DRG / DIP operation risk management intelligent monitoring index system

Abstract

The invention discloses a DRG / DIP operation risk management intelligent monitoring index system, and belongs to the technical field of hospital operation management. A data processing layer; an index calculation layer; an analysis early warning layer; a display layer; the data acquisition layer collects related data from a plurality of data sources, the data processing layer performs data processing, the index calculation layer presets a medical insurance payment operation risk management intelligent monitoring index system, and the analysis early warning layer analyzes each index value obtained by calculation, judges whether a risk point exists or not, and gives an early warning to the medical insurance payment operation risk management intelligent monitoring index system. The display layer displays an analysis early warning result to a user in the form of a visual chart, a report and the like, data can be collected and analyzed in real time, risk points in the medical insurance payment operation process can be found in time, accumulation and expansion of risks are avoided, a manager can quickly understand and master the risk condition of medical insurance payment operation conveniently, and decision-making efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of hospital operation management, and in particular relates to a DRG / DIP operation risk management intelligent monitoring indicator system. Background Art

[0002] DRG is a method of comprehensively grouping hospitalized patients according to factors such as disease diagnosis, treatment method, age, gender, and discharge outcomes; DIP is a disease-based scoring payment method based on big data.

[0003] At present, the management of the medical insurance department is unable to fully understand the overall situation of medical insurance payment operations, and is unable to promptly discover problems in medical institutions in terms of medical insurance reimbursement, diagnosis and treatment services, etc. Medical institution operations are unable to understand their own risk status in medical insurance payment. Summary of the invention

[0004] The purpose of the present invention is to propose a DRG / DIP operational risk management intelligent monitoring indicator system in order to solve the above-mentioned problems.

[0005] In order to achieve the above purpose, the present invention adopts the following technical solution: a DRG / DIP operational risk management intelligent monitoring indicator system, which includes:

[0006] The data collection layer is responsible for collecting relevant data from multiple data sources, including the information systems of medical institutions, the management systems of medical insurance departments, and other relevant third-party data platforms;

[0007] The data processing layer cleans, converts, and standardizes the collected raw data;

[0008] The indicator calculation layer calculates indicators for the processed data according to the pre-set intelligent monitoring indicator system for medical insurance payment operation risk management;

[0009] The analysis and early warning layer analyzes the calculated indicator values ​​to determine whether there are risk points;

[0010] The display layer displays the results of the analysis and early warning to users in the form of intuitive charts, reports, etc.

[0011] As a further description of the above technical solution:

[0012] The indicator calculation layer calculates cost-related indicators: Medical insurance expense growth rate = (total medical insurance expenses in this period - total medical insurance expenses in the previous period) ÷ total medical insurance expenses in the previous period × 100%; average medical insurance expense per visit = total medical insurance expenses ÷ number of visits; medical insurance expense structure ratio = a certain type of expense ÷ total medical insurance expenses × 100%.

[0013] As a further description of the above technical solution:

[0014] The indicator calculation layer calculates the medical service quality indicators: cure rate = number of cured and discharged patients ÷ total number of discharged patients × 100%; complication rate = number of patients with complications ÷ total number of discharged patients × 100%.

[0015] As a further description of the above technical solution:

[0016] The indicator calculation layer calculates the medical insurance compliance indicators: medical insurance reimbursement ratio = medical insurance reimbursement amount ÷ total medical expenses that meet the medical insurance reimbursement conditions × 100%; medical insurance violation incidence rate = number of violations ÷ total number of medical insurance reimbursements × 100%.

[0017] As a further description of the above technical solution:

[0018] The indicator calculation layer calculates the medical institution operation indicators: medical staff turnover rate = number of medical staff who have resigned ÷ total number of medical staff × 100%; bed utilization rate = actual number of beds in use ÷ number of beds set up in the hospital × 100%.

