CN116978514A

CN116978514A - Nutritional therapy assistance decision pushing method, device, computer equipment and medium

Info

Publication number: CN116978514A
Application number: CN202310987129.5A
Authority: CN
Inventors: 徐一涵; 范春; 周炜; 王涛; 孙嘉明; 徐安琪; 杨吴婕; 马洁; 金灿; 何慧敏
Original assignee: Winning Health Technology Group Co Ltd
Current assignee: Winning Health Technology Group Co Ltd
Priority date: 2023-08-07
Filing date: 2023-08-07
Publication date: 2023-10-31

Abstract

The application provides a nutrition therapy auxiliary decision pushing method, a nutrition therapy auxiliary decision pushing device, computer equipment and a nutrition therapy auxiliary decision pushing medium, and belongs to the technical field of medical informatization. The method comprises the following steps: determining the nutrition evaluation result and the crowd subdivision result of the patient to be admitted according to the basic information, the nutrition evaluation information and the crowd subdivision information of the patient to be admitted; generating label information of the patient to be admitted according to the nutrition evaluation result and the crowd subdivision result of the patient to be admitted; determining whether the patient to be admitted needs nutritional treatment or not according to the label information of the patient to be admitted and a medical outcome database constructed in advance; if yes, pushing the nutrition treatment scheme, the nutrition treatment period, the review time and the prediction of the earliest recovery time of the patient to be admitted according to the label information and the medical outcome database of the patient to be admitted. The application can achieve the effect of pushing the nutrition therapy auxiliary decision based on the nutrition evaluation result of the patient.

Description

Nutritional therapy assistance decision pushing method, device, computer equipment and medium

Technical Field

The application relates to the technical field of medical informatization, in particular to a nutrition treatment auxiliary decision pushing method, a nutrition treatment auxiliary decision pushing device, computer equipment and a medium.

Background

At present, according to the research on the relation between the nutrition risk and the disease rehabilitation, the nutrition risk can directly influence the disease rehabilitation effect, and the risks of adverse clinical reactions are increased, such as prolonged hospitalization time, reduced physiological skills, increased infection risk, slow wound healing and the like. In addition, the incidence of malnutrition in hospitalized patients is 20% -50%, and 1/3 of patients die because of malnutrition. Nutritional therapy can reduce the number and severity of complications and improve clinical treatment.

Therefore, how to screen and evaluate the nutritional risk of patients and push effective nutritional therapy assistance solutions to doctors based on the nutritional evaluation results and poor clinical outcome risk is a problem to be solved.

Disclosure of Invention

The application aims to provide a nutrition therapy auxiliary decision pushing method, a nutrition therapy auxiliary decision pushing device, computer equipment and a medium, which can achieve the effect of realizing nutrition therapy auxiliary decision pushing based on nutrition evaluation results of patients.

Embodiments of the present application are implemented as follows:

in a first aspect of the embodiment of the present application, a method for pushing an auxiliary decision for nutrition therapy is provided, including:

determining the nutrition evaluation result and the crowd subdivision result of the patient to be admitted according to the basic information, the nutrition evaluation information and the crowd subdivision information of the patient to be admitted;

Generating label information of the patient to be admitted according to the nutrition evaluation result and the crowd subdivision result of the patient to be admitted;

determining whether the patient to be admitted needs nutritional treatment according to the label information of the patient to be admitted and a medical outcome database constructed in advance, wherein the medical outcome database is used for recording basic information, medical expense, crowd subdivision information, negative medical result information, admission route, nutritional assessment result information and nutritional assessment tools of the patient to be admitted;

if yes, pushing the nutrition treatment scheme, the nutrition treatment period, the review time and the prediction of the earliest recovery time of the patient to be admitted according to the label information and the medical outcome database of the patient to be admitted.

As one possible implementation manner, determining the nutrition evaluation result and the crowd subdivision result of the patient to be admitted according to the basic information, the nutrition evaluation information and the crowd subdivision information of the patient to be admitted includes:

determining a target nutrition evaluation tool according to the basic information and the nutrition evaluation information of the patient to be admitted;

determining a nutritional assessment result for the patient to be admitted based on the target nutritional assessment tool;

and determining crowd subdivision results according to the basic information and crowd subdivision information of the patients to be admitted.

As one possible implementation manner, generating label information of the patient to be admitted according to the nutrition evaluation result and the crowd subdivision result of the patient to be admitted includes:

and taking the combination of the nutrition evaluation result of the patient to be admitted, the nutrition evaluation tool corresponding to the nutrition evaluation result and the crowd subdivision result as the label information of the patient to be admitted.

As one possible implementation, determining whether the patient to be admitted needs nutritional therapy according to the label information of the patient to be admitted and the medical outcome database constructed in advance includes:

determining first patient quantity information which is matched with the patient to be admitted and has no nutrition treatment and negative medical results in a medical outcome database according to label information of the patient to be admitted and the medical outcome database;

determining second patient quantity information of nutrition treatment in patients matched with the patients to be admitted in the medical outcome database and predicting nutrition treatment period according to the label information of the patients to be admitted and the medical outcome database;

and determining whether the patient to be admitted needs nutritional treatment according to the first patient quantity information and the second patient quantity information.

As one possible implementation, determining whether the patient to be admitted needs nutritional therapy according to the first patient number information and the second patient number information includes:

determining whether the patient to be admitted needs nutritional treatment according to the first patient quantity information;

if so, determining the nutrition treatment period of the patient to be admitted according to the second patient quantity information and the predicted nutrition treatment period.

As one possible implementation manner, determining and pushing a nutrition treatment scheme, a nutrition treatment period and a review time of the patient to be admitted according to the label information of the patient to be admitted and the medical outcome database, including:

determining the actual nutrition treatment period of the patient matched with the patient to be admitted in the medical outcome database according to the label information of the patient to be admitted and the medical outcome database;

pushing the nutrition treatment period, the re-diagnosis time and the predicted earliest recovery time of the patient to be admitted according to the actual nutrition treatment period;

determining an actual nutrition treatment scheme of a patient matched with the patient to be admitted in the medical outcome database according to the label information of the patient to be admitted and the medical outcome database;

the nutritional therapy regimen to be admitted to the patient is pushed according to the actual nutritional therapy regimen.

As a possible implementation manner, the nutrition therapy auxiliary decision pushing method further includes:

basic information, nutrition evaluation result information, negative medical result information, medical expense information and crowd subdivision information of discharged patients and admission routes are acquired;

the basic information, negative medical outcome information, medical cost information, and crowd subdivision information, admission routes, nutritional assessment outcome information for the discharged patient, and the ready-to-use nutritional assessment tool are recorded into a medical outcome database.

