CN112786167B

CN112786167B - MapReduce and big data-based statistical method and device for operating case times of antibacterial drug application

Info

Publication number: CN112786167B
Application number: CN202011311715.0A
Authority: CN
Inventors: 林�建; 霍瑞; 陈春平
Original assignee: Hangzhou Xinglin Information Technology Co ltd
Current assignee: Hangzhou Xinglin Information Technology Co ltd
Priority date: 2020-11-20
Filing date: 2020-11-20
Publication date: 2023-08-18
Anticipated expiration: 2040-11-20
Also published as: CN112786167A

Abstract

The invention provides a MapReduce and big data based statistical method and device for the times of the operation cases of applying antibacterial drugs, which divide the times of millions and tens of millions of cases of hospitalized bacteria which exceed the memory and storage limit of a server into tens of millions and hundreds of millions of small tasks based on the MapReduce framework and by utilizing the parallel computing capacity of a machine under a distributed system, execute the small tasks on a plurality of machines simultaneously, and then generate a final result by summarizing the intermediate output results of a plurality of small tasks. The invention can perform mass parallel calculation on large data containing millions, tens of millions and billions of hospitalization times according to various calibers such as provincial regions, hospital grades, hospital beds, comprehensive and special departments, public and civil camps and the like, has strong practicability of the counted operation cases of applying the antibacterial drugs, can accurately count the operation cases according to the needs of users, and can provide effective guidance for the treatment and management of the antibacterial drugs of hospitalized patients.

Description

MapReduce and big data-based statistical method and device for operating case times of antibacterial drug application

Technical Field

The invention belongs to the technical field of antibacterial drug management, and particularly relates to a method and a device for counting the number of cases of antibacterial drug application based on MapReduce and big data, in particular to a method and a device for counting the number of cases of antibacterial drug preventive application in I-type incision operation in inpatients, which are particularly suitable for the situations that the data size of the patients to be processed far exceeds the storage (magnetic disk) and the computing power (memory and CPU) of a server and task splitting and distribution cannot be performed manually.

Background

The antibacterial drug generally refers to a drug with bactericidal or bacteriostatic activity, and the invention and the application of the antibacterial drug bring convenience for treating a plurality of serious bacterial infectious diseases for human beings, and effectively reduce the death rate of various infectious diseases. The application of the antibacterial agent needs to be reasonably selected according to different infectious diseases.

For hospitalized patients, nosocomial infections fall into two categories: exogenous infection, also called cross infection, refers to infection that a patient or staff receives in a hospital through daily diagnosis and treatment activities, contact between patients or from polluted environments, such as infection occurring at a surgical site; and secondly, endogenous infection, also called self infection, refers to infection caused by disorder of normal flora in a patient and potential bacteria of the body, displacement of resident microorganisms originally existing in a body cavity or a body surface of the patient and the like in the diagnosis and treatment process due to the fact that the body resistance of the patient is reduced. Surgery on hospitalized patients is a common factor leading to infection of the patient. The patient is extremely harmful to the operation, so in the actual diagnosis and treatment process, antibacterial drugs are usually applied to the operation patient in advance, and the operation related infection is avoided.

However, the phenomenon of abuse of antibacterial agents often occurs clinically, which results in the occurrence of drug resistance of pathogenic bacteria to antibacterial agents, increasing the difficulty in healing bacterial infectious diseases. Therefore, the use of antibacterial agents should be reasonable since clinical practice, and the abuse of antibacterial agents should be stopped. Therefore, statistics of the number of surgical cases of applying the antibacterial drug has important significance for the management of the antibacterial drug, and can provide important guidance for the treatment of postoperative complications.

Therefore, how to realize statistics of the number of cases of using antibacterial drugs, especially statistics of the number of cases of using preventive drugs in cases of performing class I incision surgery in hospitalized patients, is a problem to be solved in the art.

The operation cases of applying the antibacterial drugs are relatively easy to calculate in one medical institution, the number of discharge of the medical institutions such as a common third class A is about fifty thousand per year, and the national or provincial tap hospitals have hundreds of thousands of people. The calculation of the key indexes under the condition of large data of millions, tens of millions, billions and billions of hospitalized patients in provincial areas or nationwide is much more complicated, 2749 of three-level hospitals in China in 2019, 9687 of two-level hospitals and 17487 of the hospitalized patients in public hospitals in 2019, and the original result of one-time statistical analysis is to calculate the time of nearly one year.

Therefore, how to develop standardized, normalized and homogeneous hospital infection monitoring in hundreds or thousands of hospitals in one area is the most urgent problem to be solved in developing an area informatization monitoring platform for the times of the operation cases of applying the antibacterial drugs in a specified time period under the condition of big data of inpatients.

Disclosure of Invention

The invention aims at overcoming the defects of the prior art and provides a MapReduce and big data based statistical method, device, equipment and storage medium for the times of the operation cases of applying antibacterial drugs. The operation case number counted by the invention is high in practicability, the operation case number can be counted accurately according to the user requirement, and effective guidance can be provided for the treatment and management of the antibacterial drugs of inpatients. Meanwhile, the problem of complex counting and processing of the times of the manual operation cases is avoided through automatic counting of the times of the operation cases.

In order to achieve the above purpose, the present invention adopts the following technical scheme:

the statistical method for the times of the operation cases of applying the antibacterial drugs based on MapReduce and big data comprises the following steps:

s1, acquiring hospitalization process information A of a patient, and acquiring the admission time and discharge time of the patient based on the hospitalization process information, wherein the admission time and the discharge time are taken as parameters g.MC2 together;

S2, acquiring operation information G of a patient, and acquiring operation information G (a) _Y occurring during the current hospitalization period and operation information G (a) _N occurring during the non-current hospitalization period in the operation information G based on the parameter g.MC2;

s3, judging whether an operation record exists in the operation information G (a) _Y, if so, executing the step S3, and if not, outputting the operation case frequency of preventive application of the antibacterial medicine in the I-type incision operation as 0;

s4, acquiring operation starting time and operation ending time based on the operation information G (a) _Y, and taking the operation starting time and the operation ending time as perioperative parameters g.QA4.open of the operation;

s5, collecting statistics time, operation departments, incision grades, operation classifications, operation doctors, anesthesia modes, operation duration, ASA scores, operation names, healing grades, operation positions, NNIS scores, emergency treatment in a selected period, operation rooms, operation times, antibacterial drug grades and drug administration modes selected by users, and determining authority departments of the users according to the identity information of the users;

s6, based on the operation information G (a) _Y, acquiring operation information G (S) _Y meeting the statistics time, the operation department, the incision grade, the operation classification, the operation doctor, the anesthesia mode, the operation duration, the ASA score, the operation name, the healing grade, the operation position, the NNIS score, the emergency treatment of the selected period, the operation room, the operation times and the limit of the authority department;

S7, judging whether an operation record exists in the operation information G (S) _Y, if yes, executing the step S8, and if not, outputting the operation case frequency of preventive application of the antibacterial medicine in the I-type incision operation as 0;

s8, acquiring an antibacterial medicine record F, and dividing the antibacterial medicine order record F into an antibacterial medicine record F (a) _Y used during patient hospitalization and an antibacterial medicine record F (a) _N not used during patient hospitalization based on the parameter g.MC2;

s9, acquiring an antibacterial drug record F (d) _Y in the antibacterial drug record F (a) _Y, wherein the purpose of drug use is to prevent, meet the antibacterial drug grade and the drug administration mode limit;

s10, judging whether antibacterial information exists in the antibacterial record F (d) _Y, if so, executing the step S11, and if not, outputting the operation case frequency of preventive application of the antibacterial in the I-type incision operation as 0;

s11, acquiring a medical order starting time and a medical order ending time based on the antibacterial drug record F (d) _Y, and jointly using the medical order starting time and the medical order ending time as parameters g.THW of a start-stop time period list of the medical order;

s12, dividing the operation information G (S) _Y into operation information G (t) _Y for using the antibacterial medicine in the perioperative period and operation information G (t) _N for not using the antibacterial medicine in the perioperative period based on the parameters g.THW and g.QA4. Open;

S13, outputting the number of operation cases of preventive application of the antibacterial medicine in the I-type incision operation based on the number recorded in the operation information G (t) _Y.

