Hospital operation decision analysis system based on data element driving

Abstract

The application 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 problem that in traditional Chinese medicine hospital operation, data is scattered, analysis lags behind, and it is difficult to accurately formulate resource allocation and cost control strategies, and comprises a data acquisition and storage module, a data management module, a traditional Chinese medicine advantage disease identification module and the like, wherein the data acquisition and storage module is used for integrating multi-source heterogeneous data and guaranteeing safe storage of data; the data management module is used for standardizing data processing and ensuring accuracy, consistency and safety of data; and the traditional Chinese medicine advantage disease identification module is used for quantitatively defining traditional Chinese medicine advantage diseases based on data elements. The application establishes an adaptation mechanism of traditional Chinese medicine diseases and a standardization system, and solves the compatibility problem of traditional Chinese medicine cost accounting and medical insurance grouping logic through a medical insurance policy adaptation module in combination with balanced analysis of quantitative indexes and traditional Chinese medicine characteristics, and fills the adaptation fault of traditional Chinese medicine uniqueness and the standardization system.

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 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;

[0004] 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

[0005] 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.

[0006] 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:

[0007] A data acquisition and storage module is used to integrate multi-source heterogeneous data and ensure safe storage of data;

[0008] A data governance module is used to standardize data processing and ensure the accuracy, consistency and security of data;

[0009] A traditional Chinese medicine advantage disease identification module is used to quantitatively define traditional Chinese medicine advantage diseases based on data elements;

[0010] 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;

[0011] A decision support and optimization module is used to generate resource allocation suggestions and realize dynamic optimization based on feedback;

[0012] 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.

[0013] This invention establishes an adaptation mechanism between TCM disease identification and data governance modules by synergizing TCM disease identification and data governance modules (such as the mapping relationship between TCM disease and ICD-10 codes). It also combines quantitative indicators such as TCM cure rate and VAS / ADL scores with a balance analysis of TCM characteristics to achieve accurate definition of TCM disease advantages. At the same time, it solves the compatibility problem between TCM cost accounting and medical insurance grouping logic through a medical insurance policy adaptation module, thus bridging the gap between the uniqueness of TCM and the standardization system.

[0014] Preferably, the data acquisition and storage module includes:

[0015] 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.

[0016] External data acquisition unit, accessing DIP / DRG grouping data and medical insurance policy documents from the medical insurance system;

[0017] 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.

[0018] 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.

[0019] Preferably, the data governance module includes a data standardization unit, a data cleaning unit, and a security management unit:

[0020] 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.

[0021] 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.

[0022] 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.

[0023] Preferably, the TCM dominant disease identification module comprises:

[0024] A TCM treatment rate calculation unit calculates the TCM treatment rate of each disease.

[0025] A disease stratification unit combines the disease difficulty index and the average surplus to divide the disease types by the Boston matrix.

[0026] An efficacy evaluation unit introduces VAS pain score and ADL daily function recovery score to compare the efficacy difference between TCM and non-TCM treatment plans.

[0027] Preferably, the division of disease types by the Boston matrix comprises: dominant diseases ,developing diseases ,potential diseases , and diseases to be optimized . .

[0028] Preferably, the medical insurance policy adaptation and settlement analysis module comprises:

[0029] A policy matching unit compares the identified TCM dominant diseases with the medical insurance directory, marks the diseases that can enjoy tilted payment, and tracks the medical insurance policy updates to automatically update the matching relationship between the diseases and the policies.

[0030] A DIP / DRG settlement analysis unit calculates the medical insurance surplus of TCM diseases and identifies the settlement mode.

[0031] An early warning unit sets a medical insurance overspending risk threshold, and when a disease triggers the threshold for three consecutive months, it pushes early warning information containing the disease name, overspending amount, proportion, and preliminary analysis of overspending reasons.

[0032] Preferably, the decision support and optimization module comprises a resource allocation unit, a path optimization unit, and a feedback iteration unit.

[0033] The resource allocation unit outputs resource adjustment suggestions for dominant diseases.

[0034] The path optimization unit optimizes the TCM diagnosis and treatment path based on the medical insurance surplus data and the efficacy evaluation results, including reducing unnecessary Western medicine examinations, increasing TCM characteristic projects, and adjusting the use proportion of Chinese herbal pieces and Chinese patent medicines.

[0035] A feedback iteration unit is configured to compare indexes before and after decision-making every quarter, and adjust disease stratification threshold and resource allocation model parameters based on the difference.

