The accuracy of Medicare's hospital claims data: progress has been made, but problems remain

Am J Public Health. 1992 Feb;82(2):243-8. doi: 10.2105/ajph.82.2.243.

Abstract

Background: Health care databases provide a widely used source of data for health care research, but their accuracy remains uncertain. We analyzed data from the 1985 National DRG Validation Study, which carefully reabstracted and reassigned ICD-9-CM diagnosis and procedure codes from a national sample of 7050 medical records, to determine whether coding accuracy had improved since the Institute of Medicine studies of the 1970s and to assess the current coding accuracy of specific diagnoses and procedures.

Methods: We defined agreement as the proportion of all reabstracted records that had the same principal diagnosis or procedure coded on both the original (hospital) record and on the reabstracted record. We also evaluated coding accuracy in 1985 using the concepts of diagnostic test evaluation.

Results: Overall, the percentage of agreement between the principal diagnosis on the reabstracted record and the original hospital record, when analyzed at the third digit, improved from 73.2% in 1977 to 78.2% in 1985. However, analysis of the 1985 data demonstrated that the accuracy of diagnosis and procedure coding varies substantially across conditions.

Conclusions: Although some diagnoses and all major surgical procedures that we examined were accurately coded, the variability in the accuracy of diagnosis coding poses a problem that must be overcome if claims-based research is to achieve its full potential.

Publication types

  • Comparative Study
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Abstracting and Indexing / standards*
  • Abstracting and Indexing / trends
  • Databases, Factual / standards
  • Diagnosis-Related Groups / standards*
  • Evaluation Studies as Topic
  • Hospitals / statistics & numerical data
  • Humans
  • Insurance Claim Reporting / standards*
  • Insurance Claim Reporting / trends
  • Medicare*
  • National Academies of Science, Engineering, and Medicine, U.S., Health and Medicine Division
  • Patient Discharge / statistics & numerical data*
  • United States