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Medical insurance fee control method and system based on abnormity detection algorithm

An anomaly detection and algorithm technology, applied in the field of Internet services, can solve problems such as failure to control fees, control, and inability to detect abnormal situations, and achieve the effect of effective medical insurance fee control

Pending Publication Date: 2021-05-04
BEIJING UNISOUND INFORMATION TECH +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the actual medical process, doctors use various diagnostic names, drug names, and treatment service names, and it is impossible to completely agree with the standard names issued by the Medical Insurance Bureau in terms of expression.
This caused the failure of the matching scheme in the form of regular expressions and dictionaries, and then the abnormal situation could not be found, and the fee control failed
At the same time, the fee control rules issued by the Medical Insurance Bureau are limited and fixed (for a period of time), but the unreasonable medical behaviors of fraudulent insurance are diverse and changing
As a result, the fee control rules of the Medical Insurance Bureau can only regulate limited unreasonable medical behaviors, and it is impossible to control all unreasonable medical behaviors

Method used

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  • Medical insurance fee control method and system based on abnormity detection algorithm
  • Medical insurance fee control method and system based on abnormity detection algorithm
  • Medical insurance fee control method and system based on abnormity detection algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0025] as attached figure 1 As shown, the present invention provides a method for controlling medical insurance expenses based on an abnormality detection algorithm, comprising the following steps:

[0026] S1. Process the medical record data text to obtain the vector mapping of the entity;

[0027] S2. According to the vector mapping of the entity, perform connotative consistency aggregation on all main diagnoses in the case data, and divide all medical record data into N groups (N>1) according to the main diagnosis;

[0028] S3. Perform entity vector screening on the grouped cases, and run the LOF algorithm on each group of case data to obtain a set of abnormal medical behaviors.

[0029] Further, the step S1 includes:

[0030] S101. Obtain large-scale electronic medical record text data;

[0031] Preferably, the electronic case text data is more than 10 million copies;

[0032] S102. Run the medical NER algorithm on the electronic medical record text, extract the medica...

Embodiment 2

[0075] as attached Figure 4 As shown, the present invention also provides a medical insurance fee control system based on an abnormality detection algorithm, including:

[0076] The data processing module processes the text of the medical record data to obtain the vector mapping of the entity;

[0077] The data aggregation module, according to the vector mapping of the entity, performs connotative consistency aggregation on all main diagnoses in the case data, and divides all medical record data into N groups (N>1) according to the main diagnosis;

[0078] The data screening module performs entity vector screening on the grouped cases, runs the LOF algorithm on each group of case data, and obtains a set of abnormal medical behaviors.

[0079] Further, the data processing module also includes:

[0080] Case data acquisition module, to acquire large-scale electronic medical record text data;

[0081] The entity acquisition module runs a medical NER algorithm on the electroni...

Embodiment 3

[0097] A system installed with an application program according to an embodiment of the present invention.

[0098] refer to Figure 6 , which shows the operating environment of the system installed with the application program according to the embodiment of the present invention. In this embodiment, the system for installing application programs is installed and runs in the electronic device. The electronic device may be a computing device such as a desktop computer, a notebook, a palmtop computer, or a server. The electronic device may include, but is not limited to, memory, processor, and display. The drawings only show an electronic device having the components described above, but it should be understood that implementation of all of the illustrated components is not required and that more or fewer components may instead be implemented.

[0099] In some embodiments, the memory may be an internal storage unit of the electronic device, such as a hard disk or a memory of ...

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Abstract

The invention relates to a medical insurance fee control method and system based on an abnormity detection algorithm. The method comprises the steps: processing a medical record data text to obtain a vector mapping of an entity; according to the vector mapping of the entity, performing connotation consistency aggregation on all the main diagnoses in the case data, and dividing all the case data into N groups (N being greater than 1) according to the main diagnoses; and performing entity vector screening on the grouped cases, and running an LOF algorithm on each group of case data to obtain an abnormal medical behavior set. According to the method, the thought of big data is utilized, the abnormal medical behaviors in the medical process are found through the abnormity detection technology, and then medical insurance fee control can be carried out on the unreasonable behaviors.

Description

technical field [0001] The invention relates to the technical field of Internet services, in particular to a medical insurance fee control method and system based on an abnormality detection algorithm. Background technique [0002] With the large-scale implementation of the national medical insurance, patients can use the national medical insurance to see a doctor and be hospitalized, so as to realize the reimbursement of medical expenses. But it is undeniable that there is a considerable amount of medical insurance fraud in the society at present, and the existing technology lacks effective scientific identification means for medical insurance fraud, which seriously affects the balance of income and expenditure of the medical insurance fund and violates the interests of the majority of insured people. Therefore, the risk review of medical insurance is an indispensable part of medical insurance reimbursement. Among them, the cost of medicines accounts for a high proportion ...

Claims

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Application Information

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IPC IPC(8): G06Q40/08G06F40/295G16H10/60
CPCG06Q40/08G06F40/295G16H10/60
Inventor 王晔晗刘升平梁家恩
Owner BEIJING UNISOUND INFORMATION TECH
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