In a second aspect of the embodiments of the present application, there is provided a nutrition therapy assistance decision making push device, comprising:

the first determining module is used for determining nutrition evaluation results and crowd subdivision results of the patients to be admitted according to the basic information, the nutrition evaluation information and the crowd subdivision information of the patients to be admitted;

the generating module is used for generating label information of the patient to be admitted according to the nutrition evaluation result and the crowd subdivision result of the patient to be admitted;

the second determining module is used for determining whether the patient to be admitted needs nutrition treatment according to the label information of the patient to be admitted and a medical outcome database which is constructed in advance, wherein the medical outcome database is used for recording basic information, medical expense, crowd subdivision information, negative medical result information, admission route, nutrition evaluation result information and nutrition evaluation tools of the patient to be admitted;

And the pushing module is used for pushing the nutrition treatment scheme, the nutrition treatment period, the review time and the prediction of the earliest recovery time of the patient to be admitted according to the label information of the patient to be admitted and the medical outcome database if the patient to be admitted is in the patient to be admitted.

In a third aspect of embodiments of the present application, there is provided a computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the computer program implementing the nutrition therapy assistance decision pushing method according to the first aspect, when executed by the processor.

In a fourth aspect of the embodiments of the present application, a computer readable storage medium is provided, where a computer program is stored, where the computer program is executed by a processor to implement the nutrition therapy assistance decision pushing method according to the first aspect.

The beneficial effects of the embodiment of the application include:

according to the nutritional therapy auxiliary decision pushing method provided by the embodiment of the application, basic information, nutritional evaluation information and crowd subdivision information of a patient to be admitted are acquired, nutritional evaluation is carried out on the patient to be admitted according to the basic information and the nutritional evaluation information of the patient to be admitted, the nutritional evaluation result of the patient to be admitted is determined, the crowd subdivision result of the patient to be admitted is determined according to the basic information and the crowd subdivision information of the patient to be admitted, then label information of the patient to be admitted is generated according to the nutritional evaluation result of the patient to be admitted and the crowd subdivision result, whether the patient to be admitted needs nutritional therapy is determined according to the label information of the patient to be admitted and a medical outcome database which is constructed in advance, and if the patient to be admitted needs nutritional therapy, a nutritional therapy scheme to be pushed is pushed to a main doctor of the patient for reference according to the label information of the patient to be admitted. The label information of the patient to be admitted is combined with the medical outcome database, and clinical treatment data of the discharged patient which is most matched with the patient to be admitted is searched in the medical database, so that a nutrition treatment scheme of the patient to be admitted is determined, and thus, the clinical treatment result can be effectively predicted, and the medical risk can be avoided. Therefore, the effect of pushing the nutrition therapy auxiliary decision based on the nutrition evaluation result of the patient can be achieved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and other related 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 main system provided in an embodiment of the present application;

FIG. 2 is a system architecture diagram provided in an embodiment of the present application;

fig. 3 is a flowchart of a first nutritional therapy assistance decision push method according to an embodiment of the present application;

fig. 4 is a flowchart of a second nutrition therapy assistance decision push method according to an embodiment of the present application;

fig. 5 is a flowchart of a third nutritional therapy assistance decision push method according to an embodiment of the present application;

fig. 6 is a flowchart of a fourth nutritional therapy assistance decision push method according to an embodiment of the present application;

fig. 7 is a flowchart of a fifth nutrition therapy assistance decision push method according to an embodiment of the present application;

fig. 8 is a flowchart of a sixth nutrition therapy assistance decision push method according to an embodiment of the present application;

Fig. 9 is a schematic structural diagram of a nutritional therapy assistance decision making pushing device according to an embodiment of the present application;

fig. 10 is a schematic structural diagram of a computer device according to an embodiment of the present application.

The attached drawings are identified: 10: a medical system; 101: an acquisition module; 102: a storage module; 1021: a medical outcome database; 1022: a patient archive to be admitted; 1023: a rule base; 103: the monitoring, reminding and analyzing module; 901: a first determination module; 902: a generating module; 903: a second determination module; 904: a pushing module; 1001: a memory; 1002: a processor.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.

Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures.

At present, nutrition state evaluation and diagnosis are often performed by acquiring basic information of a patient to be admitted, and if the patient to be admitted is judged to be malnourished and nutrition treatment is required, relevant nutrition treatment schemes are searched in a medical knowledge base according to nutrition state evaluation results to push. However, this nutritional regimen is scientifically matched based on the ratio of human nutrients, which results in a consistent matching regimen when the patient is malnourished with the same missing nutrients. In addition, the delivery of these nutritional treatment regimens only takes into account the patient's nutritional status, and is not based on clinical data in terms of medical quality, etc., and cannot determine whether nutritional treatment is needed or not at risk for poor clinical outcome.

Therefore, the embodiment of the application provides a nutrition therapy auxiliary decision pushing method, which comprises the steps of obtaining basic information, nutrition evaluation information and crowd subdivision information of a patient to be admitted, determining nutrition evaluation results and crowd subdivision results of the patient to be admitted, generating label information of the patient to be admitted according to the nutrition evaluation results and crowd subdivision results of the patient to be admitted, determining whether the patient to be admitted needs nutrition therapy or not according to the label information of the patient to be admitted and a medical outcome database constructed in advance, and if the patient to be admitted needs nutrition therapy, matching a nutrition therapy scheme to be pushed from the medical outcome database according to the label information of the patient to be admitted, and pushing the nutrition therapy scheme to be pushed to an attending doctor of the patient for reference, so that the nutrition therapy auxiliary decision pushing effect based on the nutrition evaluation results of the patient can be achieved.

As a possible implementation manner, the embodiment of the invention provides a nutrition treatment auxiliary decision pushing method, a hospital receives a patient to be admitted, acquires basic information, nutrition evaluation information and crowd subdivision information of the patient to be admitted through a patient to be admitted treatment record, wherein the patient to be admitted treatment record comprises an identification card of the patient to be admitted and a record of appointment with a doctor's insurance card, the record also comprises a department to which the doctor to be admitted appointment and a doctor's inquiry record of the doctor to the patient, a medical system of the hospital establishes an electronic medical record based on the record of the patient to be admitted, automatically selects a proper nutrition evaluation tool for analysis based on the basic information and the nutrition evaluation information in the medical record of the patient to be admitted, acquires a nutrition evaluation result of the patient to be admitted, meanwhile, the medical system performs crowd subdivision based on crowd subdivision information and basic information of patients to be admitted, obtains crowd subdivision results of the patients to be admitted, generates label information of the patients to be admitted according to nutrition evaluation results of the patients to be admitted and the crowd subdivision results, interfaces a medical outcome database in the medical system according to the label information of the patients to be admitted, matches medical data information of the discharged patients with highest suitability with the label information of the patients to be admitted, screens nutritional treatment schemes of the discharged patients with minimum medical risks and optimal nutritional treatment effects from the matched medical data information of the discharged patients, and uses the nutritional treatment schemes as nutritional treatment schemes to be pushed for the patients to be admitted, and pushes the nutritional treatment schemes to be pushed to a main doctor of the patients to be admitted for reference.

