Hospital operation decision analysis system based on data element driving

Abstract

The invention discloses a hospital operation decision analysis system based on data element driving, relates to the technical field of medical data management, and aims to solve the technical problems of data dispersion, analysis lagging and difficulty in accurately formulating resource configuration and cost control strategies in traditional Chinese medicine hospital operation. The data integration module is used for integrating multi-source heterogeneous data and ensuring secure storage of the data; the data management module is used for standardizing the data and ensuring the accuracy, consistency and safety of the data; and the traditional Chinese medicine dominant disease identification module is used for quantitatively defining traditional Chinese medicine dominant diseases based on the data elements. According to the invention, an adaptation mechanism of the traditional Chinese medicine syndrome and the standardization system is established, balance analysis of quantitative indexes and traditional Chinese medicine characteristics is combined, the compatibility problem of traditional Chinese medicine cost accounting and medical insurance grouping logic is solved through the medical insurance policy adaptation module, and the adaptation fault of the traditional Chinese medicine uniqueness and the standardization system is filled.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical data management, more particularly to a hospital operation decision analysis system based on data element driving. BACKGROUND

[0002] In the field of traditional Chinese medicine hospital operation management, there is a core technical problem: the uniqueness of traditional Chinese medicine diagnosis and treatment and the existing standardization system, quantitative analysis logic exist adaptation fault, leading to the difficulty of accurately defining traditional Chinese medicine advantage diseases through multi-source data, and the dynamic linkage between traditional Chinese medicine advantage diseases and medical insurance policy exists implicit deviation, which cannot provide scientific data support for hospital operation decision.

[0003] Specifically, traditional Chinese medicine syndrome differentiation and treatment scheme have subjective and personalized characteristics, and there are core logical differences between them and standardized tools such as ICD-10 coding and CMI disease difficulty index based on western medicine logic, which makes the quantitative identification of traditional Chinese medicine advantage diseases prone to distortion; At the same time, the cost accounting rules of traditional Chinese medicine treatment are not compatible with the western medicine cost logic of medical insurance DIP / DRG grouping, which leads to insufficient adaptability of medical insurance policy, further affecting the rationality of resource allocation, therefore, we propose a hospital operation decision analysis system based on data element driving. SUMMARY

[0004] The purpose of the present application is to provide a hospital operation decision analysis system based on data element driving, to solve the technical problems of data dispersion, analysis lag, and difficulty in accurately formulating resource allocation and cost control strategy in traditional Chinese medicine hospital operation.

[0005] To solve the above technical problems, the present application provides the following technical scheme: a hospital operation decision analysis system based on data element driving, comprising: A data acquisition and storage module is used for integrating multi-source heterogeneous data and ensuring safe storage of data; A data governance module is used for standardizing data processing to ensure the accuracy, consistency and security of data; A traditional Chinese medicine advantage disease identification module is used for quantitatively defining traditional Chinese medicine advantage diseases based on data elements; A medical insurance policy adaptation and settlement analysis module is used to realize the dynamic linkage between traditional Chinese medicine diseases and medical insurance policy; A decision support and optimization module is used to generate resource allocation suggestions and realize dynamic optimization based on feedback; An additional function module is used to provide traditional Chinese medicine diagnosis and treatment data deep management, cost analysis and diagnosis and treatment path index evaluation functions.

[0006] The application establishes the adaptation mechanism of TCM disease and standardization system (such as the mapping relationship between TCM disease and ICD-10 code) through the cooperation of TCM advantage disease identification module and data management module, and realizes the accurate definition of TCM advantage disease by combining the quantitative indexes such as the cure rate, VAS / ADL score and the balance analysis of TCM characteristics, and solves the compatibility problem of TCM cost accounting and medical insurance grouping logic through the medical insurance policy adaptation module, which fills the adaptation fault of TCM uniqueness and standardization system.

[0007] Preferably, the data acquisition and storage module comprises: An internal data acquisition unit is configured to acquire internal multi-system data of the hospital, including TCM diagnosis and treatment data of the HIS system, disease information of the medical record system, cost data of the financial system, and medical staff configuration data of the human resource system; An external data acquisition unit is configured to access DIP / DRG grouping data and medical insurance policy files of the medical insurance system; The DIP / DRG grouping data of the medical insurance system comprises disease score, payment standard and grouping rule, and the medical insurance policy files comprise TCM advantage disease list, payment proportion adjustment rule and regional medical insurance policy difference; A storage unit is configured to store structured data and unstructured data by using a distributed database, and to encrypt patient privacy data by using an AES encryption algorithm, wherein the structured data comprises cost, settlement data and coding mapping table, the unstructured data comprises TCM diagnosis and treatment scheme text and medical record full text, and the patient privacy data comprises ID number, medical record details and diagnosis and treatment records.

