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Estimating medical expenditures spent on rule-out diagnoses in Japan
Shinichi Tanihara1, Etsuji Okamoto, Hiroshi Une
1Department of Hygiene and Preventive Medicine, School of Medicine, Fukuoka University, Fukuoka, Japan. taniyan@cis.fukuoka-u.ac.jp
Insights
Rule-out diagnoses significantly impact medical expenditure calculations in Japan. Incorporating this data improves estimations for disease-specific costs and healthcare program evaluations.
Area of Science:
- Health Economics
- Medical Informatics
- Public Health Policy
Background:
- Japan's health insurance system mandates including rule-out diagnoses in claims for reimbursement.
- Conventional medical expenditure estimations overlook the financial impact of rule-out diagnoses.
Purpose of the Study:
- To estimate disease-specific medical expenditure, specifically accounting for rule-out diagnoses.
Main Methods:
- Utilized outpatient health insurance claims (HICs) data from corporate health insurance societies.
- Applied the proportional distribution method to allocate expenditure across disease categories based on the International Statistical Classification of Diseases and Related Health Problems, 10th Revision.
Main Results:
- Rule-out diagnoses represented 4.60% of total diagnoses and 8.5% of total medical expenditure.
- Expenditure on rule-out diagnoses varied by disease category, notably comprising 36.9% of neoplasm-related medical costs.
Conclusions:
- Rule-out diagnoses are critical for accurate disease-specific medical expenditure estimation.
- Integrating rule-out diagnosis data enhances the evaluation of prevention and treatment programs.
Background:
According to the regulations concerning reimbursement rules for the uniform coverage scheme in Japan's health insurance system, rule-out diagnoses must be included in a health insurance claim (HIC) to ensure reimbursement for clinical procedures whose results show that a suspected disease is not present. However, estimations of disease-specific medical expenditure by conventional methods have not considered the information on rule-out diagnoses.
Objectives:
To estimate disease-specific medical expenditure for rule-out diagnoses.
Methods:
Data were obtained from 169,622 outpatient HICs in May 2006 from corporate health insurance societies. We used the proportional distribution method to estimate medical expenditure for each of the major disease categories defined by the Classification of Diseases for the use of Social Insurance, which is based on the International Statistical Classification of Diseases and Related Health Problems, 10th Revision.
Results:
There were 442,010 diagnoses on the HICs, of which 20,330 (4.60%) were rule-out diagnoses. Rule-out diagnoses accounted for 8.5% of total medical expenditure. The proportion of medical expenditure spent on rule-out diagnoses varied across the major diseases categories, and it was estimated that more than one-third (36.9%) of the medical expenditure on neoplasm is spent on rule-out diagnoses.
Conclusions:
The existence of rule-out diagnoses affects the estimation of disease-specific medical expenditure. Therefore, the estimation of disease-specific medical expenditure and evaluation of prevention and treatment programmes should be improved by utilizing information on rule-out diagnoses.
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