Fig. 1 is a main system flow chart provided in the embodiment of the present application, referring to fig. 1, the system flow of the present application is mainly divided into two parts, and mainly includes: medical outcome database construction and patient to be admitted nutrition treatment protocol pushing, specifically as follows:

optionally, the construction of the medical outcome database includes receiving an electronic medical record of the discharged patient, acquiring basic information, negative medical result information, medical expense information, crowd subdivision information and the like of each discharged patient in the historical electronic medical record, storing the basic information, the negative medical result information, the medical expense information, crowd subdivision information and the like, and performing statistical analysis on medical data of the discharged patient according to preset indexes to acquire a final effect of the nutritional therapy on the medical clinical outcome.

Optionally, the system embeds analysis indexes, see table 1, which are divided into two indexes of negative medical result and medical resource consumption, and related indexes can be additionally set according to the needs to prove that the malnutrition treatment can effectively reduce the medical cost, improve the medical quality and shorten the hospitalization days. The index items may be combined, for example, the total cost of an out-patient nutrition order and the total cost of an in-patient treatment may be added, and the total cost of the out-patient treatment and the total cost of the in-patient treatment may be compared to the total cost of the direct in-patient treatment.

TABLE 1 analysis index term

Alternatively, the index statistics may be an average, a mode, a total number, etc. according to the characteristics of the index item, such as actual hospital days, the average may be used to analyze and compare the average hospital days of different nutritional outcome labels, such as postoperative diagnostic codes for surgical complications, and the mode may be used to analyze the most common postoperative complications for a patient label. Meanwhile, the ratio of indexes of different nutritional results in indexes corresponding to the label can be counted, for example, the number of times of using the breathing machine for the patient group of the label is 300 times, wherein the number of times of using the breathing machine for A1 (L) is 60 times, and the ratio is 20%.

Optionally, statistical analysis is performed on different classes of patients, according to patient labels: direct hospitalization/outpatient nutrition therapy-risk assessment tool-Ai (F) -Ai (L) -population segments, patients are grouped. Patient populations can be selected for comparative analysis according to small tags: direct hospitalization/outpatient nutrition therapy; a risk assessment tool; ai (F); ai (L); and (5) crowd subdivision. For example, comparing indices between different Ai (F) for the same risk assessment tool, crowd segments. Comparing indexes of the average values of all the Ai of different Ai (F) and the crowd subdivision group with the same risk assessment tool and crowd subdivision. Comparing the indexes of the malnutrition after treatment with the indexes of untreated indexes, namely indexes of the same risk assessment tool, crowd subdivision, the same Ai (F) and different Ai (L).

Optionally, the delivering of the patient to be admitted nutritional therapy regimen comprises: the medical system is connected with a doctor workstation, nutritional risk assessment is carried out by adopting a corresponding nutritional assessment tool according to the patient's visit data and the inquiry records, the nutritional treatment period, the medical outcome prediction and the like of the patient to be admitted are predicted according to the nutritional assessment results of the patient to be admitted in combination with the medical outcome database, the doctor is output with monitoring reminding of whether nutritional treatment is carried out, if treatment is needed, the nutritional treatment scheme of the discharged patient with the label information most matched is directly pushed, hospitalization can be directly handled without nutritional treatment, the patient needing nutritional treatment is transferred to clinic treatment, and the doctor makes corresponding nutritional treatment doctor advice and medical cost until the patient nutritional assessment results reach standards and are handled for hospitalization.

Table 2 is a nutrition order and medical cost table, as shown in Table 2, and the physician refers to the pushed nutrition treatment assistance decision to make a nutrition order and medical cost suitable for the patient as shown in the following table:

table 2 nutritional advice and medical costs Table

Fig. 2 is a schematic diagram of a system provided in an embodiment of the present application, referring to fig. 2, a medical system 10 of a nutrition therapy assistance decision push method includes an acquisition module 101, a storage module 102, and a monitoring reminding and analysis module 103, where the storage module 102 further includes a medical outcome database 1021, a patient to be admitted archive 1022, and a rule base 1023, and the acquisition module 101 is configured to acquire basic information, medical expense information, discharged patient population subdivision information, negative medical result information, admission route, nutrition evaluation information, patient population subdivision information to be admitted, nutrition evaluation tool information, and nutrition advice and medical expense information of a patient; the medical outcome database 1021 is used for recording basic information, medical expense information, discharged patient crowd subdivision information, negative medical result information, admission routes and patient nutrition evaluation and crowd subdivision results of patients; the patient to be admitted archive 1022 is used for recording basic information, admission route, nutrition evaluation information, crowd subdivision information, nutrition evaluation tool information, nutrition medical advice and medical cost information of patients, and nutrition evaluation and crowd subdivision results of patients; the rule base 1023 is used for recording nutrition evaluation rules corresponding to each nutrition evaluation tool and crowd subdivision rules; the monitoring reminding and analyzing module 103 is used for analyzing the patient label information and reminding the patient whether nutritional therapy and scientific research analysis are needed.

The nutrition therapy auxiliary decision pushing method provided by the embodiment of the application is explained in detail below.

Fig. 3 is a flowchart of a nutrition therapy assistance decision pushing method provided by the application, and the method can be applied to a medical system of a hospital. Referring to fig. 3, an embodiment of the present application provides a nutrition therapy assistance decision pushing method, including:

s301, determining nutrition evaluation results and crowd subdivision results of patients to be admitted according to basic information, nutrition evaluation information and crowd subdivision information of the patients to be admitted.

Optionally, the basic information of the patient to be admitted is obtained through the doctor-seeing record of the patient to be admitted to the hospital, and when the patient to be admitted swipes the identity card on the self-service server of the hospital and the doctor is reserved by the medical insurance card, the medical system of the hospital establishes an electronic file based on the identity card information and the medical insurance card information of the patient. The basic information of the patient to be admitted comprises the name, the identity card number, the identity card type, the medical insurance card number, the medical insurance type, the home address, the contact way, the physiological gender, the physiological age and the like of the patient.

Table 3 is a basic information table of a patient, as shown in table 3, and basic information of the patient acquired by the hospital medical system based on the identity card information and the medical insurance card information of the patient is shown in the following table:

Table 3 basic information table of patient

Optionally, the doctor receives the patient to be admitted, and the doctor makes a query on the patient to be admitted to obtain the specific condition of the current disease of the patient to be admitted, analyzes the current disease of the patient to be admitted, and makes a preliminary diagnosis, such as the type of medical operation to be performed for the current disease of the patient, the treatment means and the like.

Optionally, the doctor stores the consultation record of the patient in an electronic medical record corresponding to the patient to be admitted, and the medical system acquires nutrition evaluation information and crowd subdivision information of the patient to be admitted based on the basic information of the patient to be admitted and the inquiry record of the doctor, wherein the nutrition evaluation information comprises: age of patient, history of present, surgical and operational code, western diagnostic code, outpatient or emergency number, date and time of visit, department name of visit, and doctor of inquiry; crowd subdivision information includes: personal basic information of the patient, disease information, medical behavior information, and the like.

