital bed) is moved to elevate a limb of a patient and determine whether a septic patient is responsive to fluid resuscitation therapy. In some embodiments, the head or leg of the hospital bed is raised to determine the patient's great vessel response by using vital sign measurements to determine the response to fluid moving from the raised limb to the patient's heart.

In addition to the risk factors or data elements in tables 1-10 above, the present invention contemplates that any one or more of the data elements in table 11 below may be used to calculate a risk score or make a risk determination, including calculating patient fall scores, stress injury scores, and sepsis scores as discussed herein (some of the data elements are risk factors, including the same risk factors as listed in table 1):

TABLE 11

In table 11, the bold entry in the data element column is a title or data element category, and the data elements listed below the bold title row are data elements in the bold category.

According to the present disclosure, the form is "at least one of a and B" and "at least one of: phrases of A and B "and similar such phrases mean" A or B, or both A and B ". In the form of "at least one of a or B" and "at least one of: phrases of A or B "and similar such phrases also mean" A or B, or both A and B ".

Although certain illustrative embodiments have been described in detail above, many embodiments, variations, and modifications are possible, which are still within the scope and spirit of the disclosure as described herein and as defined by the appended claims.

Claims

1. A mobile device, comprising:

an engine programmed to receive one or more sources of patient data providing patient identification information, vital sign information, alarm information, and task information; and

a display of the mobile device, the display providing a screen having:

a first window having a list of patients assigned to a caregiver; and

a second window having a plurality of vital signs and early warning scores associated with a patient of the caregiver.

2. The mobile device of claim 1, wherein the list of patients in the first window includes a task indicator or an alert indicator associated with the patient.

3. The mobile device of claim 2, wherein the task indicator provides a numerical value associated with a plurality of tasks associated with the patient.

4. The mobile device of claim 3, wherein the task indicator is selectable to access a third window having details regarding one or more tasks associated with the patient.

5. The mobile device of claim 4, wherein each of the one or more tasks includes a selectable control that enables the caregiver to confirm a task.

6. The mobile device of claim 2, wherein the alert indicator provides a numerical value associated with a plurality of alerts associated with the patient.

7. The mobile device of claim 6, wherein the alert indicator is selectable to access a third window having details regarding one or more alerts associated with the patient.

8. The mobile device of claim 1, further comprising a third window comprising one or more messages from the caregiver associated with the patient.

9. The mobile device of claim 8, wherein the third window is a chat window that enables the caregiver to send the one or more messages to other caregivers.

10. The mobile device of claim 8, wherein the third window comprises one or more vital signs or early warning scores associated with the patient embedded in the one or more messages.

11. A system, comprising:

one or more medical devices programmed to acquire patient data;

a network; and

a mobile device, comprising:

an engine programmed to receive the patient data from the one or more medical devices over the network, the patient data providing patient identification information, vital sign information, alarm information, and task information; and

a display of the mobile device, the display providing a screen having:

a first window having a list of patients assigned to a caregiver; and

12. The system of claim 11, wherein the list of patients in the first window includes a task indicator or an alert indicator associated with the patient.

13. The system of claim 12, wherein the task indicator provides a numerical value associated with a plurality of tasks associated with the patient.

14. The system of claim 13, wherein the task indicator is selectable to access a third window having details regarding one or more tasks associated with the patient.

15. The system of claim 14, wherein each of the one or more tasks includes a selectable control that enables the caregiver to confirm a task.

16. The system of claim 12, wherein the alarm indicator provides a numerical value associated with a plurality of alarms associated with the patient.

17. The system of claim 16, wherein the alert indicator is selectable to access a third window having details regarding one or more alerts associated with the patient.

18. The system of claim 11, further comprising a third window comprising one or more messages from the caregiver associated with the patient.

19. The system of claim 18, wherein the third window is a chat window that enables the caregiver to send the one or more messages to other caregivers, and the third window includes one or more vital signs or early warning scores associated with the patient embedded in the one or more messages.

20. A method for displaying patient information on a mobile device, the method comprising:

receiving one or more patient data sources providing patient identification information, vital sign information, alarm information, and task information;

displaying a first window on the mobile device with a list of patients assigned to a caregiver, the list of patients in the first window including a task indicator or an alert indicator associated with the patient;

displaying a second window on the mobile device having a plurality of vital signs and early warning scores associated with a patient of the caregiver;

displaying a third window on the mobile device including one or more messages from the caregiver associated with the patient; and

causing the caregiver to embed vital sign information in the one or more messages sent to other caregivers in the third window.