[0036] Preferably, the additional function modules include:

[0037] A traditional Chinese medicine diagnosis and treatment data management and analysis unit is configured to implement standardized processing, in-depth analysis, and characteristic advantage mining of traditional Chinese medicine diagnosis and treatment data.

[0038] A cost and expense analysis unit is configured to implement fine analysis of costs and expenses of departments and diseases and optimization of medical resources.

[0039] A diagnosis and treatment path index evaluation unit is configured to update the efficacy of clinical paths and traditional Chinese medicine diagnosis and treatment paths in real time according to prescriptions, examination items, and efficacy, and output efficacy ratings based on VAS / ADL scoring.

[0040] Preferably, the traditional Chinese medicine diagnosis and treatment data management and analysis unit includes:

[0041] A traditional Chinese medicine medical record input module is configured to standardize and store text of traditional Chinese medicine medical records, and extract high-frequency diagnosis and treatment scheme topics through topic model analysis.

[0042] A traditional Chinese medicine diagnosis and treatment characteristic advantage module includes a directory of diseases diagnosed by traditional Chinese medicine experts, an analysis of the proportion of traditional Chinese medicine treatment expenses, identification of traditional Chinese medicine advantage diseases, and efficacy comparison, and is configured to output the use of traditional Chinese medicine and Chinese medicine, and filter traditional Chinese medicine treatment advantage diseases through score changes.

[0043] A traditional Chinese medicine diagnosis and treatment path module is configured to construct diagnosis and treatment paths based on historical cases and dynamically update them.

[0044] A traditional Chinese medicine physician diagnosis and treatment characteristic module is configured to identify mainstream diseases, prescriptions, and efficacy of physicians, and analyze expense proportions and prescription preferences.

[0045] A traditional Chinese medicine treatment expense module is configured to count traditional Chinese medicine treatment expenses and filter characteristic advantage cases and physicians.

[0046] Preferably, the cost and expense analysis unit includes:

[0047] A department cost analysis module is configured to calculate bed share values, analyze cost structures and regional ranking correlations, and monitor visit costs, disease costs, bed share values, and income and expense ratio indexes.

[0048] A disease cost structure module is configured to display disease cost structures and regional comparison data, and output medical resource optimization schemes.

[0049] A disease expense and DRG grouping module is configured to provide grouping expense structures and regional rankings, and provide a basis for expense control.

[0050] Compared with the prior art, the present application has the beneficial effects that:

[0051] 1. The present 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 governance module, and realizes the accurate definition of TCM advantage disease by combining the quantitative indicators such as TCM treatment 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.

[0052] 2. The present application also strengthens the protection of unique privacy information such as "constitution identification" and "emotional state" in TCM 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 TCM privacy data and conventional privacy data, avoiding the leakage of core diagnosis and treatment information.

[0053] 3. The present application also solves the adaptation problem of TCM regional characteristic disease and medical insurance unified framework through the dynamic iteration function of decision support and optimization module, and adjusts the disease stratification threshold and resource allocation parameters through quarterly feedback according to the differential identification of different regional medical insurance policies for TCM characteristic diseases, which improves the utilization efficiency of regional TCM resources and the accuracy of medical insurance settlement. BRIEF DESCRIPTION OF DRAWINGS

[0054] Figure 1 The figure is a schematic diagram of the system framework of the present application. DETAILED DESCRIPTION

[0055] Example 1: As shown in the figure, the present application relates to a hospital operation decision analysis system based on data element driving, which includes data collection and storage module, data governance module, TCM advantage disease identification module, medical insurance policy adaptation and settlement analysis module, decision support and optimization module and additional function module: Figure 1

[0056] The data collection and storage module is used to integrate multi-source heterogeneous data and ensure the safe storage of data, providing basic data support for subsequent analysis;

[0057] The data collection and storage module includes internal data collection unit, external data collection unit and storage unit:

[0058] The internal data collection unit is used to collect multi-system data in the hospital;

[0059] In the embodiment of the present application, the multi-system data specifically includes:

[0060] ​TCM diagnosis and treatment data (TCM project such as syndrome differentiation, prescription, acupuncture and massage) of HIS system;

[0061] Disease information (ICD-10 code, TCM disease code) of medical record system;

[0062] Cost data (department cost, disease cost, drug and consumable cost) of financial system;

[0063] Medical staff allocation data (number of physicians, professional title, department allocation, etc.) of human resource system.