Table 4 is a table for collecting nutrition evaluation information of a patient, and as shown in table 4, the nutrition evaluation information of a patient obtained by a hospital medical system based on basic information of a patient and a doctor's inquiry record is shown in the following table:

Table 4 patient nutrition assessment information acquisition table

Table 5 is a crowd subdivision information table of patients to be admitted, as shown in table 5, and the crowd subdivision information of patients to be admitted, which is obtained by the hospital medical system based on the basic information of patients to be admitted and the doctor's inquiry record, is shown in the following table:

TABLE 5 crowd subdivision information table for patients to be admitted

Optionally, the nutrition evaluation information of the patient to be admitted is determined according to the basic information and the inquiry record of the patient to be admitted, the nutrition evaluation tool applicable to the patient to be admitted is determined according to the nutrition evaluation information of the patient to be admitted, and the nutrition evaluation result of the patient to be admitted is obtained by analyzing the nutrition evaluation information through the nutrition evaluation tool. The nutritional risk assessment results included: low nutritional risk (A1), moderate nutritional risk (A2), high nutritional risk (A3).

Optionally, crowd subdivision information of the patient to be admitted can be determined according to the basic information of the patient to be admitted and the inquiry records of doctors, crowd subdivision is performed on the patient to be admitted based on crowd subdivision rules, and crowd subdivision results of the patient to be admitted are determined.

S302, generating label information of the patient to be admitted according to the nutrition evaluation result and the crowd subdivision result of the patient to be admitted.

Optionally, generating the label information of the patient to be admitted according to the nutrition evaluation result and the crowd subdivision result of the patient to be admitted, where the label information of the patient to be admitted includes: admission route-nutrition assessment tool-first nutrition assessment result-last nutrition assessment result before hospitalization-crowd subdivision result.

It should be noted that the label information of the patient to be admitted may be sequentially supplemented during the visit, for example, the crowd subdivision result, the first nutrition evaluation result, the nutrition evaluation tool and the admission route in the label information of the patient to be admitted may be primarily determined according to the inquiry record of the patient to be admitted and the visit information. The patient with qualified nutrition evaluation result can directly handle admission, the first nutrition evaluation result of the patient is the last nutrition evaluation result before hospitalization of the patient, but the patient who needs treatment after the last nutrition treatment needs to handle admission treatment needs to do a nutrition evaluation again after the last nutrition treatment is finished as the last nutrition evaluation result before hospitalization.

Alternatively, multiple nutritional assessment tools may be used for each patient to be admitted, i.e., one patient to be admitted may have multiple tag information.

For example, assuming that the patient to be admitted a uses two nutrition evaluation tools a and b, the first nutrition evaluation result of the patient to be admitted is a1 and b1, the last nutrition evaluation result before the patient to be admitted is hospitalized is a2 and b2, the crowd subdivision result of the patient to be admitted is m, the tag information of the patient to be admitted a is: outpatient nutrition therapy-a-a 1-a2-m, outpatient nutrition therapy-b-b 1-b 2-m.

S303, determining whether the patient to be admitted needs nutritional therapy according to the label information of the patient to be admitted and a medical outcome database which is constructed in advance, wherein the medical outcome database is used for recording basic information, medical expense, crowd subdivision information, negative medical result information, admission route, nutritional assessment result information and nutritional assessment tools of the patient to be admitted.

Optionally, the pre-constructed medical end database is configured to store medical data information of discharged patients, wherein the medical data information of discharged patients includes: basic information of patients, medical costs, crowd subdivision information, negative medical outcome information, admission routes, nutritional assessment outcome information, and nutritional assessment tools.

Alternatively, the medical cost information of the discharged patient may be obtained based on an electronic medical record of the patient in the medical system, and the medical cost includes: total cost of hospitalization, self-payment, medical service cost, treatment operation cost, nursing cost, diagnosis cost and the like.

Table 6 is a total table of medical costs for discharged patients, as shown in Table 6, the medical costs for discharged patients obtained by the hospital medical system based on the electronic medical records of discharged patients are shown in the following table:

Table 6 medical fee total for discharged patient

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Alternatively, the medical system may obtain complete discharged patient population segment information data from the discharged patient electronic case.

Table 7 is a table of crowd subdivision information for discharged patients, as shown in Table 7, and the crowd subdivision information for discharged patients obtained by the hospital medical system based on the electronic medical records of discharged patients is shown in the following table:

TABLE 7 crowd subdivision information form for discharged patients

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Optionally, the medical system obtains a negative medical result record list of the discharged patient such as operation complications, adverse drug reactions, medical accidents and the like from the discharged patient electronic medical record.

Table 8 is a table of negative medical outcome records for discharged patients, as shown in Table 8, the hospital medical system obtains the negative medical outcome records for discharged patients based on the electronic medical records for discharged patients as shown in the following table:

table 8 negative medical outcome records for discharged patients

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Optionally, the method includes the steps of obtaining an admission route of the discharged patient according to a historical electronic medical record of the discharged patient of the medical system, wherein the admission route comprises: direct hospitalization and outpatient nutrition treatment.

Table 9 is a table of the admission routes for discharged patients, as shown in Table 9, the hospital medical system acquires the admission routes for discharged patients based on the electronic medical records of discharged patients as shown in the following table:

Table 9 route of admission for discharged patients

Data source	Data name	Description of data
			Electronic medical record system	Patient admission route	Directly hospitalizing; nutritional therapy for outpatient service

Optionally, the pre-constructed medical outcome database is used for counting and storing basic information, medical expense, crowd subdivision information, negative medical result information, admission routes, nutrition evaluation result information and nutrition evaluation tools of discharged patients according to certain preset indexes from the electronic medical records of the discharged patients.

It is noted that the preset index is preset in the medical system, and the medical system distinguishes and counts various medical data of the discharged patient based on the preset index.

Optionally, the medical data of the discharged patient matched with the label information of the patient is matched in a pre-constructed medical outcome database according to the label information of the patient to be admitted, and the negative medical results corresponding to the labels of the discharged patient are determined based on the matched medical data of the discharged patient, so that whether the patient to be admitted needs out-patient nutritional treatment or not is determined.

By way of example, assume that there are 300 discharged patients in the pre-constructed medical outcome database that match the label a-a1-m of patient to be admitted A, with 100 patients with label 1 hospitalized directly-a-a 1-m, 100 patients with label 2 outpatient-a-a 1-a2-m, and 100 patients with label 3 outpatient-a-a 1-a 3-m. Wherein 80 negative medical outcomes of the discharged patients corresponding to the label 1, 30 negative medical outcomes of the discharged patients corresponding to the label 2, and 5 negative medical outcomes of the discharged patients corresponding to the label 3, so that the probability of the negative medical outcomes of the discharged patients corresponding to the label 3 is as low as 5%, and the patient A to be admitted is pushed to carry out nutrition treatment until the nutrition evaluation result is a3.

And S304, if so, pushing the nutrition treatment scheme, the nutrition treatment period and the review time of the patient to be admitted according to the label information and the medical outcome database of the patient to be admitted.