[0008] Preferably, the data management module comprises a data standardization unit, a data cleaning unit and a security control unit: The data standardization unit is configured to establish the mapping relationship between TCM disease and ICD-10 code, and to formulate cost accounting rules to unify data caliber; The data cleaning unit is configured to check the consistency of TCM treatment cost proportion and disease type, to eliminate repeated case data, and to correct error data to remove abnormal data; The security control unit is configured to use a role-based permission management model to limit the data viewing range of different roles, and to retain all data operation logs for audit and trace.

[0009] Preferably, the TCM advantage disease identification module comprises: A cure rate calculation unit is configured to calculate the cure rate of a single disease by counting cases with a TCM treatment cost proportion of total treatment cost of more than 50% and marking them as TCM advantage cases; A disease stratification unit is configured to combine disease difficulty index With average residual , the disease type is divided by a Boston matrix; The efficacy evaluation unit introduces VAS pain score and ADL daily function recovery score to compare the efficacy difference between TCM and non-TCM treatment schemes.

[0010] Preferably, the disease type division by the Boston matrix specifically includes: and developing diseases ( and ), potential diseases ( and ), and diseases to be optimized ( and ).

[0011] Preferably, the medical insurance policy adaptation and settlement analysis module includes: The policy matching unit is used to compare the identified TCM dominant diseases with the medical insurance catalog, mark the diseases that can enjoy tilted payment, and track the medical insurance policy updates to automatically update the matching relationship between the diseases and the policy; The DIP / DRG settlement analysis unit is used to calculate the medical insurance balance of TCM diseases and identify the settlement mode; The early warning unit is used to set a medical insurance overspending risk threshold, when a disease triggers the threshold for three consecutive months, it pushes the early warning information including the disease name, overspending amount, proportion, and preliminary analysis of overspending reasons.

[0012] Preferably, the decision support and optimization module includes a resource allocation unit, a path optimization unit, and a feedback iteration unit; The resource allocation unit is used to output resource adjustment suggestions for dominant diseases; The path optimization unit optimizes the TCM diagnosis and treatment path based on the medical insurance balance data and the efficacy evaluation results, including reducing unnecessary western medicine examinations, increasing TCM characteristic projects, and adjusting the use proportion of traditional Chinese medicine decoction and Chinese patent medicine; The feedback iteration unit is used to compare the indicators before and after the decision execution every quarter, and adjust the disease stratification threshold and resource allocation model parameters based on the difference.

[0013] Preferably, the additional function module includes: The TCM diagnosis and treatment data management and analysis unit is used to realize standardized processing, in-depth analysis, and characteristic advantage mining of TCM diagnosis and treatment data; The cost and expense analysis unit is used to realize fine analysis of costs and expenses of departments and diseases and optimization of medical resources; The diagnosis and treatment path index evaluation unit is used to update the efficacy of clinical path and TCM diagnosis and treatment path in real time according to prescription, examination items, and efficacy, and output the efficacy rating based on VAS / ADL score.

[0014] Preferably, the traditional Chinese medicine diagnosis and treatment data management and analysis unit comprises: A traditional Chinese medicine medical record input module for standardizing and storing the traditional Chinese medicine medical record text, and extracting high-frequency diagnosis and treatment scheme topics through topic model analysis; A traditional Chinese medicine diagnosis and treatment characteristic advantage module comprising a traditional Chinese medicine expert diagnosis advantage disease directory, a traditional Chinese medicine treatment cost proportion analysis, a traditional Chinese medicine advantage disease identification and curative effect comparison, for outputting the use of traditional Chinese medicine and Chinese medicine, and screening the advantage diseases of traditional Chinese medicine treatment through score change; A traditional Chinese medicine diagnosis and treatment path module for constructing a diagnosis and treatment path based on historical cases and dynamically updating the diagnosis and treatment path; A traditional Chinese medicine doctor diagnosis and treatment characteristic module for identifying the main diseases, prescriptions and curative effects of doctors, and analyzing the cost proportion and prescription preference; A traditional Chinese medicine treatment cost module for screening characteristic advantage cases and doctors.

[0015] Preferably, the cost and expense analysis unit comprises: A department cost analysis module for calculating the bed average score, analyzing the cost structure and regional ranking correlation, and monitoring the cost per visit, the cost per disease, the bed average score and the income and expenditure ratio index; A disease cost structure module for displaying disease cost structure and regional comparison data, and outputting medical resource optimization scheme; A disease cost and DRG grouping module for providing grouping cost structure and regional ranking, and providing basis for cost control.

[0016] Compared with the prior art, the present application has the following advantages: 1. The present application establishes the adaptation mechanism of traditional Chinese medicine disease and standardization system (such as the mapping relationship between traditional Chinese medicine disease and ICD-10 code) through the cooperation of the traditional Chinese medicine advantage disease identification module and the data management module, and realizes the accurate definition of traditional Chinese medicine advantage diseases by combining the balance analysis of quantitative indexes such as cure rate, VAS / ADL score and traditional Chinese medicine characteristics, and solves the compatibility problem of traditional Chinese medicine cost accounting and medical insurance grouping logic through the medical insurance policy adaptation module, which fills the adaptation fault of traditional Chinese medicine uniqueness and standardization system.