[0064] An external data acquisition unit accesses DIP / DRG grouping data and medical insurance policy files of a medical insurance system;

[0065] In the embodiment of the present application, the DIP / DRG grouping data of the medical insurance system includes disease score, payment standard and grouping rule, and the medical insurance policy files include TCM dominant disease list, payment proportion adjustment rule and regional medical insurance policy difference;

[0066] A storage unit uses a distributed database (such as MongoDB) to store structured data and unstructured data, and uses an AES encryption algorithm to encrypt patient privacy data to ensure data storage security;

[0067] The structured data includes cost, settlement data and code mapping table, the unstructured data includes TCM diagnosis and treatment scheme text and medical record full text, and the patient privacy data includes ID number, medical record details and diagnosis and treatment record;

[0068] A data governance module is used to standardize data processing to ensure data accuracy, consistency and security;

[0069] The data governance module includes a data standardization unit, a data cleaning unit and a security control unit;

[0070] The data standardization unit is used to unify data caliber;

[0071] In the embodiment of the present application, the unified data caliber specifically includes:

[0072] A mapping relationship between TCM disease and ICD-10 code is established (such as a bidirectional mapping table of TCM disease code and Western medicine diagnosis code corresponding to “lumbar disc herniation”);

[0073] Cost accounting rules are formulated (such as human and consumable cost allocation proportion of acupuncture project);

[0074] The data cleaning unit removes abnormal data through logical verification,

[0075] In the embodiments of the present application, the removing of abnormal data through logical verification specifically includes:

[0076] Verifying the consistency of TCM treatment cost proportion and disease type (e.g. the TCM treatment cost proportion of TCM dominant diseases should be significantly higher than that of non-dominant diseases);

[0077] Eliminating duplicate case data (based on duplicate verification of medical record number and hospitalization time);

[0078] Correcting error data (e.g. negative cost amount, coding format error, etc.);

[0079] The security control unit adopts a Role-Based Access Control (RBAC) model;

[0080] In the embodiments of the present application, the RBAC model specifically includes: the department director can only view the cost and disease data of his / her department, and the hospital president can view the data of the whole hospital; all data operation logs (operator, time, content, IP address) are retained for audit and traceability, to prevent data leakage or misuse.

[0081] The TCM dominant disease identification module is used to quantitatively define TCM dominant diseases based on data elements, providing a basis for subsequent linkage analysis;

[0082] In the embodiments of the present application, the TCM dominant disease identification module includes:

[0083] The TCM treatment rate calculation unit calculates the number of cases with TCM treatment cost (Chinese herbal pieces cost + TCM diagnosis and treatment project cost) accounting for more than 50% of the total treatment cost, and marks them as TCM dominant cases; and calculates the TCM treatment rate (number of TCM dominant cases / total number of cases of the disease) of each disease;

[0084] The disease stratification unit combines disease difficulty index and average residual to divide the disease types by Boston Matrix;

[0085] In the embodiments of the present application, the division of disease types by Boston Matrix specifically includes: dominant diseases and , developing diseases and , potential diseases and , and diseases to be optimized and ;

[0086] The efficacy evaluation unit introduces VAS pain score (0-10 points, the lower the score, the less the pain) and ADL daily function recovery score (0-100 points, the higher the score, the better the function), and compares the efficacy differences of TCM and non-TCM treatment schemes;

[0087] In the embodiments of the present application, the efficacy differences of TCM and non-TCM treatment schemes specifically include: calculating the mean and standard deviation of the VAS score decrease value and the ADL score increase value of the TCM treatment group and the western medicine treatment group, and analyzing the significant effect by T test;

[0088] The following formula is derived from the two-sample independent T test method in statistics, which is mainly used to determine whether there is a significant difference in the mean of two independent samples, so as to evaluate whether the TCM and western medicine treatment effects are different in the VAS score decrease value. The present application applies the classical two-sample independent T test formula to the VAS score decrease value data of the TCM and western medicine treatment groups, and the specific derivation process is as follows:

[0089] In the embodiments of the present application, the mean is calculated as:

[0090] ;

[0091] ;

[0092] In the formula, is the mean of the VAS score decrease value of the TCM treatment group, represents the VAS score decrease value of the first individual in the TCM treatment group, is the value from 1 to , , is the sample number of the TCM treatment group, i.e. the number of TCM treatment patients participating in the experiment or statistics, is the mean of the VAS score decrease value of the western medicine treatment group, represents the VAS score decrease value of the first individual in the western medicine treatment group, is the value from 1 to , , is the sample number of the western medicine treatment group, i.e. the number of western medicine treatment patients;

[0093] The formula is derived from the calculation formula of the sample mean in statistics. In the present application, it represents the mean of the VAS score decrease value of the TCM treatment group, which is obtained by adding all the VAS score decrease values of the individuals in the TCM treatment group and dividing the sum by the sample number of the group, reflecting the average level of the VAS score decrease of the TCM treatment group as a whole.