Optionally, if it is determined that the patient to be admitted needs to be subjected to nutrition therapy, the label information of the discharged patient matched with the label information is searched in the medical outcome database according to the label information of the patient to be admitted, and the nutrition therapy scheme of the discharged patient without any negative medical outcome is pushed to be used as the nutrition therapy scheme reference of the patient to be admitted based on the historical electronic cases of the discharged patient, and the nutrition therapy period of the discharged patient can be used as the nutrition therapy reference of the patient to be admitted.

Optionally, the nutritional regimen is used to indicate means of nutritional therapy, and the nutritional therapy cycle is used to predict the time of the out-patient nutritional therapy and prompt the physician and patient to review.

By way of example, assuming that the probability of a negative medical outcome for an discharged patient corresponding to tag 3 of patient to be admitted a in the pre-constructed medical outcome database is the lowest, the probability of a negative medical outcome for an discharged patient corresponding to tag 3 is as low as 5%, the average nutritional treatment period for an discharged patient corresponding to tag 3 is 40 days, and based on historical medical data for an discharged patient corresponding to tag 3, a nutritional treatment regimen for a patient to be admitted may be projected to be predicted, the nutritional treatment period being approximately 40 days.

In the embodiment of the application, basic information, nutrition evaluation information and crowd subdivision information of a patient to be admitted are determined by acquiring the doctor information and the inquiry information of the patient to be admitted, nutrition evaluation results and crowd subdivision results are determined based on nutrition evaluation tools and crowd subdivision rules, label information of the patient to be admitted is determined according to the nutrition evaluation results and the crowd subdivision results, then the medical results of the discharged patient corresponding to the label are matched in a medical result database according to the label of the patient to be admitted, whether the patient to be admitted needs nutrition treatment is determined, a nutrition treatment scheme of the patient without negative medical results is screened according to the matched results and pushed as a standard pole nutrition treatment scheme for reference by doctors, and the doctors predict the nutrition treatment scheme of the patient to be admitted according to the push result reference, so that the doctor can have the treatment effect of supporting the nutrition treatment scheme with a real evidence. Therefore, the effect of pushing the nutrition therapy auxiliary decision based on the nutrition evaluation result of the patient can be achieved.

In a possible implementation manner, referring to fig. 4, the operation in step S301 may specifically be:

S401, determining a target nutrition evaluation tool according to basic information and nutrition evaluation information of a patient to be admitted.

Optionally, a target nutrition evaluation tool of the patient to be admitted can be determined according to the basic information and the nutrition evaluation information of the patient to be admitted, wherein the target nutrition evaluation tool can be one or a plurality of target nutrition evaluation tools, and the selection of the target nutrition evaluation tools is mainly determined by the physiological age of the patient, the current medical history of the patient, the corresponding operation and operation codes on the doctor's advice of the patient and the Western diagnosis codes.

Optionally, a plurality of nutrition evaluation tools are available, and a patient can use a plurality of nutrition evaluation tools to analyze nutrition evaluation information to obtain nutrition evaluation results, for example, NRS-2002 is suitable for hospitalized patients of 18-90 years old, STRONG kid is suitable for hospitalized children of 1 month-18 years old, PG-SGA is suitable for tumor patients, SGA is suitable for kidney disease patients. The nutrition evaluation tool scores the nutrition condition of the patient according to the system rule based on the nutrition evaluation information of the patient, and then outputs the nutrition evaluation result of the patient.

As an alternative embodiment, the present application is exemplified by the NRS-2002 nutrition assessment tool, but is not intended to be representative of the application in which the nutrition assessment tool can only be used for nutrition assessment, and the application is not limited in detail.

Table 10 is an NRS-2002 evaluation information acquisition table, as shown in Table 10, and the NRS-2002 evaluation information acquisition information acquired by the medical system of the hospital based on the electronic medical record of the patient is shown in the following table:

table 10NRS-2002 evaluation information acquisition Table

For example, assuming that the patient to be admitted A is a 17-year-old tumor patient, the target nutrition evaluation tool for the patient to be admitted A can be determined to be three of NRS-2002, STRONG kid and PG-SGA according to the basic information and the nutrition evaluation information of the patient to be admitted A.

S402, determining a nutrition evaluation result of the patient to be admitted based on the target nutrition evaluation tool.

Optionally, the target nutrition evaluation tool scores nutrition evaluation information of the patient to be admitted based on nutrition evaluation rules of the medical system, and further determines a nutrition evaluation result of the patient to be admitted.

As an alternative embodiment, the application is exemplified by the nutritional assessment rules of the NRS-2002 nutritional assessment tool, and the assessment rules of other nutritional assessment tools are similar, as the application is not particularly limited in this regard.

Alternatively, the scoring items for severity of disease in the nutritional assessment rules are derived from the current medical history in the patient's electronic case and the disease diagnosis I CD-10 code map.

Table 11 is a table of NRS-2002 nutrition evaluation rules, as shown in Table 11, for a NRS-2002 nutrition evaluation tool in a medical system as shown in the following table:

TABLE 11NRS-2002 nutrient evaluation rules Table

S403, determining crowd subdivision results according to the basic information and crowd subdivision information of the patients to be admitted.

Optionally, the basic information and the crowd subdivision information of the patient to be admitted are analyzed based on the crowd subdivision rule to determine the crowd subdivision result of the patient to be admitted.

Optionally, the crowd subdivision result adopts a layering method and is formed by mixing a plurality of pieces of information, and the crowd subdivision result is divided into three levels from left to right and separated by '-'. The primary result can be used alone, or the primary result and the secondary result can be used together, or the primary result, the secondary result and the tertiary result can be used simultaneously.

Optionally, the structure of the crowd subdivision result includes: primary diagnostic code/primary surgery and procedure code/primary surgery and procedure level (primary) -age/sex/general surgery procedure code (secondary) -discharge other diagnostic codes/secondary surgery and procedure code/admission to department/discharge to department/mode of discharge to hospital/actual number of hospital stay/number of rescue/discharge for 31 days to plan/day to operate (tertiary).

It is noted that the first level is the most important medical information, the second level is the basic information of the patient and the secondary medical information predictable by the outpatient, and the third level is the medical information in the hospitalization process of the patient.

Table 12 is a table of patient nutrition assessments and population segment results, as shown in Table 12, for which the medical system determines based on the nutrition assessment rules and population segment rules as shown in the following table:

table 12 patient nutritional assessment and crowd subdivision results table

In the embodiment of the application, the basic information and the nutrition evaluation information of the patient to be admitted are used for determining the target nutrition evaluation tool required by the patient to be admitted, the target nutrition evaluation tool is used for determining the nutrition evaluation result of the patient to be admitted based on the nutrition evaluation rule, and the crowd subdivision result of the patient to be admitted is obtained by analyzing the crowd subdivision information of the patient to be admitted based on the crowd subdivision rule, so that the core tag information of the patient to be admitted can be determined. In this way, the effect of pushing effective nutritional therapy aid decisions based on the nutritional assessment results of the patient can be achieved.