Further, the hospital procedure information includes a patient case number, an admission department, an admission time, an discharge department, and an discharge time; the operation information comprises patient case number, operation department, operation category, operation doctor, anesthesia mode, operation name, operation starting time, operation ending time, incision, healing grade, ASA, emergency treatment in period, operation position, NNIS score, operation room and operation times; the antibacterial record comprises a patient case number, an ordered department, an antibacterial name, a start time, an end time, an antibacterial grade, a drug administration mode, a drug purpose, an ordered doctor and an ordered doctor grade.

Further, the step S6 includes:

s61, filtering to obtain operation information G (b) Y within a statistical time range according to the operation information G (a) Y and the statistical time, and filtering operation information G (b) N not within the statistical time range;

s62, according to the operation information G (b) _Y and the authority department information, filtering to obtain operation information G (c) _Y within the authority range, and filtering operation information G (c) _N not within the authority range;

S63, according to the operation information G (c) _Y and the selected operation department, filtering to obtain operation information G (d) _Y in the selected operation department range, and filtering operation information G (d) _N not in the selected range;

s64, according to the operation information G (d) _Y, filtering to obtain operation information G (e) _Y of the type I incision selected by the user, and filtering operation information G (e) _N which is not in the selection range;

s65, according to the surgical information G (e) _Y and the selected surgical classification, filtering to obtain the surgical information G (f) _Y in the selected surgical classification range, and filtering the surgical information G (f) _N not in the selected range;

s66, according to the operation information G (f) _Y and the selected operation doctor, filtering to obtain operation information G (G) _Y in the selected operation doctor range, and filtering operation information G (G) _N not in the selected range;

s67, according to the operation information G (G) _Y and the selected anesthesia mode, filtering to obtain operation information G (h) _Y within the selected anesthesia mode range, and filtering operation information G (h) _N not within the selected range;

s68, according to the operation information G (h) _Y and the selected operation duration information, filtering to obtain operation information G (i) _Y within the selected operation duration range, and filtering operation information G (i) _N not within the selected range;

S69, according to the operation information G (i) _Y and the selected ASA score, filtering to obtain operation information G (j) _Y in the selected ASA score range, and filtering operation information G (j) _N not in the selected range;

s610, according to the operation information G (j) _Y and the selected operation name, filtering to obtain operation information G (k) _Y in the selected operation name range, and filtering operation information G (k) _N not in the selected range;

s611, according to the surgical information G (k) _Y and the selected healing grade, filtering to obtain the surgical information G (m) _Y within the selected healing grade range and filtering to obtain the surgical information G (m) _N not within the selected range;

s612, filtering to obtain surgical information G (N) Y in a selected surgical position range according to the surgical information G (m) Y and the selected surgical position information, and filtering to obtain surgical information G (N) N not in the selected range;

s613, filtering to obtain the surgical information G (p) _Y in the selected NNIS scoring range according to the surgical information G (N) _Y and the selected NNIS scoring, and filtering the surgical information G (p) _N not in the selected range;

s614, according to the operation information G (p) _Y and the selected period emergency information, filtering to obtain operation information G (q) _Y in the selected period emergency range, and filtering operation information G (q) _N not in the selected range;

S615, filtering to obtain operation information G (r) Y in the selected operating room range according to the operation information G (q) Y and the selected operating room, and filtering to obtain operation information G (r) N which is not in the selected range;

s616, according to the operation information G (r) _Y and the selected operation times, filtering to obtain operation information G (S) _Y in the selected operation times range, and filtering to obtain operation information G (S) _N not in the selected range.

Further, the step S9 includes:

s91, dividing the antibacterial drug record F (a) _Y into an antibacterial drug order F (b) _Y for preventive drugs and an antibacterial drug order F (b) _N for non-preventive drugs based on whether the purpose of medication is preventive or not;

s92, dividing the antibacterial drug record F (b) _Y into an antibacterial drug record F (c) _Y which is consistent with the antibacterial drug administration mode selected by a user and an antibacterial drug record F (c) _N which is not consistent with the antibacterial drug administration mode selected by the user based on the administration mode;

s93, based on the antibacterial drug grade, dividing the antibacterial drug record F (c) _Y into an antibacterial drug record F (d) _Y consistent with the antibacterial drug grade selected by the user and an antibacterial drug record F (d) _N not consistent with the antibacterial drug grade selected.

The invention also provides a device for counting the number of the surgical cases of applying the antibacterial drug based on MapReduce and big data, which comprises the following steps:

A first acquisition unit for acquiring hospitalization process information a of a patient, acquiring a time of admission and a time of discharge of the patient based on the hospitalization process information, and jointly serving as a parameter g.mc2;

a surgical information first dividing unit for acquiring surgical information G of a patient, and acquiring surgical information G (a) _y occurring during a present hospitalization period and surgical information G (a) _n occurring during a non-present hospitalization period in the surgical information G based on the parameter g.mc2;

a first judging unit, configured to judge whether an operation record exists in the operation information G (a) _y, if yes, execute step S3, and if not, output the number of cases of preventive application of the antibacterial agent in the class I incision operation as 0;

a second acquisition unit that acquires operation start time and operation end time based on the operation information G (a) _y, together as perioperative parameters g.qa4.open of the operation;

the third acquisition unit is used for receiving the statistics time, the operation department, the incision grade, the operation classification, the operation doctor, the anesthesia mode, the operation duration, the ASA score, the operation name, the healing grade, the operation position, the NNIS score, the emergency treatment in the first stage, the operation room, the operation times, the antibacterial medicine grade and the administration mode selected by the user, and determining the authority department of the user according to the identity information of the user;