[0094] The formula The same is the application of sample mean calculation formula, the mean of VAS score reduction value of western medicine treatment group is represented, the sum of VAS score reduction value of all individuals in western medicine treatment group is divided by the sample number , the average VAS score reduction of western medicine treatment group is reflected.

[0095] In the embodiment of the application, the standard deviation is calculated:

[0096] ;

[0097] ;

[0098] In the formula, the standard deviation of traditional Chinese medicine treatment group is calculated, which is used to measure the dispersion degree of VAS score reduction value of each individual in traditional Chinese medicine treatment group relative to the mean , is the degree of freedom, the standard deviation of western medicine treatment group is calculated, which is used to measure the dispersion degree of VAS score reduction value of each individual in traditional Chinese medicine treatment group relative to the mean , is the degree of freedom;

[0099] Formula Based on the calculation formula of sample standard deviation in statistics, the standard deviation of traditional Chinese medicine treatment group is calculated in the application, which is used to measure the dispersion degree of VAS score reduction value of each individual in traditional Chinese medicine treatment group relative to the mean . The formula first calculates the square of the difference between each individual value and the mean, adds these square values, divides by the sample number minus 1, and then takes the square root. The larger the standard deviation, the more dispersed the data, that is, the greater the difference in VAS score reduction value between individuals in the traditional Chinese medicine treatment group.

[0100] Formula and the calculation logic is the same, which is used to calculate the standard deviation of western medicine treatment group, and reflects the dispersion degree of data in western medicine treatment group.

[0101] In the embodiment of the application, the combined variance is calculated: ;

[0102] In the formula, is the combined variance in the two-sample independent T test, , the variances of traditional Chinese medicine treatment group and western medicine treatment group, respectively;

[0103] Formula is the calculation formula of combined variance in the two-sample independent T test. In the application, it comprehensively considers the variance information of traditional Chinese medicine and western medicine two treatment groups, which is used to The two groups of data are compared in the test. The formula obtains a combined variance estimate value for subsequent calculation by dividing the sum of the product of the degrees of freedom (the number of samples minus 1) and the variance of each of the two groups by the sum of the degrees of freedom of the two groups statistic.

[0104] In an embodiment of the application, the T statistic is calculated as follows: , wherein is the T statistic in the two-sample independent T test, is the combined standard deviation ( );

[0105] 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 combined variance is calculated to integrate the variance information of the two groups; finally, the mean difference, the combined 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, providing a quantitative basis for the efficacy evaluation of the dominant diseases of traditional Chinese medicine.

[0106] The formula is the T statistic calculation formula in the two-sample independent T test. In the present 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 combined 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.

[0107] The medical insurance policy adaptation and settlement analysis module is used to realize the dynamic linkage of traditional Chinese medicine diseases and medical insurance policies, balance compliance and benefits;

[0108] In an embodiment of the 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.

[0109] The policy matching unit is used to compare the identified dominant diseases of traditional Chinese medicine with the medical insurance directory (regional dominant diseases of traditional Chinese medicine recommendation directory) and mark the diseases that can enjoy tilted payment (diseases with a 10% increase in payment ratio); track the update of medical insurance policies and automatically update the matching relationship between diseases and policies.

[0110] The DIP / DRG settlement analysis unit is used to calculate the medical insurance balance of traditional Chinese medicine diseases (medical insurance payment amount-disease cost) and identify the settlement mode.

[0111] 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).

[0112] The early warning unit is used for setting a medical insurance overspending risk threshold (actual cost exceeding 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.

[0113] The decision support and optimization module is used for generating resource configuration suggestions, and realizing dynamic optimization based on feedback;

[0114] 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;

[0115] The resource configuration unit is used for outputting resource adjustment suggestions for dominant diseases;

[0116] 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).

[0117] The path optimization unit optimizes the Chinese medicine diagnosis and treatment path based on the medical insurance surplus data and the efficacy evaluation results;

[0118] 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 pieces and Chinese patent medicines.