In a possible implementation manner, the operation of step S302 may specifically be:

Optionally, the label information of the patient to be admitted includes: the nutritional evaluation results comprise a first nutritional evaluation result of a patient to be admitted and a last nutritional evaluation result before hospitalization, wherein when the nutrition of the patient to be admitted is qualified and hospitalization can be directly handled, the first nutritional evaluation result of the patient is the same as the last nutritional evaluation result before hospitalization, and the last nutritional evaluation result before hospitalization of the patient to be admitted requiring outpatient nutritional therapy is affirmed to be qualified, so that negative medical fatalities can be greatly reduced.

In a possible implementation manner, referring to fig. 5, the operation in step S303 may specifically be:

s501, according to label information of patients to be admitted and a medical outcome database, determining first patient number information of patients which are matched with the patients to be admitted and have not undergone nutrition treatment and have negative medical results in the medical outcome database.

Optionally, the number of discharged patients matching the label information of the direct hospitalization of the patient to be admitted is searched in the medical outcome database according to the label information of the patient to be admitted, i.e. the discharged patients who are directly hospitalized and are clinically treated are not treated with nutrition.

Optionally, counting the number of patients with negative medical results in the discharged patients corresponding to the label information of direct hospitalization, and determining first patient number information, wherein the first patient number information is used for indicating the ratio of the patients with negative medical results in the discharged patients corresponding to the label to the total number of the discharged patients corresponding to the label, namely the probability of the negative medical results.

By way of example, assuming 100 discharged patients matching tag 1 of patient to be admitted a are hospitalized directly-a-a 1-a2-m and 100 discharged patients matching tag 2 are hospitalized directly-b-b 1-b2-m in the pre-constructed medical outcome database, 60 negative medical outcomes are generated for the discharged patients corresponding to tag 1 and 70 negative medical outcomes are generated for the discharged patients corresponding to tag 2, the first patient number information corresponding to tag 1 is 60% and the first patient number information corresponding to tag 2 is 70%.

S502, determining second patient quantity information of the patients matched with the patients to be admitted and subjected to nutrition treatment in the medical outcome database and predicting nutrition treatment period according to the label information of the patients to be admitted and the medical outcome database.

Optionally, the number of discharged patients matched with the label information of the outpatient nutrition treatment of the patient to be admitted is searched in a medical outcome database according to the label information of the patient to be admitted, and the number of patients with negative medical results in the discharged patients corresponding to the label information of the direct hospitalization is counted, wherein the second number information is used for indicating the proportion of the patients with negative medical outcomes when the discharged patients corresponding to the label reach different nutrition evaluation results and are hospitalized again, namely the probability of the negative medical outcomes when the nutrition treatment results are different.

By way of example, assuming 100 discharged patients matching the label 3 out-patient nutrition therapy-a-a 1-a2-m of the patient to be admitted to the medical outcome database and 100 discharged patients matching the label 4 out-patient nutrition therapy-b-b 1-b2-m, wherein 10 negative medical outcomes occur for the discharged patients corresponding to the label 3, 5 negative medical outcomes for the discharged patients corresponding to the label 4, the average treatment period for the discharged patients corresponding to the label 3 is 15 days, and the average nutritional treatment period for the discharged patients corresponding to the label 4 is 20 days, it can be seen that the second patient number information for the non-negative medical outcomes corresponding to the label 3 is 90% and the average nutritional treatment period is 15 days, and the second patient number information for the non-negative medical outcomes corresponding to the label 4 is 95% and the average nutritional treatment period is 20 days.

S503, determining whether the patient to be admitted needs nutritional therapy according to the first patient quantity information and the second patient quantity information.

Optionally, the probability of occurrence of a negative medical outcome corresponding to different label information of the patient can be indicated according to the number information of the first patients and the second patient information matched with the labels of the patients to be admitted, and whether the patients to be admitted need nutritional treatment or not is indicated together according to the magnitude of the probability of the negative medical outcome.

For example, assuming that the first patient number information corresponding to the label 1 of the patient to be admitted is 60% and the first patient number information corresponding to the label 2 is 70%, the second patient number information corresponding to the label 3, in which the negative medical outcome does not occur, is 90% and the average nutritional treatment period is 15 days, and the second patient number information corresponding to the label 4, in which the negative medical outcome does not occur, is 95% and the average nutritional treatment period is 20 days in the medical outcome database, it is known that the risk of the negative medical outcome occurring when the patient to be admitted is directly hospitalized is high according to the first patient number information, and the risk of the negative medical outcome occurring when the patient to be admitted is hospitalized after the medical treatment is managed according to the second patient number information can be greatly reduced, so that the patient to be admitted needs to be subjected to nutritional treatment.

Optionally, the medical system may calculate preset weights of different negative medical events according to the severity, and output a medical quality prediction score, where the item and weight of the negative medical event may be individually adjusted by the doctor.

Alternatively, the prediction scoring result of the medical quality may be obtained by the following formula (1). Specifically, the prediction is performed for the possible negative medical outcome of the patient, and the following formula (1) is called to obtain the medical quality prediction score of the patient.

Wherein Y represents a medical quality prediction score, P _i Representing the weight corresponding to each negative medical treatment, i representing the probability of each negative medical treatment event, defaulting to a benchmark score of 10 for each negative medical treatment event,

for example, assuming that patient a to be admitted determines that a rectal tumor operation is required, that the patient a to be admitted has a negative medical outcome and a probability of 15% of infection by the surgical incision, 10% of dysuria, 5% of stoma fistula, 5% of ileus, etc., doctor x sets the preset weight of infection by the surgical incision to 0.2, the preset weight of dysuria to 0.2, the preset weight of stoma fistula to 0.3, and the preset weight of ileus to 0.3, there is a medical prediction score for each negative medical event, i.e., the medical prediction score corresponding to patient a to be admitted is y=10- (0.2 x 15% x 10+0.2 x 10% x 10+0.3 x 5% x 10+0.3 x 10) =9.2, i.e., the medical quality of patient a is high and the risk factor is low.

In the embodiment of the application, the probability of negative medical outcome of the patient to be admitted under different nutrition evaluation results can be indicated by searching the corresponding first patient quantity information and second patient quantity information in the medical outcome database according to the label information of the patient to be admitted. Therefore, the effect of pushing the nutrition therapy auxiliary decision based on the nutrition evaluation result of the patient can be achieved.

In a possible implementation manner, referring to fig. 6, the operation in step S502 may specifically be:

s601, determining whether a patient to be admitted needs nutritional therapy according to the first patient quantity information.

Optionally, the first patient number information is used to indicate a probability of a negative medical outcome of direct hospitalization of the patient to be admitted, and whether the patient to be admitted needs nutritional therapy or not can be determined according to the first patient number information, if the first patient number information is 80%, the patient to be admitted must be subjected to nutritional therapy, and if the first patient number information is 1%, the patient to be admitted may not be subjected to nutritional therapy.