The operation information dividing unit is used for acquiring operation information G(s) _Y meeting the statistics time, the operation department, the incision grade, the operation classification, the operation doctor, the anesthesia mode, the operation duration, the ASA score, the operation name, the healing grade, the operation position, the NNIS score, the selected emergency, the operation room, the operation times and the permission department limit based on the operation information G (a) _Y;

a second judging unit, configured to judge whether an operation record exists in the operation information G (S) _y, if yes, execute step S8, and if not, output the number of cases of preventive application of the antibacterial agent in the class I incision operation as 0;

an antibacterial drug record first dividing unit for acquiring an antibacterial drug record F, dividing the antibacterial drug order record F into an antibacterial drug record F (a) _y used during patient hospitalization and an antibacterial drug record F (a) _n not used during patient hospitalization based on the parameter g.mc2;

an antibacterial drug record dividing unit, configured to obtain an antibacterial drug record F (d) _y in the antibacterial drug record F (a) _y, where the purpose of drug administration is to prevent, satisfy the antibacterial drug grade and the administration mode limitation;

the third judging unit is used for judging whether antibacterial information exists in the antibacterial record F (d) _Y, if so, the fourth collecting unit is called, and if not, the operation case frequency of preventive application of the antibacterial in the I-type incision operation is output to be 0;

The fourth acquisition unit is used for acquiring the start time and the end time of the medical advice based on the antibacterial drug record F (d) _Y and jointly taking the start time and the end time of the medical advice as parameters g.THW of a start-stop time period list of the medical advice;

an antibacterial drug record fifth dividing unit for dividing the operation information G(s) _y into operation information G (t) _y for using antibacterial drugs in the perioperative period and operation information G (t) _n for not using antibacterial drugs in the perioperative period based on the parameter g.thw and the parameter g.qa4. Open;

and an output unit for outputting the number of cases of preventive application of the antibacterial agent in the class I incision operation based on the number recorded in the operation information G (t) _Y.

Further, the operation information dividing unit includes:

the surgical information second dividing unit is used for filtering to obtain surgical information G (b) Y within a statistical time range according to the surgical information G (a) Y and the statistical time, and filtering to obtain surgical information G (b) N not within the statistical time range;

the third division unit of the operation information is used for filtering the operation information G (c) Y within the authority range according to the operation information G (b) Y and the authority department information, and filtering the operation information G (c) N not within the authority range;

the fourth division unit of the operation information is used for filtering the operation information G (d) Y in the selected operation room range according to the operation information G (c) Y and the selected operation room, and filtering the operation information G (d) N which is not in the selected range;

a fifth division unit of operation information, which is used for filtering to obtain operation information G (e) _Y of the incision with the class I incision grade selected by the user according to the operation information G (d) _Y, and filtering operation information G (e) _N which is not in the selection range;

a sixth division unit of operation information, which is used for filtering operation information G (f) Y within the selected operation classification range according to the operation information G (e) Y and the selected operation classification, and filtering operation information G (f) N not within the selected range;

A seventh dividing unit of operation information, which is used for filtering operation information G (G) Y in the range of the selected surgeon according to the operation information G (f) Y and the selected surgeon, and filtering operation information G (G) N not in the range of the selected surgeon;

the eighth division unit of the operation information is used for filtering the operation information G (h) Y within the selected anesthesia mode range according to the operation information G (G) Y and the selected anesthesia mode, and filtering the operation information G (h) N not within the selected range;

the ninth division unit of the operation information is used for filtering operation information G (i) _Y within the selected operation duration range according to the operation information G (h) _Y and the selected operation duration information, and filtering operation information G (i) _N not within the selected range;

a tenth dividing unit of operation information, which is used for filtering operation information G (j) _Y within the selected ASA scoring range according to the operation information G (i) _Y and the selected ASA scoring, and filtering operation information G (j) _N not within the selected range;

an eleventh surgical information dividing unit for filtering out surgical information G (k) N not in the selected surgical name range according to the surgical information G (j) Y and the selected surgical name;

A twelfth surgical information dividing unit for filtering to obtain surgical information G (m) Y within the selected healing level range and filtering surgical information G (m) N not within the selected range according to the surgical information G (k) Y and the selected healing level;

a thirteenth division unit of operation information, which is used for filtering operation information G (N) _Y in the selected operation position range according to the operation information G (m) _Y and the selected operation position information, and filtering operation information G (N) _N not in the selected range;

a fourteenth division unit of operation information, which is used for filtering operation information G (p) _Y within the selected NNIS scoring range according to the operation information G (N) _Y and the selected NNIS scoring, and filtering operation information G (p) _N not within the selected range;

a fifteenth division unit of operation information, which is used for filtering operation information G (q) _Y in the selected period emergency treatment range according to the operation information G (p) _Y and the selected period emergency treatment information, and filtering operation information G (q) _N which is not in the selected range;

a sixteenth surgical information dividing unit for filtering the surgical information G (r) Y within the selected operating room according to the surgical information G (q) Y and the selected operating room, filtering the surgical information G (r) N not within the selected operating room;

A seventeenth dividing unit for filtering the surgical information G(s) Y within the selected surgical frequency range and filtering the surgical information G(s) N not within the selected range according to the surgical information G (r) Y and the selected surgical frequency.

Further, the antibacterial drug record dividing unit includes:

an antibacterial drug record second dividing unit for dividing the antibacterial drug record F (a) _y into an antibacterial drug order F (b) _y for preventive administration and an antibacterial drug order F (b) _n for non-preventive administration based on whether the purpose of medication is preventive or not;

an antibacterial drug record third dividing unit for dividing the antibacterial drug record F (b) _y into an antibacterial drug record F (c) _y conforming to the user-selected antibacterial drug administration mode and an antibacterial drug record F (c) _n not conforming to the antibacterial drug administration mode selection, based on the administration mode;

an antibacterial drug record fourth dividing unit for dividing the antibacterial drug record F (c) _y into an antibacterial drug record F (d) _y consistent with the antibacterial drug grade selected by the user and an antibacterial drug record F (d) _n not consistent with the antibacterial drug grade selected based on the antibacterial drug grade.

The invention also provides computer equipment, which is characterized by comprising a memory and a processor, wherein the memory is stored with a computer program, and the processor realizes the counting method of the operation cases using the antibacterial medicine when executing the computer program.

The invention also provides a storage medium, which is characterized in that the storage medium stores a computer program, and the computer program can realize the statistical method of the operation cases of applying the antibacterial medicine when being executed by a processor.

The invention details the specific implementation mode of statistics of the operation cases of applying the antibacterial drugs, utilizes hospitalization process information, antibacterial drug doctor advice records, operation information, selected statistics time, operation departments, incision grades, operation classifications, operation doctors, anesthesia modes, operation duration, ASA scores, operation names, healing grades, operation positions, NNIS scores, emergency treatment in a selected period, operation rooms, operation times, antibacterial drug grades and administration modes, determines the authority departments of users according to the identity information of the users, and determines the operation cases of I-type incision operations of hospitalized patients and preventive application of the antibacterial drugs. The operation case number counted by the invention is strong in practicability, the operation case number can be counted accurately according to the user requirement, and effective guidance can be provided for the treatment and management of the antibacterial drugs of inpatients. Meanwhile, the problem of complex counting and processing of the times of the manual operation cases is avoided through automatic counting of the times of the operation cases.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a flow chart of a statistical method for the number of cases of an antibacterial drug application based on MapReduce and big data according to an embodiment of the present invention;

fig. 2 is a schematic block diagram of each unit of a statistical device for the number of cases of antimicrobial drug application based on MapReduce and big data according to an embodiment of the present invention.

Detailed Description

The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

It should be understood that the terms "comprises" and "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

The invention is further described below with reference to the drawings and specific examples, which are not intended to be limiting.

