CN112652389A - Fee control method based on DRGs pre-grouping - Google Patents
Fee control method based on DRGs pre-grouping Download PDFInfo
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- CN112652389A CN112652389A CN202110068433.0A CN202110068433A CN112652389A CN 112652389 A CN112652389 A CN 112652389A CN 202110068433 A CN202110068433 A CN 202110068433A CN 112652389 A CN112652389 A CN 112652389A
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/40—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
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- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/08—Payment architectures
- G06Q20/10—Payment architectures specially adapted for electronic funds transfer [EFT] systems; specially adapted for home banking systems
- G06Q20/102—Bill distribution or payments
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Abstract
The invention discloses a fee control method based on DRGs pre-grouping, which comprises the following steps: 1) data integration: acquiring data from a hospital hospitalization clinical system by adopting a charge control system; 2) predicting, by the in-hospital grouper, a grouping; 3) predicting cost and hospitalization days according to medical insurance historical settlement data; 4) obtaining the DRG average charge and the average hospitalization days in the last month area through a medical insurance computing platform; 5) early warning in real time; 6) DRG balance statistical analysis; 7) monitoring the charge control state: the variation trend of the hospital hospitalization cost increase, the medicine ratio, the actual compensation ratio and the self-fee project cost ratio. The invention is based on the pre-grouping technology, extends to the diagnosis and treatment process of doctors, has higher real-time performance, can manually specify the grouping when the main doctors disagree with the prediction grouping, completes the calculation of real-time cost and expense, can predict the hospitalization expense and cost factor in real time, and is used for hospitals to better adapt to the DRG medical insurance payment mode of the grouping related to the disease diagnosis.
Description
Technical Field
The invention belongs to the technical field of information, and particularly relates to a fee control method based on DRGs pre-grouping.
Background
The current information system of the public hospital in China cannot adapt to a DRG payment mode, and if no good charge control method is available, the hospital can only passively bear heavier and heavier cost pressure. How to design a charge control method suitable for a DRG medical insurance payment mode can adapt to the new situation of medical improvement, and various puzzles brought by the DRG medical insurance payment mode are solved, which becomes a difficult problem of modern hospital management.
The disadvantages of the prior art are as follows:
1. there is no in-hospital grouper;
2. the hospital can only check the amount settled by the DRGs for the medical insurance afterwards (the settlement data of the medical insurance can be fed back to the hospital in the next month);
3. and the medical insurance settlement data cannot be effectively counted and analyzed.
Disclosure of Invention
In order to solve the defects and shortcomings in the prior art, the invention provides a fee control method based on DRGs pre-grouping, which is based on a pre-grouping technology, is extended to the diagnosis and treatment process of doctors, has higher real-time performance, can manually specify grouping when the main doctors give objections to prediction grouping, completes the calculation of real-time cost and cost, can predict hospitalization cost and cost elements in real time, and is used for hospitals to better adapt to a DRG medical insurance payment mode according to relevant groups of disease diagnosis.
The technical scheme of the invention is as follows: a fee control method based on DRGs pre-grouping comprises the following steps:
1) data integration: acquiring data from a hospital hospitalization clinical system by adopting a charge control system;
2) predicting, by the in-hospital grouper, a grouping;
3) predicting cost and hospitalization days according to medical insurance historical settlement data;
4) obtaining the DRG average charge and the average hospitalization days in the last month area through a medical insurance computing platform;
5) real-time early warning: DRG in the exceeding area is charged, the cost of two days after the operation is too low, the cost of half the hospitalization days is too low, the medical expense accounts for too high, the medical record is early-warned, and the attending physician/medical team member is notified through a short message or other message system;
6) DRG balance statistical analysis: department balance analysis, doctor balance analysis, DRG disease group balance analysis and main reason analysis of overdraft;
7) monitoring the charge control state: the variation trend of the hospital hospitalization cost increase, the medicine ratio, the actual compensation ratio and the self-fee project cost ratio.