S602, if so, determining the nutrition treatment period of the patient to be admitted according to the second patient quantity information and the predicted nutrition treatment period.

In the embodiment of the application, the risk of negative medical outcome occurrence in direct hospitalization of the patient to be admitted is indicated by the first patient information of the discharged patient corresponding to the label information of the patient to be admitted, and when the patient to be admitted is determined to need nutrition treatment, the nutrition treatment period of the patient to be admitted is determined according to the effect of decreasing the negative medical outcome probability corresponding to different nutrition evaluation results indicated by the second patient quantity information, so that the risk of negative medical outcome occurrence after the patient to be admitted is treated to be admitted can be greatly reduced. Therefore, the effect of pushing the nutrition therapy auxiliary decision based on the nutrition evaluation result of the patient can be achieved.

In a possible implementation manner, referring to fig. 7, the operation of step S304 may specifically be:

s701, determining the actual nutrition treatment period and the actual re-diagnosis time of the patient matched with the patient to be admitted in the medical outcome database according to the label information of the patient to be admitted and the medical outcome database.

Optionally, according to the label information of the patient to be admitted, searching medical data of the discharged patient without any negative medical outcome in a medical outcome database, taking the nutrition treatment scheme of the patient as the nutrition treatment scheme which is most matched with the patient to be admitted, and analyzing the actual nutrition treatment period and the actual review time of the nutrition treatment scheme. The nutrition treatment period comprises an average nutrition treatment period, a shortest nutrition treatment period and a longest nutrition treatment period, and the nutrition treatment scheme, the nutrition treatment period, the review time and the earliest recovery time of the patient to be admitted are preliminarily predicted according to the actual nutrition treatment period of the discharged patient.

By way of example, assuming 100 patients in the medical outcome database who match the label information of patient a to be admitted and who have not had any negative medical outcome following the treatment of nutrition, analyzing the electronic cases of these 100 discharged patients determines an average nutritional treatment period of 40 days, a longest nutritional treatment period of 56 days, and a shortest nutritional treatment period of 30 days, the nutritional treatment period of the patient to be admitted is predicted to be 40 days.

S702, pushing the nutrition treatment period, the review time and the predicted earliest recovery time of the patient to be admitted according to the actual nutrition treatment period.

Optionally, the nutritional therapy period and the review time are pushed to the clinician as reference values for the patient to be admitted based on the determined actual nutritional period for the discharged patient.

By way of example, given that 100 patients in the medical outcome database who match the tag information of patient a to be admitted and who have no negative medical outcome after the treatment of nutrition have occurred, the average actual nutritional treatment period is determined to be 40 days, the longest nutritional treatment period is 56 days, the shortest nutritional treatment period is 30 days, the average nutritional treatment period delivered to clinician x is 40 days, the longest nutritional treatment period is 56 days, the shortest nutritional treatment period is 30 days, the review time is 30 days, and the earliest recovery time is 30 days, based on the electronic cases of the discharged patients.

S703, determining the actual nutrition treatment scheme of the patient matched with the patient to be admitted in the medical outcome database according to the label information of the patient to be admitted and the medical outcome database.

Optionally, searching the discharged patient without any negative medical outcome after the business care treatment matched with the label information of the patient in the medical outcome database according to the label information of the patient to be admitted, and determining the nutritional treatment scheme recorded in the electronic medical record of the patient as the nutritional treatment scheme of the patient to be admitted. It is worth noting that the pushed nutritional therapy aid decision may comprise a plurality of nutritional therapy regimens or may comprise only one nutritional therapy regimen.

S704, pushing the nutritional treatment scheme of the patient to be admitted according to the actual nutritional treatment scheme.

Optionally, the doctor is pushed with the nutritional therapy regimen of the patient to be admitted according to the actual nutritional therapy regimen recorded in the electronic medical record of the discharged patient whose label information is the best match and which does not have any negative medical incidents.

In the embodiment of the application, the electronic medical records of the discharged patients which are most matched with the label information of the patients to be admitted and have no negative medical accidents are searched in the medical outcome database through the label information of the patients to be admitted, the nutrition treatment period of the patients to be admitted is predicted according to the historical electronic medical records, and the nutrition treatment schemes supported by clinical data are pushed to the patients to be admitted, so that the main doctor is taken as a reference scheme, and the beneficial effect of nutrition treatment can be ensured. Therefore, the effect of pushing the nutrition therapy auxiliary decision based on the nutrition evaluation result of the patient can be achieved.

Fig. 8 as a possible implementation of the nutritional therapy aid decision pushing, referring to fig. 8, the nutritional therapy aid decision pushing method further includes:

s801, basic information, nutrition evaluation result information, negative medical result information, medical expense information and crowd subdivision information of discharged patients and admission routes are acquired.

Optionally, the medical outcome database interfaces with a medical system of the hospital to obtain historical electronic medical records of discharged patients, and basic information, nutrition evaluation result information, negative medical result information, medical expense information, crowd subdivision information and admission routes of the discharged patients are obtained from the historical electronic medical records based on certain preset rules.

S802, recording basic information, negative medical result information, medical expense information and crowd subdivision information of the discharged patient, admission routes, nutrition evaluation result information and nutrition evaluation tools into a medical outcome database.

Optionally, the obtained basic information, negative medical result information, medical cost information, crowd subdivision information, admission route, nutrition evaluation result information and nutrition evaluation tool of the discharged patient are recorded into a medical outcome database, and the method can be suitable for matching in the database through the label information of the discharged patient to find the patient medical data optimally adapted to the condition of the discharged patient.

In the embodiment of the application, basic information, negative medical result information, medical expense information and crowd subdivision information, admission routes, nutrition evaluation result information and nutrition evaluation tools of discharged patients are counted through analyzing the historical electronic medical records of the discharged patients, so that the expected clinical medical data can be matched in a database through label information of the patients to be admitted. Therefore, the effect of pushing the nutrition therapy auxiliary decision based on the nutrition evaluation result of the patient can be achieved.

The following describes a device, equipment, a computer readable storage medium, etc. for implementing the nutritional therapy assistance decision pushing method provided by the present application, and specific implementation processes and technical effects thereof are referred to above, and are not described in detail below.

Fig. 9 is a schematic structural diagram of a nutritional therapy assistance decision push device according to an embodiment of the present application, referring to fig. 9, the device includes:

the first determining module 901 is configured to determine a nutrition evaluation result and a crowd subdivision result of a patient to be admitted according to basic information, nutrition evaluation information and crowd subdivision information of the patient to be admitted;

the generating module 902 is configured to generate label information of a patient to be admitted according to a nutrition evaluation result and a crowd subdivision result of the patient to be admitted;

A second determining module 903, configured to determine whether the patient to be admitted needs to undergo nutritional therapy according to the label information of the patient to be admitted and a medical outcome database that is pre-constructed, where the medical outcome database is used to record basic information, medical expense, crowd subdivision information, negative medical result information, admission route, nutritional assessment result information, and nutritional assessment tool of the patient who has been discharged;

and the pushing module 904 is configured to push the nutritional treatment scheme, the nutritional treatment period and the review time of the patient to be admitted to predict the earliest recovery time according to the label information of the patient to be admitted to the patient and the medical outcome database if the patient to be admitted to the patient is not admitted to the patient.