It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

It should be further understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.

In the following examples, the X (y) type is described:

X represents a data set with a certain type;

y represents a sequence number, and is used for distinguishing data sets of the same type of data before and after in different logic units;

x (y) represents the data set under different logical units for a certain type of data;

y represents a compliance;

n represents an unconformity;

the embodiment provides a statistical method for the number of times of the operation cases of applying the antibacterial drug based on MapReduce and big data, and the statistical method is applied to a server, for example, a cloud server. The server obtains hospital data. Hospital data is processed. As shown in fig. 1, the statistical method of the number of operations of applying the antibacterial agent includes the following steps S1 to S13:

s1, acquiring hospitalization process information A of a patient, and acquiring the time of admission and the time of discharge of the patient based on the hospitalization process information, wherein the time and the time of admission and the time of discharge of the patient are taken as parameters g.MC2 together;

the number of cases of preventive application of antibacterial drugs in the class I incision surgery is the number of cases of hospitalized patients performing class I incision surgery and using preventive drugs. The need to identify surgical patients for prophylactic use of antibacterial agents in class I incision surgery is met by: 1. the patients are hospitalized simultaneously, and the time of the patient's admission and discharge is within a statistical time range. I.e. the time period formed by the time of admission and discharge of the patient, and the statistical time are crossed; 2. class I incision surgery is performed during patient hospitalization, and antibacterial agents are used prophylactically during perioperative surgery. The corresponding condition is that the perioperative period of the operation and the administration time period of the preventive medication are crossed; 3. the condition of the user's selection is satisfied.

The inpatient process information is used for integrally recording inpatient processes, and specifically comprises a patient case number, an inpatient department, an inpatient time, an inpatient department and an inpatient time. The invention firstly acquires the hospitalization process information A of the patient, and further acquires relevant information of the admission time and discharge time fields in the hospitalization process information A, and the hospitalization process information A and the discharge time are taken as parameters g.MC2 together.

For example, the hospitalization procedure information a is:

patient case number	Department of admission	Time of admission	Department of discharge	Discharge time
					123456(1)	Neurology department	2019-01-01 00:00:12	Rehabilitation department	2019-01-12 03:00:12

And (3) outputting: MC2, which has a value of [ 2019-01-01:00:12, 2019-01-12:03:00:12 ]

the operation information is used for recording specific conditions of the operation performed by the patient, including patient case number, operation department, operation category, operation doctor, anesthesia mode, operation name, operation starting time, operation ending time, incision, healing grade, ASA, emergency treatment, operation position, NNIS score, operation room and operation times. In order to know the operation record information of the error time which does not occur in the hospitalization period, the invention firstly screens the collected operation information G, and selects the operation information G (a) _Y which is performed in the time range of patient admission and discharge, namely the operation information G (a) _Y which occurs in the hospitalization period. Specifically, the present invention filters out the operation information G (a) _n that the operation time does not occur during the present hospitalization period based on the comparison of the "operation start time", "operation end time" fields and the discharge-in time parameter g.mc2 in the operation information, and obtains the operation information G (a) _y that is performed in the discharge-in time range of the patient.

For example, the collected operation information G is:

for the above g.MC2 [ 2019-01-01:00:12, 2019-01-12 03:00:12], then the corresponding G (a) _Y is:

g (a) _N is:

and S3, judging whether an operation record exists in the operation information G (a) _Y, if so, executing the step S3, and if not, outputting the operation case frequency of preventive application of the antibacterial medicine in the I-type incision operation as 0.

Specifically, the invention judges according to the operation information G (a) _Y, if the patient still has records after the steps, the operation is continued downwards, if the patient does not have records, the operation is ended, and the result 0 is output.

For example, for G (a) _y described above, two records are included, and thus step S3 is continued to be performed.

the invention determines the parameter of the perioperative period based on the operation information G (a) _Y, and prepares for acquiring intersection operation information in the perioperative period and doctor's advice time range subsequently. The perioperative phase is a whole process surrounding the operation, starting from the patient's decision to receive the surgical treatment, to the surgical treatment until substantial recovery, including a period of time before, during and after the operation, specifically from the time the surgical treatment is determined until the treatment associated with this operation is substantially completed. In the present invention, the perioperative time is determined as one day before the operation start time to one day after the operation end time.

For example, for the above-mentioned surgical information G (a) _Y, the perioperative parameter g.QA4.open, values are [ 2019-01-06:08:00, 2019-01-08:30:00 ] and [ 2019-01-08:00:00, 2019-01-10:09:30:00 ].

S5, receiving statistics time, surgery department, incision grade, surgery classification, surgeons, anesthesia mode, surgery duration, ASA score, surgery name, healing grade, surgery position, NNIS score, emergency treatment in a selected period, surgery department, surgery times, antibacterial medicine grade and administration mode selected by a user, and determining authority department of the user according to identity information of the user;

the invention is used for automatic statistics of the operation cases of preventive application of antibacterial drugs in the class I incision operation, so that a user is required to select a corresponding time period, namely, the user selects a corresponding statistics time, and statistics and search are carried out on the class I incision operation patients discharged in the statistics time. In addition, for the type I incision surgery patient, the user usually manages the number of cases for a specific surgery department, so the invention sets a corresponding surgery department besides counting time. In addition, aiming at specific operations, the user can select the operation name, the operation classification, the operation doctor, the anesthesia mode, the operation duration, the ASA score, the incision grade, the healing grade, the operation position, the NNIS score, the emergency treatment, the operating room and the operation times, so that the accurate statistics and monitoring of the times of the patients suffering from the incision operation of the class I of the hands are realized. In addition, the invention screens the record information related to the antibacterial drugs, so that the antibacterial drug grade and the administration mode can be set for the antibacterial drugs.

The hospital data has corresponding privacy, so that the user is required to acquire corresponding data authority for the statistics and management of the hospital data in the invention. The data authority of the user is associated with the corresponding identity information, so that the invention determines the authority department of the user according to the identity information of the operating user, and performs statistics and monitoring on the number of cases of the type I incision operation patient on the data in the authority department.

the present invention screens the operation information G (a) _y according to statistics time, operation department, incision level, operation classification, operation doctor, anaesthesia mode, operation duration, ASA score, operation name, healing level, operation position, NNIS score, emergency treatment in the first stage, operation room, operation times, and authority department, in an embodiment, referring to fig. 2, step S6 may include steps S61 to S616.

S61, according to the operation information G (a) _Y and the statistical time, filtering to obtain operation information G (b) _Y in the statistical time range, and filtering operation information G (b) _N not in the statistical time range;

the invention firstly screens the operation information G (a) _Y occurring in the hospitalization period based on the statistical time, specifically, the invention acquires an operation starting time field in the operation information G (a) _Y occurring in the hospitalization period, judges whether the operation starting time in the operation record occurring in the hospitalization period belongs to the range of the statistical time period or not, if yes, adds the operation record into the operation information G (b) _Y in the statistical time period, otherwise, adds the operation record into the operation information G (b) _N not in the statistical time range.