[0119] 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.

[0120] The additional function module is used for providing Chinese medicine diagnosis and treatment data depth management, cost and expense analysis and diagnosis and treatment path index evaluation functions;

[0121] In the embodiments of the present application, the additional function module includes a traditional 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;

[0122] The traditional Chinese medicine diagnosis and treatment data management and analysis unit is used for realizing standardized processing, deep analysis, and characteristic advantage mining of traditional Chinese medicine diagnosis and treatment data.

[0123] In the embodiments of the present application, the traditional Chinese medicine diagnosis and treatment data management and analysis unit includes a traditional Chinese medicine medical record input module, a traditional Chinese medicine diagnosis and treatment characteristic advantage module, a traditional Chinese medicine diagnosis and treatment path module, a traditional Chinese medicine doctor diagnosis and treatment characteristic module, and a traditional Chinese medicine treatment cost module.

[0124] The traditional Chinese medicine medical record input module is used for standardizing processing (such as unifying syndrome differentiation and classification term) of traditional Chinese medicine 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.

[0125] The traditional Chinese medicine diagnosis and treatment characteristic advantage module includes 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, and is used for outputting traditional Chinese medicine and Chinese medicine use conditions of the whole hospital / specialty / disease (such as traditional Chinese medicine special disease characteristic analysis and traditional Chinese medicine cost proportion change trend); and screening traditional Chinese medicine treatment advantage diseases through changes of VAS scores and curative effect indexes before and after diagnosis and treatment.

[0126] The traditional Chinese medicine diagnosis and treatment path module constructs diagnosis and treatment paths of traditional Chinese medicine special diseases and diagnosis diseases based on historical cases, analyzes curative effects and prescription conditions in path execution in real time, and dynamically updates path content (such as adjusting dosages of traditional Chinese medicine prescriptions).

[0127] The traditional Chinese medicine doctor diagnosis and treatment characteristic module identifies mainstream diseases, prescriptions and curative effects of doctors, compares traditional Chinese medicine diagnosis and treatment cost averages of the doctors with cost averages of the same diagnosis groups, analyzes cost proportions, and displays prescription preferences (such as high-frequency used traditional Chinese medicine decoctions) of the doctors based on diagnosis groups.

[0128] The traditional Chinese medicine treatment cost module is used for counting traditional Chinese medicine treatment costs of the whole hospital / specialty / doctor, screening traditional Chinese medicine characteristic advantage cases (traditional Chinese medicine treatment cost proportion ≥ preset threshold, curative effect rating is high, and cost average is not lower than disease average), and identifying traditional Chinese medicine characteristic advantage doctors (personal traditional Chinese medicine treatment cost proportion ≥ preset threshold).

[0129] The cost and expense analysis unit is used for realizing fine analysis of costs and expenses of departments and diseases and optimization of medical resources.

[0130] In the embodiments of the present application, the cost and expense analysis unit includes a department cost analysis module, a disease cost structure module, and a disease cost and DRG grouping module.

[0131] Department cost analysis module, for calculating the bed average score (DIP / DRG score / bed number) of the hospital department, analyzing the score difference of different departments; showing the cost structure of a single or all departments (proportion of manpower, consumables, equipment depreciation); correlation analysis of department cost structure and regional ranking, establishment of cost responsibility model, real-time monitoring of diagnosis cost, disease cost, bed average score, cost-benefit ratio.

[0132] Disease cost structure module, for showing the cost structure of DRG / DIP disease (proportion of drugs, consumables, examination, treatment) and regional comparison data; for the same disease, comparing the cost structure and cost-benefit ratio of regional benchmark hospitals to evaluate the reasonableness of their own cost; supporting disease cost regional ranking query and benchmark tracking, outputting medical resource optimization scheme (such as reducing the procurement cost of high proportion of consumables).

[0133] Disease cost and DRG grouping module, for providing the cost structure under DRG grouping (outpatient / hospitalization cost proportion) and the cost average of each grouping; analyzing the regional ranking of each disease grouping cost of the hospital; for a single disease, showing the grouping cost average, structure and regional benchmark cost structure, providing basis for cost control.

[0134] Diagnosis and treatment path index evaluation unit, for real-time updating the efficacy of clinical path and traditional Chinese medicine diagnosis and treatment path according to prescription drug use, examination items, and efficacy, outputting efficacy rating (based on VAS / ADL score grading table), providing basis for path optimization.