[0017] 2. The present application also strengthens the protection of unique privacy information such as "constitution identification" and "emotional state" in traditional Chinese medicine medical records through the security mechanism of distributed database storage combined with AES encryption and RBAC permission management, which not only ensures the safe storage of multi-source heterogeneous data, but also solves the problem of differential protection of traditional Chinese medicine privacy data and conventional privacy data, and avoids the leakage of core diagnosis and treatment information.

[0018] 3. This invention also leverages the dynamic iteration function of the decision support and optimization module to address the differentiated identification of TCM-specific diseases under different regional medical insurance policies. By adjusting the disease stratification threshold and resource allocation parameters through quarterly feedback, it solves the adaptation problem between TCM-specific regional diseases and the unified medical insurance framework, thereby improving the utilization efficiency of regional TCM resources and the accuracy of medical insurance settlement. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the system framework of the present invention. Detailed Implementation

[0020] Example 1: As Figure 1 As shown, the present invention relates to a data-driven hospital operation decision analysis system, comprising a data acquisition and storage module, a data governance module, a TCM advantageous disease identification module, a medical insurance policy adaptation and settlement analysis module, a decision support and optimization module, and additional functional modules: The data acquisition and storage module is used to integrate multi-source heterogeneous data, ensure secure data storage, and provide basic data support for subsequent analysis. The data acquisition and storage module includes an internal data acquisition unit, an external data acquisition unit, and a storage unit. Internal data acquisition unit, used to collect data from multiple systems within the hospital; In embodiments of the present invention, the multi-system data specifically includes: Traditional Chinese medicine diagnosis and treatment data (syndrome differentiation, prescriptions, acupuncture and massage, etc.) from the HIS system. Disease information in the medical record system (ICD-10 code, TCM disease and syndrome code); Cost data from the financial system (departmental costs, disease-specific costs, drug and consumable costs); Medical staff allocation data (number of physicians, professional titles, department allocation, etc.) from the human resources system.

[0021] External data acquisition unit, accessing DIP / DRG grouping data and medical insurance policy documents from the medical insurance system; In embodiments of the present invention, the DIP / DRG grouping data of the medical insurance system includes disease scores, payment standards, and grouping rules, and the medical insurance policy documents include a list of traditional Chinese medicine advantageous diseases, payment ratio adjustment rules, and regional differences in medical insurance policies; The storage unit uses a distributed database (such as MongoDB) to store structured and unstructured data, and uses the AES encryption algorithm to encrypt patient privacy data to ensure data storage security. The structured data includes cost, settlement data, and coding mapping table, the unstructured data includes traditional Chinese medicine diagnosis and treatment scheme text and medical record full text, and the patient privacy data includes ID card number, medical record details and diagnosis and treatment record. The data governance module is used for standardizing the data to ensure the accuracy, consistency and security of the data. The data governance module comprises a data standardization unit, a data cleaning unit and a security control unit. The data standardization unit is used for unifying the data caliber. In the embodiment of the present application, the unified data caliber specifically comprises: establishing the mapping relationship between traditional Chinese medicine disease and ICD-10 coding (such as the bidirectional mapping table of the corresponding traditional Chinese medicine disease coding and western medicine diagnosis coding of "lumbar disc herniation"); formulating the cost accounting rules (such as the human cost and consumable cost allocation proportion of acupuncture project); The data cleaning unit removes abnormal data through logical verification. In the embodiment of the present application, the removal of abnormal data through logical verification specifically comprises: verifying the consistency of the proportion of traditional Chinese medicine treatment cost and disease type (such as the proportion of traditional Chinese medicine treatment cost of traditional Chinese medicine dominant disease should be significantly higher than that of non-dominant disease); eliminating repeated case data (based on the repeated verification of medical record number and hospitalization time); correcting error data (such as negative cost amount, coding format error, etc.); The security control unit adopts a role-based permission management (RBAC) model. In the embodiment of the present application, the role-based permission management (RBAC) model specifically comprises: the department director can only view the cost and disease data of the department, the hospital director can view the data of the whole hospital; all data operation logs (operator, time, content, IP address) are retained for audit traceability to prevent data leakage or abuse.