For G (a) _Y above, the statistical time is [ 2019-01-06:00:00, 2019-01-20:23:59:59 ], then G (b) _Y is:

g (b) _N is:

s62, according to the operation information G (b) Y and the authority department information, filtering to obtain operation information G (c) Y within the authority range, and filtering operation information G (c) N not within the authority range

Because the rights of each user are different, the invention screens the operation information G (b) _Y based on the rights department, so that the data operated by the user is suitable for the corresponding rights. The field of the "department of surgery" in the operation information is compared with the authority department, and whether the field of the "department of surgery" belongs to the range of the authority department is judged. The operation information G (c) _y is operation information in departments that are within the authority range managed by the user, and the operation information G (c) _n is operation information in departments that are not within the authority range managed by the user.

For example, for G (b) _y described above, when the right department is all departments, G (c) _y is:

g (c) _N is:

s63, according to the operation information G (c) Y and the selected operation department, filtering to obtain operation information G (d) Y in the selected operation department range, and filtering operation information G (d) N not in the selected range

According to the invention, the times of the operation patients are monitored based on the specific operation department, and the user can manage the times of the operation patients aiming at the specific operation department, so that the operation information G (c) _Y is screened based on the selected operation department, the counted and screened data are adapted to the operation department selected by the user independently, the user can select the corresponding data according to the needs, and the times of the operation patients from the specific operation department are counted. The "surgery department" field in the surgery information is compared with the selected surgery department, and whether the "surgery department" field belongs to the selected surgery department range is judged.

For example, for all departments selected by the user, G (c) _y, G (d) _y is:

g (d) _N is:

The invention can manage the times of the patient cases of the operation aiming at the class I incision so as to determine the operation condition of the class I grade incision. Therefore, the invention screens the operation information G (d) _Y based on the class I grade incision, so that the counted and screened data are suitable for the class I grade incision selected by the user independently, the user can select the corresponding data according to the needs, and the times of the class I grade incision operation in patients are counted.

For example, for G (d) _Y, where the incision is a class I incision, G (e) _Y is:

g (e) _N is:

the surgical classification is a set of operations with rules, such as the classification of surgery as hernia surgery, which includes inguinal hernia repair, laparoscopic hernia repair, high ligation, etc. The user can manage the times of the surgical patient cases according to specific surgical classifications, so that the invention screens the surgical information G (e) _Y based on the selected surgical classifications, so that the counted and screened data are suitable for the surgical classifications selected by the user, the user can select corresponding data according to the needs, and the times of the surgical patient cases of the specific surgical classifications are counted.

For example, the user does not limit the classification of the surgery, and G (f) N is null for G (e) Y, where G (f) Y is the same as G (e) Y.

S66, according to the operation information G (f) _Y and the selected operation doctor, filtering to obtain operation information G (G) _Y in the range of the selected operation doctor, and filtering operation information G (G) _N not in the range of the selected operation doctor;

the invention can manage the times of the operation patient cases aiming at specific surgeons so as to determine the occurrence of the infection of the operation part executed by the appointed doctor. Therefore, the invention screens the operation information G (f) _Y based on the selected operation doctor, so that the statistical and screened data are suitable for the operation doctor selected by the user independently, the user can select the corresponding data according to the needs, and the number of times of the patient cases of the operation of the specific operation doctor is counted.

For example, the user does not limit the surgeon, and for G (f) _y, G (G) _y is the same as G (f) _y, G (G) _n is empty.

the invention can manage the times of the operation patient according to the specific anesthesia mode so as to determine the infection occurrence condition of the operation part with the designated anesthesia mode. Therefore, the invention screens the operation information G (G) _Y based on the selected anesthesia mode, so that the statistical and screened data are suitable for the anesthesia mode selected by the user independently, the user can select the corresponding data according to the needs, and the number of times of the patient operated in the specific anesthesia mode is counted.

For example, the user does not limit the anesthesia mode, and G (h) _n is empty for G (G) _y, which is the same as G (G) _y.

the user can manage the times of the surgical patient cases according to specific surgical time so as to determine the surgical conditions of different surgical time. Therefore, the invention screens the operation information G (h) _Y based on the selected operation time length, so that the counted and screened data are suitable for the operation time length selected by the user independently, the user can select the corresponding data according to the needs, and the times of the patient operated under the specific operation time length are counted.

For example, the user does not limit the operation duration, and G (i) _n is null for G (h) _y described above, where G (i) _y is the same as G (h) _y.

ASA scoring is a system of classification by American Society of Anesthesiologists (ASA) based on patient physical condition and surgical risk. ASA classification is based on the physical condition of the patient and rules for classifying surgical risks, with higher ASA mortality being higher. The user can manage the times of the operation patient according to the specific ASA scores so as to determine the operation conditions of different ASA scores. Therefore, the invention screens the operation information G (i) _Y based on the selected ASA score, so that the data counted and screened are suitable for ASA scores selected by the user independently, the user can select the corresponding data according to the needs, and the times of the patient cases of the operation corresponding to the ASA score are counted.

For example, the user does not limit the ASA score, and G (j) _N is null for G (i) _Y described above, where G (j) _Y is the same as G (i) _Y.

in actual monitoring, the user needs to monitor the frequency information of surgical patients with different surgical names, and the step is used for adapting. The user can manage the times of the surgical patient cases according to the specific surgical names, so that the invention screens the surgical information G (j) _Y based on the selected surgical names, so that the counted and screened data are suitable for the surgical names selected by the user independently, the user can select the corresponding data according to the needs, and the times of the surgical patient cases with the specific surgical names are counted. The "operation name" field in the operation information is compared with the selected operation name, and whether the "operation name" field is within the selected operation name range is judged.

For example, the user does not limit the operation name, and G (k) _n is null for G (j) _y, G (k) _y being the same as G (j) _y.

the user can manage the times of the surgical patient cases according to specific healing grades so as to determine the surgical conditions of different healing grades. Therefore, the invention screens the operation information G (k) _Y based on the selected healing grade, so that the counted and screened data are suitable for the healing grade selected by the user independently, the user can select the corresponding data according to the needs, and the times of the patient in the operation with the specific healing grade are counted.

For example, the user does not limit the healing level, and for G (k) _Y described above, G (m) _Y is the same as G (k) _Y, and G (m) _N is null.

the user can manage the times of the surgical patient cases according to the specific surgical position so as to determine the surgical conditions of different surgical positions. The surgical site is divided into superficial incisions, deep incisions and organ cavities. Therefore, the invention screens the operation information G (m) _Y based on the selected operation position, so that the counted and screened data are suitable for the operation position selected by the user independently, the user can select the corresponding data according to the requirement, and the times of the patient in the operation of the specific operation position are counted.

For example, the user does not limit the surgical site, and G (N) _n is null for G (m) _y, which is the same as G (m) _y.

the general "operation risk classification" method of the international medical quality index system is to divide operations into four stages, namely, NNIS0 stage, NNIS1 stage, NNIS2 stage and NNIS3 stage, according to the "operation risk classification standard (NNIS)" in the american "hospital infection monitoring manual". The invention can manage the times of the operation patient cases aiming at different NNIS scores so as to determine the operation conditions of different NNIS scores. Therefore, the invention screens the operation information G (n) _Y based on the selected NNIS score, so that the statistical and screened data are suitable for the NNIS score selected by the user independently, the user can select the corresponding data according to the need, and the times of the patient in the specific NNIS scoring operation are counted.