[0135] Example two: taking "lumbar disc herniation" as a candidate for traditional Chinese medicine advantage disease, and focusing on the core indicators of each module:

[0136] I. Data collection and storage module test data;

[0137] 1. Internal data;

[0138] HIS system: Traditional Chinese medicine diagnosis and treatment data (200 times of acupuncture, 150 prescriptions of traditional Chinese medicine);

[0139] Medical record system: ICD-10 code M51.2, TCD-0502 code of traditional Chinese medicine disease;

[0140] Financial system: single disease cost 7500 yuan (3000 yuan for manpower, 1500 yuan for consumables);

[0141] Human resources: 8 traditional Chinese medicine doctors and 12 nurses in the department.

[0142] 2. External data;

[0143] Medical insurance DIP data: disease score 800 points, payment standard 8000 yuan, grouping rule (main diagnosis + traditional Chinese medicine treatment proportion ≥ 50%);

[0144] Medical insurance policy: increase the payment ratio of TCM advantage diseases by 10% (original 80%→90%).

[0145] 3. Store information;

[0146] Structured data: cost accounting table (Excel), coding mapping table (TCM disease TCD-0502→ICD-10 M51.2);

[0147] Unstructured data: TCM diagnosis and treatment plan text ("traction + moxibustion + Duhuo Jisheng Decoction"); encrypted privacy data: patient ID number (AES encrypted storage), medical record details.

[0148] Second, the test data of the TCM advantage disease identification module;

[0149] 1. The cure rate calculation unit;

[0150] Total cases 100; TCM treatment cost accounted for 60 cases (TCM treatment cost 4200 yuan, total cost 7000 yuan); the cure rate was 60% (60 / 100);

[0151] 2. Disease stratification unit;

[0152] CMI value is 2.0 (higher than 1.8); ASIP (average per unit surplus) is 500 yuan (8000 yuan of medical insurance payment-7500 yuan of cost); disease type is advantage disease (CMI>1.8 and ASIP>0);

[0153] 3. Efficacy evaluation unit;

[0154] (1) TCM treatment group (50 cases);

[0155] VAS score: 7.5±1.2 before treatment, 3.0±0.8 after treatment (decrease 4.5±0.5);

[0156] ADL score: 50±8 before treatment, 80±5 after treatment (increase 30±3).

[0157] (2) Western medicine treatment group (50 cases);

[0158] VAS score: 7.3±1.0 before treatment, 4.3±0.9 after treatment (decrease 3.0±0.6);

[0159] ADL score: 52±7 before treatment, 72±6 after treatment (increase 20±2).

[0160] (3) T test results: P<0.05 (TCM group is significantly better than western medicine group);

[0161] Three, medical insurance policy adaptation and settlement analysis module test data;

[0162]

[0163] Table 1 medical insurance policy adaptation and settlement analysis module test data table

[0164] Four, decision support and optimization module test data;

[0165]

[0166] Table 2 decision support and optimization module test data table

[0167] Five, additional function module test data (part of the core indicators);

[0168]

[0169] Table 3 additional function module test data table

[0170] Conclusion: Based on the whole process analysis process 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 actual operation scene of the hospital is simulated. 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 adaptation, 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 improvement of TCM group VAS score is better than that of western medicine group), but also optimize the medical insurance settlement income (realize the clear and real profit), and promote the improvement of department operation efficiency (the proportion of advantage diseases increases by 5%, and the medical insurance surplus rate increases 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.

[0171] The embodiments of the present application are disclosed, but are not limited to this, and those 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, they 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. It includes a data standardization unit, which is used to unify data standards by establishing a mapping relationship between TCM diseases and ICD-10 codes and formulating cost accounting rules. The TCM Advantage Disease Identification Module is used to quantitatively define TCM advantage diseases based on data elements, including: 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. The medical insurance policy adaptation and settlement analysis module is used to achieve dynamic linkage between TCM diseases and medical insurance policies, including: 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. 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 also includes a data cleaning unit and a security management unit: 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 classification of disease types using the Boston Matrix specifically includes: dominant diseases: and ; Development of disease categories: and Potential diseases: and Diseases requiring optimization: and .

5. A hospital operation decision analysis system based on data element-driven approach 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.

6. 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.

7. A hospital operation decision analysis system based on data elements as described in claim 6, 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.

8. A hospital operation decision analysis system based on data element-driven approach according to claim 7, 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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