The invention is based on the pre-grouping technology, extends to the diagnosis and treatment process of doctors, has higher real-time performance, can manually specify the grouping when the main doctors disagree with the prediction grouping, completes the calculation of real-time cost and expense, can predict the hospitalization expense and cost factor in real time, and is used for hospitals to better adapt to the DRG medical insurance payment mode of the grouping related to the disease diagnosis.
Preferably, the front end and the back end of the fee control system in the step 1) are separated, the front end adopts a new generation of Web-based cross-platform desktop technology Electron, and the installation and use of Windows, Mac and Linux systems are supported; the back-end service adopts a micro-service architecture, which is convenient for big data analysis and processing.
Preferably, the fee control system in the step 1) is integrated with the EMR electronic medical record system to acquire the data state in real time, and the attending physician is informed of the problem found in the diagnosis and treatment process of the physician.
Preferably, the data acquired from the hospital in-patient clinical system in step 1) includes basic patient information, cost information, main diagnosis information and operation information.
Preferably, the in-hospital grouper in the step 2) adopts a CHS-DRG grouper, so that the result is closer to the result of the medical insurance computing platform, and the prediction grouping is more accurate.
Preferably, the cost information is subjected to big data analysis according to a historical medical insurance statement, and the predicted cost is more accurate to the number of hospitalization days.
Preferably, the calculation of the average hospital cost adds CMI-CMI adjusted average hospital cost increase (average cost of hospital in this year/CMI in this year)/(average cost of hospital in last year/CMI in last year).
The invention is based on the pre-grouping technology, extends to the diagnosis and treatment process of doctors, has higher real-time performance, can manually specify the grouping when the main doctors disagree with the prediction grouping, completes the calculation of real-time cost and expense, can predict the hospitalization expense and cost factor in real time, and is used for hospitals to better adapt to the DRG medical insurance payment mode of the grouping related to the disease diagnosis.
Detailed Description
The present invention is further illustrated in detail by the following examples, which are not intended to limit the scope of the invention.
Examples
A fee control method based on DRGs pre-grouping comprises the following steps:
1) data integration: acquiring data from a hospital hospitalization clinical system by adopting a charge control system;
2) predicting, by the in-hospital grouper, a grouping;
3) predicting cost and hospitalization days according to medical insurance historical settlement data;
4) obtaining the DRG average charge and the average hospitalization days in the last month area through a medical insurance computing platform;
5) real-time early warning: DRG in the exceeding area is charged, the cost of two days after the operation is too low, the cost of half the hospitalization days is too low, the medical expense accounts for too high, the medical record is early-warned, and the attending physician/medical team member is notified through a short message or other message system;
6) DRG balance statistical analysis: department balance analysis, doctor balance analysis, DRG disease group balance analysis and main reason analysis of overdraft;
7) monitoring the charge control state: the variation trend of the hospital hospitalization cost increase, the medicine ratio, the actual compensation ratio and the self-fee project cost ratio.
The front end and the back end of the charge control system in the step 1) are separated, and the front end adopts a new generation of Web-based cross-platform desktop technology Electron to support the installation and use of Windows, Mac and Linux systems; the back-end service adopts a micro-service architecture, which is convenient for big data analysis and processing.
The charge control system in the step 1) and the EMR electronic medical record system are integrated to acquire the data state in real time, and a doctor is informed of a problem in the diagnosis and treatment process.
The data acquired from the hospital clinical system in step 1) comprises basic information of patients, cost information, main diagnosis information and operation information.
The nosocomial grouter in the step 2) adopts a CHS-DRG grouter, so that the result is closer to the result of a medical insurance computing platform, and the prediction grouping is more accurate.
The expense information is subjected to big data analysis according to a historical medical insurance settlement list, and the expense prediction and the hospitalization days are more accurate.