For example, the user does not limit the NNIS score, and G (p) _n is null for G (N) _y, which is the same as G (N) _y.

The invention can manage the times of the operation patient according to different operation types (the selected emergency), so as to determine the operation condition of the selected emergency. Therefore, the invention screens the operation information G (p) _Y based on the selected period-selecting emergency, so that the statistics and screening data are suitable for the period-selecting emergency selected by the user, the user can select the corresponding data according to the needs, and the statistics is carried out on the patient number of the specific period-selecting emergency operation.

For example, the user does not limit the choice emergency, and G (q) _N is empty for G (p) _Y, which is the same as G (p) _Y.

the invention can manage the times of the operation patient cases aiming at the specific operating rooms so as to determine the operation conditions of different operating rooms. Therefore, the invention screens the operation information G (q) _Y based on the selected operating room, so that the statistical and screened data are suitable for the operating room selected by the user independently, the user can select the corresponding data according to the needs, and the number of times of the patient operating in the specific operating room is counted.

For example, the user does not restrict the operating room, and G (r) _n is empty for G (q) _y, which is the same as G (q) _y.

S616, according to the operation information G (r) _Y and the selected operation times, filtering to obtain operation information G (S) _Y in the selected operation times range, and filtering to obtain operation information G (S) _N not in the selected range;

the invention can manage the times of the operation patient according to the specific times of the operation so as to determine the operation conditions of different times of the operation. Therefore, the invention screens the operation information G (r) _Y based on the selected operation times, so that the counted and screened data are adapted to the operation times selected by the user independently, the user can select the corresponding data according to the needs, and the times of the patient in the operation with the specific operation times are counted.

For example, the number of operations is not limited by the user, and G(s) _n is empty for G (r) _y, which is the same as G (r) _y.

And S7, judging whether an operation record exists in the operation information G (S) _Y, if so, executing the step S8, and if not, outputting the operation case frequency of preventive application of the antibacterial medicine in the I-type incision operation as 0.

Specifically, the invention judges according to the operation information G(s) _Y, if the patient still has records after the steps, the operation is continued downwards, if the patient does not have records, the operation is ended, and the result 0 is output.

For example, for the above G (S) _y, two records are included, and thus step S8 is continued.

the antibacterial record F is used for recording doctor's advice information of each patient, and specifically comprises patient's medical records, advice departments, antibacterial names, start time, end time, antibacterial grades, administration mode, administration purpose, advice doctors and advice doctor grades. The patient using the antibacterial drug in the normal observation period has the antibacterial drug doctor order record start time and end time which are in the hospitalization time range of the patient, so the invention screens obviously wrong data according to the parameter g.MC2. Specifically, the invention filters out the antibacterial medicine records F (a) _N which are not in the period of patient hospitalization based on the comparison of the fields of the 'start time', 'end time' in the antibacterial medicine doctor advice record and the parameter of the time of admission and discharge g.MC2, and obtains one antibacterial medicine record F (a) _Y which is used by the 'start time', 'end time' in the period of patient hospitalization.

For example, antibacterial record F is:

patient case number

Order-prescribed department

Antibacterial drug designation

Start time

End time

Administration mode

The purpose of medication

123456(1)

Neurology department

Cefuroxime

2019-01-03 08:00:00

2019-01-07 08:30:00

Oral administration

Prevention of

123456(1)

Neurology department

Cefuroxime

2019-01-02 08:00:00

2019-01-02 08:30:00

Pumping in

Treatment of

For g.mc2, F (a) _y above is:

patient case number

Order-prescribed department

Antibacterial drug designation

Start time

End time

Administration mode

The purpose of medication

123456(1)

Neurology department

Cefuroxime

2019-01-03 08:00:00

2019-01-07 08:30:00

Oral administration

Prevention of

123456(1)

Neurology department

Cefuroxime

2019-01-02 08:00:00

2019-01-02 08:30:00

Pumping in

Treatment of

F (a) _N is:

patient case number

Order-prescribed department

Antibacterial drug designation

Start time

End time

Administration mode

The purpose of medication

in an embodiment, referring to fig. 1, step S9 may include steps S91 to S93.

S91, dividing the antibacterial drug record F (a) _Y into an antibacterial drug order F (b) _Y for pre-preventive drug administration and an antibacterial drug order F (b) _N for non-preventive drug administration based on whether the drug purpose is preventive or not;

The monitoring of this index is not required for the recording of antimicrobial drugs that are administered for non-prophylactic purposes. Thus, the present invention screens an antimicrobial record F (a) _Y based on the "purpose of administration" field in the antimicrobial record. When the "purpose of medication" field is "prevention", then it belongs to the antibacterial record F (b) _y, otherwise it belongs to the antibacterial record F (b) _n.

For F (a) _Y, F (b) _Y is:

patient case number

Order-prescribed department

Antibacterial drug designation

Start time

End time

Administration mode

The purpose of medication

123456(1)

Neurology department

Cefuroxime

2019-01-03 08:00:00

2019-01-06 08:30:00

Oral administration

Prevention of

F(b)_N：

Patient case number

Order-prescribed department

Antibacterial drug designation

Start time

End time

Administration mode

The purpose of medication

123456(1)

Neurology department

Cefuroxime

2019-01-02 08:00:00

2019-01-02 08:30:00

Pumping in

Treatment of

the present invention screens against the antimicrobial record F (b) _y based on the "mode of administration" field in the antimicrobial record. When the "mode of administration" field is consistent with the mode of administration selected by the user, it is the antibacterial drug record F (c) _Y, otherwise it is the antibacterial drug record F (c) _N.

For example, when the mode of administration of the antibacterial drug is selected for oral administration, the above-mentioned F (b) _y, F (c) _y is:

patient case number

Order-prescribed department

Antibacterial drug designation

Start time

End time

Administration mode

The purpose of medication

123456(1)

Neurology department

Cefuroxime

2019-01-03 08:00:00

2019-01-07 08:30:00

Oral administration

Prevention of

F(c)_N：

Patient case number

Order-prescribed department

Antibacterial drug designation

Start time

End time

Administration mode

The purpose of medication

123456(1)

Neurology department

Cefuroxime

2019-01-02 08:00:00

2019-01-02 08:30:00

Pumping in

Treatment of

S93, dividing the antibacterial drug record F (c) _Y into an antibacterial drug record F (d) _Y consistent with the antibacterial drug grade selected by the user and an antibacterial drug record F (d) _N not consistent with the antibacterial drug grade selected based on the antibacterial drug grade;

the present invention screens the antimicrobial record F (c) _y based on the "antimicrobial grade" field in the antimicrobial record. When the field of the antibacterial medicine grade is consistent with the antibacterial medicine grade selected by the user, the field belongs to the antibacterial medicine record F (d) _Y, and otherwise, the field belongs to the antibacterial medicine record F (d) _N.

For example, when no antimicrobial grade is selected, F (d) N is empty for F (c) Y, F (d) Y being the same as F (c) Y.

S10, judging whether antibacterial information exists in the antibacterial record F (d) _Y, if so, executing the step S11, and if not, outputting the operation case number of preventive application of the antibacterial in the class I incision operation as 0.