[0022] The traditional Chinese medicine dominant disease identification module is used for quantitatively defining the traditional Chinese medicine dominant disease based on data elements to provide a basis for subsequent linkage analysis. In the embodiment of the present application, the traditional Chinese medicine dominant disease identification module comprises: The treatment rate calculation unit calculates the proportion of traditional Chinese medicine treatment cost (traditional Chinese medicine decoction cost + traditional Chinese medicine diagnosis and treatment project cost) in total treatment cost, and marks the case as a traditional Chinese medicine dominant case; and calculates the treatment rate of a single disease (the number of traditional Chinese medicine dominant cases / the total number of cases of the disease). The disease stratification unit combines the disease difficulty index with the average residual Disease types are classified using the Boston Matrix; In embodiments of the present invention, the classification of disease types using the Boston Matrix specifically includes: dominant diseases ( and ), development of disease types ( and Potential diseases () and Diseases to be optimized and ); The efficacy evaluation unit introduces the VAS pain score (0-10 points, the lower the score, the less pain) and the ADL daily function recovery score (0-100 points, the higher the score, the better the function) to compare the efficacy differences between traditional Chinese medicine and non-traditional Chinese medicine treatment plans. In an embodiment of the present invention, comparing the efficacy differences between traditional Chinese medicine (TCM) and non-TCM treatment plans specifically includes: calculating the mean and standard deviation of the decrease in VAS scores and the increase in ADL scores in the TCM treatment group and the Western medicine treatment group, and analyzing the significance of efficacy through a T-test; The following formula is derived from the two-sample independent t-test in statistics, primarily used to determine whether there is a significant difference between the means of two independent samples, thereby assessing whether the effects of traditional Chinese medicine (TCM) and Western medicine treatments differ in terms of VAS score reduction. This application applies the classic two-sample independent t-test formula, combined with VAS score reduction data from the TCM and Western medicine treatment groups. The specific derivation process is as follows: In an embodiment of the present invention, the mean is calculated as follows: ; ; In the formula, To reflect the mean decrease in VAS score of the TCM treatment group, Representing the first in the TCM treatment group The decrease in VAS score for each individual, The value ranges from 1 to , This refers to the sample size of the Traditional Chinese Medicine (TCM) treatment group, i.e., the number of TCM treatment patients who participated in the experiment or statistical analysis. The mean decrease in VAS score in the Western medicine treatment group. Indicating the first in the Western medicine treatment group The decrease in VAS score for each individual, The value ranges from 1 to , This refers to the sample size of the Western medicine treatment group, i.e., the number of patients treated with Western medicine. formula Originated from the formula of calculating the mean of a sample in statistics. In this application, it represents the mean of the VAS score reduction of the TCM treatment group. The mean is calculated by adding the VAS score reductions of all individuals in the TCM treatment group and dividing the sum by the sample size of the group. The mean value of the VAS score reduction of the TCM treatment group is obtained, reflecting the average level of the VAS score reduction of the TCM treatment group as a whole.

[0023] Formula Similarly, the mean of the VAS score reduction of the Western medicine treatment group is calculated by applying the formula of calculating the mean of a sample, i.e., by summing the VAS score reductions of all individuals in the Western medicine treatment group and dividing the sum by the sample size. The mean value of the VAS score reduction of the Western medicine treatment group is obtained, reflecting the average level of the VAS score reduction of the Western medicine treatment group.

[0024] In the embodiments of the present application, the standard deviation is calculated as follows: ; ; In the formula, the standard deviation of the TCM treatment group is calculated, which is used to measure the dispersion of the VAS score reductions of the individuals in the TCM treatment group relative to the mean , the degree of freedom is the standard deviation of the Western medicine treatment group is calculated, which is used to measure the dispersion of the VAS score reductions of the individuals in the Western medicine treatment group relative to the mean , the degree of freedom is Formula Based on the formula of calculating the standard deviation of a sample in statistics, the formula is used to calculate the standard deviation of the TCM treatment group, which is used to measure the dispersion of the VAS score reductions of the individuals in the TCM treatment group relative to the mean . The formula first calculates the square of the difference between each individual value and the mean, then adds these square values and divides the sum by the sample size minus 1, and finally takes the square root. The larger the standard deviation, the more dispersed the data, i.e., the greater the difference in the VAS score reductions of the individuals in the TCM treatment group.

[0025] Formula and have the same calculation logic, which is used to calculate the standard deviation of the Western medicine treatment group, reflecting the dispersion of the data in the Western medicine treatment group.

[0026] In the embodiments of the present application, the pooled variance is calculated as follows: ; In the formula, is the pooled variance in the two-sample independent T test, , the variances of the TCM treatment group and the Western medicine treatment group, respectively; Formula is the formula for calculating the pooled variance in the two-sample independent T test. In this application, it comprehensively considers the variance information of the two treatment groups of traditional Chinese medicine and Western medicine, and is used for comparing the two groups of data in the test. The formula obtains a pooled variance estimate by dividing the sum of the product of the degrees of freedom (sample size minus 1) of the two groups and the variance by the sum of the degrees of freedom of the two groups, which is used for subsequent calculation of statistic.