CMI is added in the calculation of the average hospitalization cost, and the CMI adjusted increase of the average hospitalization cost is (average hospitalization cost in the current year/CMI in the current year)/(average hospitalization cost in the last year/CMI in the last year).
The main innovation points of the invention are as follows:
1. the grouping device is based on CHS-DRG standard issued by the national medical insurance bureau;
2. supporting in-hospital localization deployment and cloud SAAS mode deployment;
3. real-time prediction of DRG groupings and costs for medical records;
4. monitoring and alarming abnormal medical records of hospitalization;
5. comparing and analyzing the prediction group and the medical insurance actual group;
6. comparing and analyzing the predicted cost and the actual settlement cost of the medical insurance;
and 7, performing statistical analysis on balance of medical insurance settlement by the DRG.
Claims (7)
1. A fee control method based on DRGs pre-grouping is characterized in that: the method comprises the following steps:
data integration: acquiring data from a hospital hospitalization clinical system by adopting a charge control system;
predicting, by the in-hospital grouper, a grouping;
predicting cost and hospitalization days according to medical insurance historical settlement data;
obtaining the DRG average charge and the average hospitalization days in the last month area through a medical insurance computing platform;
real-time early warning: DRG in the exceeding area is charged, the cost of two days after the operation is too low, the cost of half the hospitalization days is too low, the medical expense accounts for too high, the medical record is early-warned, and the attending physician/medical team member is notified through a short message or other message system;
DRG balance statistical analysis: department balance analysis, doctor balance analysis, DRG disease group balance analysis and main reason analysis of overdraft;
monitoring the charge control state: the variation trend of the hospital hospitalization cost increase, the medicine ratio, the actual compensation ratio and the self-fee project cost ratio.
2. The method of claim 1 for controlling charges based on DRGs pre-packets, wherein: the front end and the back end of the charge control system in the step 1) are separated, and the front end adopts a new generation of Web-based cross-platform desktop technology Electron to support the installation and use of Windows, Mac and Linux systems; the back-end service adopts a micro-service architecture, which is convenient for big data analysis and processing.
3. The method of claim 1 for controlling charges based on DRGs pre-packets, wherein: the charge control system in the step 1) and the EMR electronic medical record system are integrated to acquire the data state in real time, and a doctor is informed of a problem in the diagnosis and treatment process.
4. The method of claim 1 for controlling charges based on DRGs pre-packets, wherein: the data acquired from the hospital clinical system in step 1) comprises basic information of patients, cost information, main diagnosis information and operation information.
5. The method of claim 1 for controlling charges based on DRGs pre-packets, wherein: the nosocomial grouter in the step 2) adopts a CHS-DRG grouter, so that the result is closer to the result of a medical insurance computing platform, and the prediction grouping is more accurate.
6. The method of claim 1 for controlling charges based on DRGs pre-packets, wherein: the expense information is subjected to big data analysis according to a historical medical insurance settlement list, and the expense prediction and the hospitalization days are more accurate.
7. The method of claim 5 in which the DRGs pre-packet based fee control method comprises: calculating the average hospitalization cost of the times, and adding CMI, wherein the CMI adjusted average hospitalization cost is increased = (average hospitalization cost of the year/CMI of the year)/(average hospitalization cost of the last year/CMI of the last year).
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Cited By (3)
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|---|---|---|---|---|
| CN113903437A (en) * | 2021-09-26 | 2022-01-07 | 北京思普科软件股份有限公司 | Management analysis system for disease control fee |
| CN115910308A (en) * | 2023-01-05 | 2023-04-04 | 中南大学湘雅医院 | Expense fine control method and device under DRG system, and electronic equipment |
| CN116563038A (en) * | 2023-06-26 | 2023-08-08 | 江南大学附属医院 | Medical insurance fee control recommendation method, system and storage medium based on regional big data |
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Cited By (4)
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Application publication date: 20210413 |