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Method for detecting abnormal hospitalized personnel based on threshold screening and condition exclusion
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A detection method and personnel technology, applied in the field of medical artificial intelligence, which can solve the problems of single indicator, misjudgment, and inability to measure abnormal hospitalization behaviors well.
Inactive Publication Date: 2021-06-22
SHANDONG IND TECH RES INST OF ZHEJIANG UNIV
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There are some problems with this method: 1) The index is too single, including only the cost index, which cannot measure the abnormal inpatient behavior well; 2) Screening the abnormal inpatients according to the threshold value may cause misjudgment
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Embodiment 1
[0039] Embodiment 1, a method for detecting abnormal hospitalized persons based on threshold screening and condition exclusion, comprising the following steps:
[0040] S1. Set indicators for threshold screening according to abnormal hospitalization conditions, wherein the indicators include cost indicators, time indicators and age indicators.
[0041] Specifically, the cost indicators include the proportion of drug expenses for a single hospitalization, the proportion of inspection and testing fees for a single hospitalization, the total cost of a single hospitalization, and the average daily cost of a single hospitalization;
[0042] The time index includes at least the number of days of single hospitalization and the number of hospitalizations per year;
[0043] The age index is the age of the inpatients.
[0044] S2. Group the hospitalization record data according to the type of hospitalization, and analyze the data of each group to obtain the corresponding threshold valu...
Embodiment 2
[0054] Embodiment 2, take medical examination type hospitalization as an example.
[0055] S1. Group hospitalization record data by hospital type, and sort out personal hospitalization information:
[0056]Hospitalization record data includes the following fields: fixed-point medical institution code, medical serial number, personal number, name, gender, age, drug, item code, type of charging item, name of hospital charging item, charging category, unit price, quantity, amount, medical expenses Total amount, self-pay amount, self-care expenses, total reimbursement amount, date of admission, date of discharge, type of designated institution, type of profit, classification code of designated institution.
[0057] The inpatient data are divided into four groups according to the type of hospital: public hospitals, community hospitals, private hospitals and other private hospitals.
[0058] In each set of data, personal hospitalization information is aggregated and sorted out, inc...
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Abstract
The invention belongs to the technical field of medical artificial intelligence, and particularly relates to a method for detecting abnormal hospitalized personnel based on threshold screening and condition elimination. The method for detecting the abnormal hospitalization personnel based on threshold value screening and condition exclusion comprises the following steps: S1, setting an index for threshold value screening according to an abnormal hospitalization condition; s2, grouping the hospitalization record data according to the hospitalization type, and analyzing each group of data to obtain a corresponding threshold value of the index in the step S1; s3, screening the hospitalization record data according to the index threshold obtained in the step S2 to obtain suspicious persons with abnormal hospitalization; and S4, setting exclusion conditions of normal persons with abnormal hospitalization under special conditions, and obtaining a final list of abnormal hospitalization persons. The invention aims to solve the technical problem of abnormal hospitalization in the field of medical insurance, and provides a method for detecting abnormal hospitalization personnel based on threshold screening and condition elimination.
Description
technical field [0001] The invention belongs to the technical field of medical artificial intelligence, and in particular relates to a method for detecting abnormal hospitalized persons based on threshold screening and condition exclusion. Background technique [0002] With the continuous improvement of the medical insurance system and the continuous expansion of medical insurance coverage, the normal operation of the medical insurance fund has been closely related to the vital interests of the people. However, in the actual operation of the medical insurance fund, there are a large number of medical insurance fraudulent behaviors, which greatly threaten the normal operation of the medical insurance fund. Abnormal hospitalization is an important manifestation of medical insurance fraud. [0003] Abnormal hospitalization mainly has three scenarios: physical examination-style hospitalization, drug-style hospitalization, and medical care-style hospitalization. Its characteris...
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