[0027] In the embodiments of the present application, the T statistic is calculated as: , wherein is the T statistic in the two-sample independent T test, is the pooled standard deviation (s) ). The logical relationship of these formulas is as follows: first, the mean value calculation formula is used to obtain the mean value of the VAS score reduction of the traditional Chinese medicine and Western medicine treatment groups, reflecting the average treatment effect of the two groups; then the standard deviation calculation formula is used to obtain the dispersion degree of the data of the two groups; based on the former two, the pooled variance is calculated, which comprehensively considers the variance information of the two groups; finally, the mean difference, the pooled variance and the sample size are substituted into the statistic formula to determine whether there is a significant difference between the treatment effects of the two groups, thereby providing a quantitative basis for the efficacy evaluation of the traditional Chinese medicine dominant disease.

[0028] The formula is the T statistic calculation formula in the two-sample independent T test. In this application, it is used to measure whether the mean difference between the traditional Chinese medicine treatment group and the Western medicine treatment group is significant. The larger the T value, the more obvious the mean difference between the two groups. The formula obtains a standardized statistic by calculating the difference between the means of the two groups, dividing by the product of the pooled standard deviation and the square root of the reciprocal of the sample size, which can be compared with the critical value of the T distribution, so as to determine whether there is a statistically significant difference between the two groups in the VAS score reduction.

[0029] The medical insurance policy adaptation and settlement analysis module is used to realize the dynamic linkage of the traditional Chinese medicine disease and the medical insurance policy, balance the compliance and the benefit; In the embodiments of the present application, the medical insurance policy adaptation and settlement analysis module comprises a policy matching unit, a DIP / DRG settlement analysis unit and a warning unit. The policy matching unit is used to compare the identified traditional Chinese medicine dominant disease with the medical insurance directory (regional traditional Chinese medicine dominant disease recommendation directory), mark the disease that can enjoy the tilted payment (the disease with a payment ratio increased by 10%); track the medical insurance policy update, and automatically update the matching relationship between the disease and the policy.

[0030] The DIP / DRG settlement analysis unit is used to calculate the medical insurance balance (medical insurance payment amount-disease cost) of the traditional Chinese medicine disease, and identify the settlement mode. In the embodiments of the present application, the settlement mode includes: "clear surplus in reality" (medical insurance surplus > 0 and income and expenditure surplus > 0), "clear surplus in loss" (medical insurance surplus > 0 but income and expenditure surplus < 0), "clear loss in reality" (medical insurance surplus < 0 but income and expenditure surplus > 0), "clear loss in loss" (medical insurance surplus < 0 and income and expenditure surplus < 0), "surplus and loss balance - medical insurance" (medical insurance surplus = 0), "surplus and loss balance - income and expenditure" (income and expenditure surplus = 0).

[0031] The early warning unit is used for setting a medical insurance overspending risk threshold (actual cost exceeding the payment standard by 10%), when a certain disease type triggers the threshold for three consecutive months, an early warning information (including disease type name, overspending amount, proportion, etc.) is pushed to the operation team, and a preliminary analysis of overspending reasons (such as high cost of consumables, too many diagnosis and treatment projects) is attached.

[0032] The decision support and optimization module is used for generating resource configuration suggestions, and realizing dynamic optimization based on feedback; In the embodiments of the present application, the decision support and optimization module includes a resource configuration unit, a path optimization unit and a feedback iteration unit; The resource configuration unit is used for outputting resource adjustment suggestions for dominant diseases; In the embodiments of the present application, the output resource adjustment suggestions include: manpower (increasing the number of Chinese medicine physicians, adjusting physician scheduling); equipment (purchasing acupuncture treatment instruments, traditional Chinese medicine decoction machines, etc.); beds (increasing the proportion of beds in the disease area of dominant diseases, optimizing bed turnover efficiency).

[0033] The path optimization unit optimizes the Chinese medicine diagnosis and treatment path based on the medical insurance surplus data and the efficacy evaluation results; In the embodiments of the present application, the optimization of the Chinese medicine diagnosis and treatment path includes: reducing unnecessary western medicine examinations (such as reducing CT repeated examinations for lumbar disc herniation); increasing Chinese medicine characteristic projects (such as increasing moxibustion and cupping); adjusting the use proportion of traditional Chinese medicine decoction and Chinese patent medicine.

[0034] The feedback iteration unit is used for comparing the indicators (proportion of dominant diseases, medical insurance surplus rate, cure rate, VAS / ADL score improvement value) before and after the decision execution every quarter, and adjusting the disease type stratification threshold (such as adjusting the threshold of 1.8 according to the regional CMI average) and the resource configuration model parameter (such as the investment return period calculation coefficient of equipment procurement) based on the difference.