[0019] As a further description of the above technical solution:

[0020] The indicator calculation layer calculates the medical insurance policy implementation indicators: Medical insurance policy awareness rate = number of people who know the medical insurance policy ÷ total number of people surveyed × 100%; Medical insurance policy adjustment response rate = the number of times medical institutions adjust their diagnosis and treatment behaviors, charging standards, etc. in accordance with the new medical insurance policy ÷ the number of times that should be adjusted × 100%.

[0021] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0022] In the present invention, relevant data are collected from multiple data sources through the data acquisition layer, the data processing layer performs data processing, the indicator calculation layer pre-sets the intelligent monitoring indicator system for medical insurance payment operation risk management, the analysis and early warning layer analyzes the calculated indicator values ​​to determine whether there are risk points, and the display layer analyzes and warns the results of the warning in the form of intuitive charts, reports, etc. to display users, which can collect and analyze data in real time, timely discover risk points in the medical insurance payment operation process, avoid the accumulation and expansion of risks, and facilitate managers to quickly understand and grasp the risk status of medical insurance payment operations and improve decision-making efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is a system block diagram of a DRG / DIP operational risk management intelligent monitoring indicator system. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] Example:

[0026] The data collection layer is responsible for collecting relevant data from multiple data sources, including the information systems of medical institutions, the management systems of medical insurance departments, and other relevant third-party data platforms. The types of data collected include basic patient information, medical records, medical expense details, medical insurance reimbursement information, medical institution operation data, etc. It usually uses data interfaces and data extraction tools to connect with various data sources and obtain data to ensure the accuracy and completeness of the data. For example, through the standard interface with the HIS system of the medical institution, the patient's medical information and cost data are extracted regularly;

[0027] The data processing layer cleans, converts, and standardizes the collected raw data. Cleaning data is to remove erroneous data, duplicate data, and incomplete data; converting data is to unify data in different formats into a format that is easy to analyze, such as unifying the date format; standardizing data means normalizing some indicator data to facilitate comparison and analysis on the same scale, using data cleaning tools (such as OpenRefine, etc.), data conversion scripts (such as Python scripts, etc.), and data standardization algorithms (such as Z-score standardization algorithm, etc.) to complete the corresponding processing tasks;

[0028] The indicator calculation layer calculates the indicators of the processed data according to the pre-set intelligent monitoring indicator system for risk management of medical insurance payment operations. According to the calculation formula of average medical insurance cost per visit (total medical insurance cost ÷ number of visits), the average medical insurance cost per visit indicator value is calculated using the processed total medical insurance cost data and the number of visits data. The indicator calculation logic is implemented by writing program codes (such as Java, Python and other programming languages), and the calculation results are stored in the database for subsequent analysis and display.

[0029] The calculations include:

[0030] The indicator calculation layer calculates cost-related indicators: medical insurance expense growth rate = (total medical insurance expense of this period - total medical insurance expense of the previous period) ÷ total medical insurance expense of the previous period × 100%; average medical insurance expense per visit = total medical insurance expense ÷ number of visits; medical insurance expense structure ratio = a certain type of expense ÷ total medical insurance expense × 100%;

[0031] The indicator calculation layer calculates the medical service quality indicators: cure rate = number of cured and discharged patients ÷ total number of discharged patients × 100%; complication rate = number of patients with complications ÷ total number of discharged patients × 100%;

[0032] The indicator calculation layer calculates the medical insurance compliance indicator: medical insurance reimbursement ratio = medical insurance reimbursement amount ÷ total medical expenses that meet the medical insurance reimbursement conditions × 100%; medical insurance violation behavior incidence rate = number of violations ÷ total number of medical insurance reimbursements × 100%;

[0033] The indicator calculation layer calculates the operating indicators of medical institutions: medical staff turnover rate = number of medical staff who have resigned ÷ total number of medical staff × 100%; bed utilization rate = actual number of beds in use ÷ number of beds set up in the hospital × 100%;

[0034] The indicator calculation layer calculates the medical insurance policy implementation indicators: Medical insurance policy awareness rate = number of people who know the medical insurance policy ÷ total number of people surveyed × 100%; Medical insurance policy adjustment response rate = the number of times medical institutions adjust diagnosis and treatment behaviors, charging standards, etc. according to the new medical insurance policy ÷ the number of times that should be adjusted × 100%;