As an alternative embodiment, the first determining module 901 is specifically configured to:

As an alternative embodiment, the generating module 902 is specifically configured to:

As an alternative embodiment, the second determining module 903 is specifically configured to:

As an alternative embodiment, the second determining module 903 may be further configured to:

As an alternative embodiment, the pushing module 904 is specifically configured to:

As an alternative embodiment, the nutritional therapy profile pushing device may in particular also be used for:

the basic information, negative medical outcome information, medical cost information, and crowd subdivision information, admission routes, nutritional assessment outcome information, and nutritional assessment tools for the discharged patient are recorded into a medical outcome database.

The foregoing apparatus is used for executing the method provided in the foregoing embodiment, and its implementation principle and technical effects are similar, and are not described herein again.

The above modules may be one or more integrated circuits configured to implement the above methods, for example: one or more application specific integrated circuits (Application Specific Integrated Circuit, abbreviated as ASICs), or one or more microprocessors, or one or more field programmable gate arrays (Field Programmable Gate Array, abbreviated as FPGAs), etc. For another example, when a module above is implemented in the form of a processing element scheduler code, the processing element may be a general-purpose processor, such as a central processing unit (Central Processing Unit, CPU) or other processor that may invoke the program code. For another example, the modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).

Fig. 10 is a schematic structural diagram of a computer device according to an embodiment of the present application. Referring to fig. 10, a computer apparatus includes: memory 1001, and processor 1002, and the memory 1001 stores a computer program executable on the processor 1002, and when the processor 1002 executes the computer program, the steps in any of the above-described method embodiments are implemented.

Embodiments of the present application also provide a computer readable storage medium storing a computer program which, when executed by a processor, performs the steps of the respective method embodiments described above.

Optionally, the present application also provides a program product, such as a computer readable storage medium, comprising a program for performing any of the above-described embodiments of the nutritional therapy aid decision pushing method when being executed by a processor.

In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of elements is merely a logical functional division, and there may be additional divisions of actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

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 units may be implemented in hardware or in hardware plus software functional units.

The integrated units implemented in the form of software functional units described above may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium, and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor (english: processor) to perform part of the steps of the methods of the embodiments of the invention. And the aforementioned storage medium includes: u disk, mobile hard disk, read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), magnetic disk or optical disk, etc.

The foregoing is merely illustrative of embodiments of the present application, and the present application is not limited thereto, and any changes or substitutions can be easily made by those skilled in the art within the technical scope of the present application, and the present application is intended to be covered by the present application. Therefore, the protection scope of the application is subject to the protection scope of the claims.

The above description is only of the preferred embodiments of the present application and is not intended to limit the present application, but various modifications and variations can be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A nutrition therapy aid decision pushing method, comprising:

determining a nutrition evaluation result and a crowd subdivision result of a patient to be admitted according to basic information, nutrition evaluation information and crowd subdivision information of the patient to be admitted;

If yes, pushing the nutrition treatment scheme, the nutrition treatment period, the review time and the prediction earliest time of treatment of the patient to be admitted according to the label information of the patient to be admitted and the medical outcome database.

2. The nutrition therapy aid decision pushing method according to claim 1, wherein the determining the nutrition evaluation result and the crowd subdivision result of the patient to be admitted according to the basic information, the nutrition evaluation information and the crowd subdivision information of the patient to be admitted comprises:

and determining the crowd subdivision result according to the basic information and crowd subdivision information of the patient to be admitted.

3. The nutrition therapy aid decision pushing method according to claim 2, wherein the generating label information of the patient to be admitted according to the nutrition evaluation result and the crowd subdivision result of the patient to be admitted comprises:

4. The nutritional therapy assistance decision pushing method according to claim 1, wherein said determining whether said patient to be admitted needs nutritional therapy based on said label information of said patient to be admitted and a pre-constructed medical outcome database comprises:

determining first patient quantity information which is matched with the patient to be admitted and has no nutrition treatment and negative medical results in the medical outcome database according to the label information of the patient to be admitted and the medical outcome database;

determining second patient quantity information and a predicted nutritional treatment period of nutritional treatment in patients matched with the patient to be admitted in the medical outcome database according to the label information of the patient to be admitted and the medical outcome database;

and determining whether the patient to be admitted needs nutritional treatment or not according to the first patient quantity information and the second patient quantity information.

5. The nutritional therapy assistance decision push method according to claim 4, wherein said determining whether the patient to be admitted needs nutritional therapy based on the first patient number information and the second patient number information comprises:

if yes, determining the nutrition treatment period of the patient to be admitted according to the second patient quantity information and the predicted nutrition treatment period.

6. The nutritional therapy aid decision pushing method according to claim 1, wherein determining and pushing the nutritional therapy regimen, the nutritional therapy cycle, the review time and the predicted earliest time of receipt of the patient to be admitted according to the label information of the patient to be admitted and the medical outcome database comprises:

pushing the nutritional treatment period, the review time and the predicted earliest recovery time of the patient to be admitted according to the actual nutritional treatment period;

determining an actual nutritional treatment scheme of a patient matched with the patient to be admitted in the medical outcome database according to the label information of the patient to be admitted and the medical outcome database;

Pushing the nutritional therapy regimen of the patient to be admitted according to the actual nutritional therapy regimen.

7. The nutrition therapy assistance decision push method according to any one of claims 1-6, further comprising:

recording the basic information, negative medical outcome information, medical cost information, and crowd subdivision information, admission route, nutritional assessment outcome information, and nutritional assessment tool of the discharged patient into the medical outcome database.

8. A nutrition therapy aid decision pushing device, the device comprising:

the first determining module is used for determining the nutrition evaluation result and the crowd subdivision result of the patient to be admitted according to the basic information, the nutrition evaluation information and the crowd subdivision information of the patient to be admitted;

the generation module is used for generating label information of the patient to be admitted according to the nutrition evaluation result and the crowd subdivision result of the patient to be admitted;

the second determining module is used for determining whether the patient to be admitted needs nutritional treatment according to the label information of the patient to be admitted and a medical outcome database which is constructed in advance, wherein the medical outcome database is used for recording basic information, medical expense, crowd subdivision information, negative medical result information, admission route, nutritional assessment result information and nutritional assessment tools of the patient to be admitted;

9. A computer device, comprising: memory, a processor, in which a computer program is stored which is executable on the processor, when executing the computer program, realizing the steps of the method of any of the preceding claims 1 to 7.

10. A computer readable storage medium, characterized in that it has stored thereon a computer program which, when executed by a processor, implements the steps of the method according to any of claims 1 to 7.