[0035] The additional function module is used for providing the functions of Chinese medicine diagnosis and treatment data deep management, cost and expense analysis and diagnosis and treatment path index evaluation; In the embodiments of the present application, the additional function module includes a Chinese medicine diagnosis and treatment data management and analysis unit, a cost and expense analysis unit and a diagnosis and treatment path index evaluation unit; The TCM diagnosis and treatment data management and analysis unit is used for realizing standardization processing, deep analysis and characteristic advantage mining of TCM diagnosis and treatment data. In the embodiment of the present application, the TCM diagnosis and treatment data management and analysis unit comprises a TCM medical record input module, a TCM diagnosis and treatment characteristic advantage module, a TCM diagnosis and treatment path module, a TCM doctor diagnosis and treatment characteristic module and a TCM treatment cost module. The TCM medical record input module is used for standardizing processing (such as unified syndrome classification terminology) of TCM medical record text, storing in categories and then performing theme model analysis (such as extracting high-frequency diagnosis and treatment scheme theme by LDA model) to provide text data support for disease identification. The TCM diagnosis and treatment characteristic advantage module comprises a TCM expert diagnosis advantage disease directory, a TCM treatment cost proportion analysis, a TCM advantage disease identification and curative effect comparison and is used for outputting TCM and Chinese medicine usage (such as TCM special disease characteristic analysis and TCM cost proportion change trend) of the whole hospital / specialty / disease; and screening TCM treatment advantage diseases through VAS score and curative effect index change before and after diagnosis and treatment. The TCM diagnosis and treatment path module constructs diagnosis and treatment paths of TCM special diseases and diagnosis diseases based on historical cases, analyzes curative effect and prescription in path execution in real time and dynamically updates path content (such as adjusting dosage of Chinese medicine prescription). The TCM doctor diagnosis and treatment characteristic module identifies mainstream diseases, prescriptions and curative effects of doctors, compares TCM diagnosis and treatment cost average of doctors with cost average of the same diagnosis group, analyzes cost proportion, displays prescription preference (such as high-frequency used Chinese medicine decoction pieces) of doctors based on diagnosis group. The TCM treatment cost module is used for counting TCM treatment cost of the whole hospital / specialty / doctor, screening TCM characteristic advantage cases (TCM treatment cost proportion ≥ preset threshold, curative effect rating is high and cost average is not lower than disease average) and identifying TCM characteristic advantage doctors (personal TCM treatment cost proportion ≥ preset threshold). The cost and cost analysis unit is used for realizing cost and cost fine analysis of departments and diseases and medical resource optimization. In the embodiment of the present application, the cost and cost analysis unit comprises a department cost analysis module, a disease cost structure module and a disease cost and DRG grouping module. The department cost analysis module is used for calculating bed average points (DIP / DRG points / bed number) of hospital departments, analyzing point difference of different departments, displaying cost structure (proportion of manpower, consumables and equipment depreciation) of single or all departments, performing correlation analysis on department cost structure and its regional ranking, establishing a cost responsibility model and realizing real-time monitoring of diagnosis cost, disease cost, bed average points and cost and income ratio.

[0036] The disease cost structure module is used to show the cost structure (drug, consumables, examination, treatment proportion) of DRG / DIP diseases and the comparison data in the region; for the same disease, the cost structure and income and expenditure of the regional benchmark hospital are compared to evaluate the reasonableness of the cost; support disease cost regional ranking query and benchmark tracking, and output medical resource optimization scheme (such as reducing the procurement cost of high proportion of consumables).

[0037] The disease cost and DRG grouping module is used to provide the cost structure (outpatient / hospitalization cost proportion) under DRG grouping and the cost average of each grouping; analyze the regional ranking of the grouping cost of each disease of the hospital; for a single disease, the grouping cost average, structure and regional benchmark cost structure are displayed to provide basis for cost control.

[0038] The diagnosis and treatment path index evaluation unit is used to update the efficacy of clinical path and traditional Chinese medicine diagnosis and treatment path in real time according to prescription drug, examination item and efficacy, and output the efficacy rating (based on VAS / ADL score to develop a grading table) to provide basis for path optimization.

[0039] Example two: taking "lumbar disc herniation" as a candidate for traditional Chinese medicine advantage disease, and expanding around the core indicators of each module: I. Data collection and storage module test data; 1. Internal data; HIS system: traditional Chinese medicine diagnosis and treatment data (200 times of acupuncture, 150 prescriptions of traditional Chinese medicine); Medical record system: ICD-10 code M51.2, traditional Chinese medicine disease code TCD-0502; Financial system: single disease cost 7500 yuan (labor 3000 yuan, consumables 1500 yuan); Human resources: 8 traditional Chinese medicine doctors and 12 nurses in the department.

[0040] 2. External data; Medical insurance DIP data: disease score 800 points, payment standard 8000 yuan, grouping rule (main diagnosis + traditional Chinese medicine treatment proportion ≥ 50%); Medical insurance policy: increase the payment proportion of traditional Chinese medicine advantage disease by 10% (from 80% to 90%).

[0041] 3. Storage information; Structured data: cost accounting table (Excel), coding mapping table (traditional Chinese medicine disease TCD-0502→ICD-10 M51.2); Unstructured data: traditional Chinese medicine diagnosis and treatment scheme text ("traction + moxibustion + Duhuo Jisheng Decoction"); encrypted privacy data: patient ID number (stored after AES encryption), medical record details.