Specifically, the invention judges according to the antibacterial drug record F (d) _Y, if the patient still has records after the steps, the process continues downwards, if the patient does not have records, the operation is ended, and the result 0 is output.

For example, for the above-described F (d) _y, one record is included, and thus step S11 is continued.

the present invention determines the parameter g.thw of the list of start-stop time periods of the order based on the antimicrobial record F (d) _y. The parameter g.thw is a parameter list consisting of order start time, order end time. Specifically, the start time and end time fields in the antimicrobial record F (d) _y are acquired, and a corresponding parameter g.thw is generated for each order [ start time and end time ].

For F (d) _Y above, g.THW is [ 2019-01-03:08:00:00, 2019-01-07:08:30:00 ].

S12, dividing the operation information G (S) _Y into operation information G (t) _Y for using the antibacterial drugs in the perioperative period and operation information G (t) _N for not using the antibacterial drugs in the perioperative period based on the parameters g.THW and g.QA4. Open;

Specifically, the invention compares the parameter g.THW and the parameter g.QA4. Open, judges whether the parameter g.THW and the parameter g.QA4. Open are crossed, if so, the invention belongs to the operation information G (t) _Y of using the antibacterial medicament in the perioperative period, otherwise, the invention belongs to the operation information G (t) _N of not using the antibacterial medicament in the perioperative period, and thus, the operation records which are not intersected in the perioperative period and the doctor's advice start-stop period are filtered.

The surgical information G(s) _y, the parameter g.thw, and the parameter g.qa4. Open, G (t) _y are as follows:

g (t) _N is:

The obtained operation information G (t) _Y is the operation record of I type incision operation and preventive medicine use of inpatients. And outputting 0 if the record in the operation information G (t) _Y is empty, and outputting the corresponding operation example times of preventive application of the antibacterial medicine in the I-type incision operation if the record is not empty. When a specific surgical record needs to be output, G (t) _y is output.

Since the operation information G (t) _y includes one record, the number of cases of preventive application of the antibacterial agent in the class I incision operation is 1.

Fig. 2 is a schematic block diagram of a statistical device for the number of cases of an antibacterial drug application based on MapReduce and big data according to an embodiment of the present invention. As shown in fig. 2, the present invention also provides a device for counting the number of cases of using antibacterial drugs based on MapReduce and big data, corresponding to the above method for counting the number of cases of using antibacterial drugs. The apparatus for counting the number of cases of the application of the antibacterial agent includes a unit for performing the above-described counting method of the number of cases of the application of the antibacterial agent, and may be configured in a server. Specifically, referring to fig. 2, the statistics device for the number of cases of the operation using the antibacterial drug includes a first collecting unit, a first dividing unit for the operation information, a first judging unit, a second collecting unit, a third collecting unit, a dividing unit for the operation information, a second judging unit, a first dividing unit for the antibacterial drug record, a third judging unit, a fourth collecting unit, a fifth dividing unit for the antibacterial drug record, and an output unit.

A first acquisition unit for acquiring hospitalization process information a of a patient, acquiring a time of admission and a time of discharge of the patient based on the hospitalization process information, and jointly serving as a parameter g.mc2; a first dividing unit for acquiring operation information G of a patient, and acquiring operation information G (a) _y occurring during a current hospitalization period and operation information G (a) _n occurring during a non-current hospitalization period in the operation information G based on the parameter g.mc2; a first judging unit, configured to judge whether an operation record exists in the operation information G (a) _y, if yes, call the second collecting unit, and if not, output the number of cases of preventive application of the antibacterial agent in the class I incision operation as 0; a second acquisition unit that acquires operation start time and operation end time based on the operation information G (a) _y, and uses the operation start time and the operation end time as perioperative parameters g.qa4.open of the operation; the third acquisition unit is used for receiving the statistical time, the operation department, the incision grade, the operation classification, the operation doctor, the anesthesia mode, the operation duration, the ASA score, the operation name, the healing grade, the operation position, the NNIS score, the emergency treatment in the selected period, the operation room, the operation times, the antibacterial medicine grade and the administration mode selected by the user, and determining the authority department of the user according to the identity information of the user; the operation information dividing unit is used for acquiring operation information G(s) _Y meeting the statistics time, the operation department, the incision grade, the operation classification, the operation doctor, the anesthesia mode, the operation duration, the ASA score, the operation name, the healing grade, the operation position, the NNIS score, the selected emergency, the operation room, the operation times and the permission department limit based on the operation information G (a) _Y; the second judging unit is used for judging whether the operation record exists in the operation information G(s) _Y, if so, calling the first dividing unit for the antibacterial medicine record, and if not, outputting the operation case frequency of preventive application of the antibacterial medicine in the I-type incision operation as 0; an antibacterial drug record first dividing unit for acquiring an antibacterial drug record F, dividing the antibacterial drug order record F into an antibacterial drug record F (a) _y used during patient hospitalization and an antibacterial drug record F (a) _n not used during patient hospitalization based on the parameter g.mc2; an antibacterial drug record dividing unit, configured to obtain an antibacterial drug record F (d) _y in the antibacterial drug record F (a) _y, where the purpose of drug administration is pre-defense, the antibacterial drug grade is satisfied, and the drug administration mode is limited; a third judging unit, configured to judge whether antibacterial information exists in the antibacterial record F (d) _y, if yes, call the fourth collecting unit, and if no, output the number of cases of preventive application of the antibacterial in the class I incision operation as 0; the fourth acquisition unit is used for acquiring the start time and the end time of the medical advice based on the antibacterial drug record F (d) _Y and jointly taking the start time and the end time of the medical advice as parameters g.THW of a start-stop time period list of the medical advice; an antibacterial drug record fifth dividing unit for dividing the operation information G(s) _y into operation information G (t) _y for using antibacterial drugs in the perioperative period and operation information G (t) _n for not using antibacterial drugs in the perioperative period based on the parameter g.thw and the parameter g.qa4. Open; and an output unit for outputting the number of cases of preventive application of the antibacterial agent in the class I incision operation based on the number recorded in the operation information G (t) _Y.

In an embodiment, the surgical information dividing unit includes a surgical information second dividing unit to a surgical information seventeenth dividing unit.

In an embodiment, the antibacterial drug record dividing unit includes an antibacterial drug record second dividing unit, an antibacterial drug record third dividing unit, and an antibacterial drug record fourth dividing unit.

an antibacterial drug record fourth dividing unit for dividing the antibacterial drug record F (c) _y into an antibacterial drug record F (d) _y conforming to the antibacterial drug grade selected by the user and an antibacterial drug record F (d) _n not conforming to the antibacterial drug grade selected based on the antibacterial drug grade.

It should be noted that, as those skilled in the art can clearly understand the statistics device of the number of times of the operation cases of applying the antibacterial agent and the specific implementation process of each unit, reference may be made to the corresponding description in the foregoing method embodiment, and for convenience and brevity of description, the description is omitted herein.

The above-described statistics of the number of instances of the application of the antimicrobial drug may be implemented in the form of a computer program that is executable on a computer device.

The computer device may be a server, where the server may be a stand-alone server, or may be a server cluster formed by a plurality of servers.

The computer device includes a processor, memory, and a network interface connected by a system bus, where the memory may include a non-volatile storage medium and an internal memory.

