Evidence map›Paper›PMID 25716369›Full record

ArticleJournal of epidemiology2015

Assessment of text documentation accompanying uncoded diagnoses in computerized health insurance claims in Japan.

Shinichi Tanihara

Abstract read
In one paragraph

Article in Journal of epidemiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

1 author.

Shinichi TaniharaDepartment of Public Health and Preventive Medicine, School of Medicine, Fukuoka University.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUncoded diagnoses in health insurance claims (HICs) may introduce bias into Japanese health statistics dependent on computerized HICs. This study's aim was to identify the causes and characteristics of uncoded diagnoses.

methodsUncoded diagnoses from computerized HICs (outpatient, inpatient, and the diagnosis procedure-combination per-diem payment system [DPC/PDPS]) submitted to the National Health Insurance Organization of Kumamoto Prefecture in May 2010 were analyzed. The text documentation accompanying the uncoded diagnoses was used to classify diagnoses in accordance with the International Classification of Diseases-10 (ICD-10). The text documentation was also classified into four categories using the standard descriptions of diagnoses defined in the master files of the computerized HIC system: 1) standard descriptions of diagnoses, 2) standard descriptions with a modifier, 3) non-standard descriptions of diagnoses, and 4) unclassifiable text documentation. Using these classifications, the proportions of uncoded diagnoses by ICD-10 disease category were calculated.

resultsOf the uncoded diagnoses analyzed (n = 363 753), non-standard descriptions of diagnoses for outpatient, inpatient, and DPC/PDPS HICs comprised 12.1%, 14.6%, and 1.0% of uncoded diagnoses, respectively. The proportion of uncoded diagnoses with standard descriptions with a modifier for Diseases of the eye and adnexa was significantly higher than the overall proportion of uncoded diagnoses among every HIC type.

conclusionsThe pattern of uncoded diagnoses differed by HIC type and disease category. Evaluating the proportion of uncoded diagnoses in all medical facilities and developing effective coding methods for diagnoses with modifiers, prefixes, and suffixes should reduce number of uncoded diagnoses in computerized HICs and improve the quality of HIC databases.

Indexed as

DiagnosisDocumentationInsurance, HealthClinical CodingHumansInsurance Claim ReportingInsurance Claim ReviewInternational Classification of DiseasesJapan

Identifiers

PMID25716369
PMCPMC4340994

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