[0042] Two, the test data of the traditional Chinese medicine advantage disease identification module; 1. Middle rate calculation unit; Total cases 100; TCM treatment cost accounted for more than 50% of the total number of cases 60 (TCM treatment costs average 4200 yuan, the total cost of the average 7000 yuan); The middle rate is 60% (60 / 100); 2. Disease stratification unit; CMI value is 2.0 (higher than 1.8); ASIP (average surplus) is 500 yuan (8000 yuan of medical insurance payment-7500 yuan of cost); Disease type is dominant disease (CMI>1.8 and ASIP>0); 3. Efficacy evaluation unit; (1) TCM treatment group (50 cases); VAS score: 7.5±1.2 before treatment, 3.0±0.8 after treatment (decrease 4.5±0.5); ADL score: 50±8 before treatment, 80±5 after treatment (increase 30±3).

[0043] (2) Western medicine treatment group (50 cases); VAS score: 7.3±1.0 before treatment, 4.3±0.9 after treatment (decrease 3.0±0.6); ADL score: 52±7 before treatment, 72±6 after treatment (increase 20±2).

[0044] (3) T test results: P<0.05 (TCM group is significantly better than western medicine group); Three, medical insurance policy adaptation and settlement analysis module test data;

[0045] Table 1 medical insurance policy adaptation and settlement analysis module test data table Four, decision support and optimization module test data;

[0046] Table 2 decision support and optimization module test data table Five, additional function module test data (part of the core indicators);

[0047] Table 3 additional function module test data table Conclusion: Based on the whole process analysis of "lumbar disc herniation" as a TCM advantage disease in the real hospital operation scene, the system function verification and effect evaluation can be supported, and the whole process analysis of "lumbar disc herniation" as a TCM advantage disease in the hospital actual operation scene is simulated systematically. Through the multi-source data integration of the data acquisition and storage module, the quantitative evaluation of the TCM advantage disease identification module, the rule verification of the medical insurance policy adaptation and settlement analysis module, the strategy deduction of the decision support and optimization module and the deep analysis of the additional function module, the effectiveness of the TCM advantage disease analysis system in data processing accuracy, disease identification scientificity, medical insurance policy adaptability, operation decision guidance and the like is fully verified. The test results show that "lumbar disc herniation" is included in the TCM advantage disease, which can not only significantly improve the clinical curative effect (the TCM group VAS score improvement is better than the western medicine group), but also optimize the medical insurance settlement income (realize the clear and real profit), and promote the improvement of the department operation efficiency (the advantage disease proportion is increased by 5%, and the medical insurance surplus rate is increased by 1.75%) through resource allocation and diagnosis and treatment path optimization. The data model provides a solid quantitative basis for the function perfection and clinical application of the TCM advantage disease analysis system, and has important reference value for the promotion of TCM characteristic diagnosis and treatment and hospital fine management.

[0048] The embodiments of the present application are disclosed, but are not limited to the embodiments, and the ordinary skilled in the art can easily understand the spirit of the present application according to the above embodiments, and make different inferences and changes, as long as they do not deviate from the spirit of the present application, which are within the protection scope of the present application.

Claims

1. A hospital operation decision analysis system based on data elements, characterized in that, include: The data acquisition and storage module is used to integrate multi-source heterogeneous data and ensure secure data storage. The data governance module is used to standardize data processing and ensure data accuracy, consistency, and security. The TCM Advantage Disease Identification Module is used to quantitatively define TCM Advantage Diseases based on data elements. The medical insurance policy adaptation and settlement analysis module is used to achieve dynamic linkage between TCM diseases and medical insurance policies; The decision support and optimization module is used to generate resource allocation suggestions and perform dynamic optimization based on feedback; Additional functional modules are provided to offer in-depth management of TCM diagnosis and treatment data, cost analysis, and evaluation of diagnosis and treatment pathway indicators.

2. The hospital operation decision analysis system based on data element-driven approach according to claim 1, characterized in that, The data acquisition and storage module includes: The internal data acquisition unit is used to collect data from multiple systems within the hospital, including TCM diagnosis and treatment data from the HIS system, disease information from the medical record system, cost data from the financial system, and medical staff allocation data from the human resources system. External data acquisition unit, accessing DIP / DRG grouping data and medical insurance policy documents from the medical insurance system; The DIP / DRG grouping data of the medical insurance system includes disease scores, payment standards, and grouping rules; the medical insurance policy documents include a list of diseases with advantages in traditional Chinese medicine, rules for adjusting payment ratios, and differences in regional medical insurance policies. The storage unit uses a distributed database to store structured and unstructured data, and encrypts patient privacy data using the AES encryption algorithm. The structured data includes cost, settlement data, and encoding mapping table. The unstructured data includes TCM treatment plan text and full medical records. The patient privacy data includes ID number, medical record details, and treatment records.