The non-volatile storage medium may store an operating system and a computer program. The computer program comprises program instructions which, when executed, cause the processor to perform a method of counting the number of instances of an antimicrobial drug application.

The processor is used to provide computing and control capabilities to support the operation of the entire computer device.

The internal memory provides an environment for the execution of a computer program in a non-volatile storage medium that, when executed by a processor, causes the processor to perform a statistics of the number of instances of an antimicrobial drug application.

The network interface is for network communication with other devices. It will be appreciated by persons skilled in the art that the computer device structures described above are merely partial structures relevant to the present inventive arrangements and do not constitute a limitation of the computer device to which the present inventive arrangements are applied, and that a particular computer device may include more or less components than those shown in the drawings, or may combine certain components, or have a different arrangement of components.

Wherein the processor is configured to run a computer program stored in a memory, the program implementing a method for counting the number of cases of an antimicrobial drug application as described in embodiment one.

It should be appreciated that in embodiments of the application, the processor may be a central processing unit (Central Processing Unit, CPU), which may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSPs), application specific integrated circuits (Application Specific Integrated Circuit, ASICs), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. Wherein the general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

Those of ordinary skill in the art will appreciate that implementing all or part of the methodologies of the above embodiments may be accomplished by computer programs to instruct related hardware. The computer program comprises program instructions, and the computer program can be stored in a storage medium, which is a computer readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the flow steps of the embodiments of the method described above.

The invention also provides a storage medium. The storage medium may be a computer readable storage medium. The storage medium stores a computer program, wherein the computer program when executed by a processor causes the processor to perform a statistical method for the number of cases of an antimicrobial drug application as described in embodiment one.

The storage medium may be a U-disk, a removable hard disk, a Read-Only Memory (ROM), a magnetic disk, or an optical disk, or other various computer-readable storage media that can store program codes.

Those of ordinary skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein may be embodied in electronic hardware, in computer software, or in a combination of the two, and that the elements and steps of the examples have been generally described in terms of function in the foregoing description to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the device embodiments described above are merely illustrative. For example, the division of each unit is only one logic function division, and there may be another division manner in actual implementation. For example, multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed.

The steps in the method of the embodiment of the invention can be sequentially adjusted, combined and deleted according to actual needs. The units in the device of the embodiment of the invention can be combined, divided and deleted according to actual needs. In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.

The integrated unit may be stored in a storage medium if implemented in the form of a software functional unit and sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention may be substantial or a part contributing to the prior art, or all or a part of the technical solution may be embodied in the form of a software product, which is stored in a storage medium, and includes several instructions for causing a computer device (which may be a personal computer, a terminal, or a network device, etc.) to perform all or a part of the steps of the method according to the embodiments of the present invention.

Note that the above is only a preferred embodiment of the present invention and the technical principle applied. Those skilled in the art will appreciate that the invention is not limited to the specific embodiments described herein, and that various obvious changes, rearrangements and substitutions can be made by those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.

Claims

1. The statistical method for the number of the operation cases of applying the antibacterial drug based on MapReduce and big data is characterized by comprising the following steps:

s5, collecting statistics time, operation departments, incision grades, operation classifications, operation doctors, anesthesia modes, operation duration, ASA scores, operation names, healing grades, operation positions, NNIS scores, emergency treatment in a selected period, operation rooms, operation times, antibacterial medicament grades and administration modes selected by users, and determining authority departments of the users according to identity information of the users;

s6, based on the operation information G (a) _Y, acquiring operation information G (S) _Y meeting the statistics time, the operation department, the incision grade, the operation classification, the operation doctor, the anesthesia mode, the operation duration, the ASA score, the operation name, the healing grade, the operation position, the NNIS score, the emergency treatment in the selected period, the operation room, the operation times and the limit of the authority department;

s8, acquiring an antibacterial medicine record F, and dividing the antibacterial medicine doctor order record F into an antibacterial medicine record F (a) _Y used during patient hospitalization and an antibacterial medicine record F (a) _N not used during patient hospitalization based on the parameter g.MC2;

s10, judging whether antibacterial information exists in the antibacterial record F (d) _Y, if so, executing the step S11, and if not, outputting the operation case frequency of preventive application of the antibacterial in the class I incision operation as 0;

2. The statistical method of claim 1, wherein the hospital procedure information comprises patient case number, admission department, admission time, discharge department, discharge time; the operation information comprises patient case numbers, operation departments, operation categories, operation doctors, anesthesia modes, operation names, operation starting time, operation ending time, incisions, healing grades, ASA, emergency treatment in a selected period, operation positions, NNIS scores, operation rooms and operation times; the antibacterial record comprises a patient case number, an ordered department, an antibacterial name, a start time, an end time, an antibacterial grade, a drug administration mode, a drug purpose, an ordered doctor and an ordered doctor grade.

3. The statistical method according to claim 2, wherein the step S6 comprises:

4. The statistical method according to claim 2, wherein the step S9 comprises:

s91, dividing the antibacterial drug record F (a) _Y into an antibacterial drug order F (b) _Y for preventive administration and an antibacterial drug order F (b) _N for non-preventive administration based on whether the purpose of administration is preventive or not;

5. The utility model provides a statistics device of the number of times of using antibacterial medicine's operation case based on MapReduce and big data which characterized in that includes:

a first dividing unit for acquiring operation information G of a patient, and acquiring operation information G (a) _y occurring during the present hospitalization period and operation information G (a) _n occurring during the non-present hospitalization period in the operation information G based on the parameter g.mc2;

6. The statistical device of claim 5, wherein the hospital course information comprises patient case number, admission department, admission time, discharge department, discharge time; the operation information comprises patient case numbers, operation departments, operation categories, operation doctors, anesthesia modes, operation names, operation starting time, operation ending time, incisions, healing grades, ASA, emergency treatment in a selected period, operation positions, NNIS scores, operation rooms and operation times; the antibacterial record comprises a patient case number, an ordered department, an antibacterial name, a start time, an end time, an antibacterial grade, a drug administration mode, a drug purpose, an ordered doctor and an ordered doctor grade.

7. The statistical device according to claim 6, wherein the operation information dividing unit comprises:

the third division unit of the operation information is used for filtering operation information G (c) Y within the authority range according to the operation information G (b) Y and the authority department information, and filtering operation information G (c) N not within the authority range;

a fifth division unit of operation information, which is used for filtering operation information G (e) _Y with the incision grade of I class selected by the user according to the operation information G (d) _Y, and filtering operation information G (e) _N which is not in the selection range;

a ninth division unit of operation information, configured to filter operation information G (i) _y within a selected operation duration range according to operation information G (h) _y and selected operation duration information, and filter operation information G (i) _n not within the selected range;

A seventeenth dividing unit for filtering out the surgical information G(s) N not in the selected range according to the surgical information G (r) Y and the selected surgical times to obtain the surgical information G(s) Y in the selected surgical times range.

8. The statistical device of claim 6, wherein the antimicrobial record partitioning unit comprises:

9. A computer device, characterized in that the device comprises a memory and a processor, the memory having stored thereon a computer program, which processor, when executing the computer program, implements the method according to any of claims 1-4.

10. A storage medium storing a computer program which, when executed by a processor, performs the method of any one of claims 1 to 4.