[0035] The analysis and early warning layer analyzes the calculated values ​​of various indicators to determine whether there are risk points and sets an upper threshold for the average medical insurance cost per visit. When the calculated average medical insurance cost per visit exceeds the threshold, it is determined that there is a potential risk. At the same time, the corresponding early warning information is generated based on the analysis results, and relevant personnel (such as medical insurance managers, medical institution managers, etc.) are notified in a timely manner to take measures. Data analysis software (such as Tableau, PowerBI, etc.) is used for visual analysis, and the early warning logic is implemented by writing rule engine code (such as Drools, etc.), and early warning information is sent through SMS platforms, email systems, etc.;

[0036] The display layer displays the results of analysis and warning to users in the form of intuitive charts and reports, so that they can quickly understand the risk status of medical insurance payment operations. The displayed content may include the real-time values, historical trends, and risk warning information of various monitoring indicators. It uses visualization tools (such as Echarts, Highcharts, etc.) to create various charts (such as bar charts, line charts, pie charts, etc.), and generates detailed reports through report generation tools (such as JasperReports, BIRT, etc.) and displays them on the web or mobile terminal.

[0037] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A DRG / DIP operational risk management intelligent monitoring indicator system, characterized by: include: The data collection layer is responsible for collecting relevant data from multiple data sources, including the information systems of medical institutions, the management systems of medical insurance departments, and other relevant third-party data platforms; The data processing layer cleans, converts, and standardizes the collected raw data; The indicator calculation layer calculates indicators for the processed data according to the pre-set intelligent monitoring indicator system for medical insurance payment operation risk management; The analysis and early warning layer analyzes the calculated indicator values ​​to determine whether there are risk points; The display layer displays the results of the analysis and early warning to users in the form of intuitive charts, reports, etc.

2. According to claim 1, a DRG / DIP operational risk management intelligent monitoring indicator system is characterized in that: The indicator calculation layer calculates cost-related indicators: Medical insurance expense growth rate = (total medical insurance expenses in this period - total medical insurance expenses in the previous period) ÷ total medical insurance expenses in the previous period × 100%; average medical insurance expense per visit = total medical insurance expenses ÷ number of visits; medical insurance expense structure ratio = a certain type of expense ÷ total medical insurance expenses × 100%.

3. According to claim 1, a DRG / DIP operational risk management intelligent monitoring indicator system is characterized in that: The indicator calculation layer calculates the medical service quality indicators: cure rate = number of cured and discharged patients ÷ total number of discharged patients × 100%; complication rate = number of patients with complications ÷ total number of discharged patients × 100%.

4. According to claim 1, a DRG / DIP operational risk management intelligent monitoring indicator system is characterized in that: The indicator calculation layer calculates the medical insurance compliance indicators: medical insurance reimbursement ratio = medical insurance reimbursement amount ÷ total medical expenses that meet the medical insurance reimbursement conditions × 100%; medical insurance violation incidence rate = number of violations ÷ total number of medical insurance reimbursements × 100%.

5. According to claim 1, a DRG / DIP operational risk management intelligent monitoring indicator system is characterized in that: The indicator calculation layer calculates the medical institution operation indicators: medical staff turnover rate = number of medical staff who have resigned ÷ total number of medical staff × 100%; bed utilization rate = actual number of beds in use ÷ number of beds set up in the hospital × 100%.

6. A DRG / DIP operational risk management intelligent monitoring indicator system according to claim 1, characterized in that: The indicator calculation layer calculates the medical insurance policy implementation indicators: Medical insurance policy awareness rate = number of people who know the medical insurance policy ÷ total number of people surveyed × 100%; Medical insurance policy adjustment response rate = the number of times medical institutions adjust their diagnosis and treatment behaviors, charging standards, etc. in accordance with the new medical insurance policy ÷ the number of times that should be adjusted × 100%.

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