3. The hospital operation decision analysis system based on data element-driven approach according to claim 1, characterized in that, The data governance module includes a data standardization unit, a data cleaning unit, and a security control unit. Data standardization units are established by creating a mapping relationship between TCM diseases and ICD-10 codes and by formulating cost accounting rules to unify data standards. The data cleaning unit removes abnormal data by verifying the consistency between the proportion of TCM treatment costs and disease types, eliminating duplicate case data, and correcting erroneous data. The security control unit adopts a role-based access control model to restrict the data viewing scope of different roles and retain all data operation logs for auditing and traceability.

4. The hospital operation decision analysis system based on data element driving according to claim 1, characterized in that, The TCM-advantageous disease identification module includes: The TCM treatment rate calculation unit statistically analyzes cases where "TCM treatment costs account for ≥50% of total treatment costs," marks them as TCM-advantaged cases, and calculates the TCM treatment rate for a single disease. Disease stratification unit, combined with disease difficulty index and average balance Disease types are classified using the Boston Matrix; The efficacy evaluation unit incorporates the VAS pain score and ADL daily function recovery score to compare the efficacy differences between traditional Chinese medicine and non-traditional Chinese medicine treatment plans.

5. A hospital operation decision analysis system based on data element-driven approach according to claim 4, characterized in that, The classification of disease types using the Boston Matrix specifically includes: dominant diseases ( and ), development of disease types ( and Potential diseases () and ) and diseases to be optimized ( and ).

6. The hospital operation decision analysis system based on data element driving according to claim 1, characterized in that, The medical insurance policy adaptation and settlement analysis module includes: The policy matching unit is used to compare the identified TCM-advantaged diseases with the medical insurance catalog, mark the diseases that can enjoy preferential payment, and track updates to medical insurance policies, automatically updating the matching relationship between diseases and policies. The DIP / DRG settlement analysis unit is used to calculate the medical insurance surplus for TCM diseases and identify the settlement mode. The early warning unit is used to set the medical insurance overspending risk threshold. When a certain disease triggers the threshold for three consecutive months, it will push an early warning message containing the disease name, overspending amount, percentage, and preliminary analysis of the reasons for overspending.

7. The hospital operation decision analysis system based on data element driving according to claim 1, characterized in that, The decision support and optimization module includes a resource allocation unit, a path optimization unit, and a feedback iteration unit. The resource allocation unit is used to output resource adjustment suggestions for advantageous diseases; The pathway optimization unit optimizes TCM diagnosis and treatment pathways based on medical insurance surplus data and efficacy evaluation results, including reducing unnecessary Western medicine examinations, increasing TCM characteristic items, and adjusting the usage ratio of Chinese herbal medicine pieces and prepared Chinese medicines. The feedback iteration unit is used to compare indicators before and after decision implementation every quarter, and adjust the disease stratification threshold and resource allocation model parameters based on the differences.

8. The hospital operation decision analysis system based on data element driving according to claim 1, characterized in that, The additional functional modules include: The Traditional Chinese Medicine (TCM) diagnosis and treatment data management and analysis unit is used to achieve standardized processing, in-depth analysis, and the discovery of unique advantages of TCM diagnosis and treatment data. The cost and expense analysis unit is used to achieve refined cost and expense analysis for departments and diseases, as well as optimization of medical resources. The diagnostic and treatment pathway indicator evaluation unit is used to update the efficacy of clinical pathways and traditional Chinese medicine diagnostic and treatment pathways in real time based on prescription medication, examination items, and efficacy, and output efficacy ratings based on VAS / ADL scores.

9. A hospital operation decision analysis system based on data element-driven approach according to claim 8, characterized in that, The TCM diagnosis and treatment data management and analysis unit includes: The TCM medical record input module is used to standardize and classify TCM medical record texts and extract high-frequency treatment plan themes through topic model analysis. The TCM diagnosis and treatment feature and advantage module includes a directory of TCM experts' diagnostic advantages for diseases, an analysis of the proportion of TCM treatment costs, identification of TCM advantageous diseases and comparison of efficacy, which is used to output the usage of TCM and Chinese medicine, and to screen TCM treatment advantages for diseases through changes in scores; The TCM diagnosis and treatment pathway module constructs and dynamically updates diagnosis and treatment pathways based on historical cases. The TCM physician diagnosis and treatment module identifies the physician's mainstream diseases, prescriptions and efficacy, and analyzes the cost ratio and prescription preferences. The Traditional Chinese Medicine (TCM) treatment cost module provides statistics on TCM treatment costs and allows users to filter out distinctive and advantageous cases and physicians.

10. A hospital operation decision analysis system based on data element-driven approach according to claim 8, characterized in that, The cost and expense analysis unit includes: The department cost analysis module is used to calculate the average score per bed, analyze the correlation between cost structure and regional ranking, and monitor the cost per visit, cost per disease, average score per bed, and revenue-expenditure ratio. The disease cost structure module is used to display the cost structure of diseases and regional comparison data, and output medical resource optimization solutions; The disease-specific cost and DRG grouping module provides the cost structure and regional ranking for each group, thus providing a basis for cost control.

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