Literature DB >> 21208348

Estimating medical expenditures spent on rule-out diagnoses in Japan.

Shinichi Tanihara1, Etsuji Okamoto, Hiroshi Une.   

Abstract

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.
© 2011 Blackwell Publishing Ltd.

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Year:  2011        PMID: 21208348     DOI: 10.1111/j.1365-2753.2010.01601.x

Source DB:  PubMed          Journal:  J Eval Clin Pract        ISSN: 1356-1294            Impact factor:   2.431


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