Literature DB >> 7795964

Data quality in a DRG-based information system.

C Colin1, R Ecochard, F Delahaye, G Landrivon, P Messy, E Morgon, Y Matillon.   

Abstract

The aim of this study initiated in May 1990 was to evaluate the quality of the medical data collected from the main hospital of the "Hospices Civils de Lyon", Edouard Herriot Hospital. We studied a random sample of 593 discharge abstracts from 12 wards of the hospital. Quality control was performed by checking multi-hospitalized patients' personal data, checking that each discharge abstract was exhaustive, examining the quality of abstracting, studying diagnoses and medical procedures coding, and checking data entry. Assessment of personal data showed a 4.4% error rate. It was mainly accounted for by spelling mistakes in surnames and first names, and mistakes in dates of birth. The quality of a discharge abstract was estimated according to the two purposes of the medical information system: description of hospital morbidity per patient and Diagnosis Related Group's case mix. Error rates in discharge abstracts were expressed in two ways: an overall rate for errors of concordance between Discharge Abstracts and Medical Records, and a specific rate for errors modifying classification in Diagnosis Related Groups (DRG). For abstracting medical information, these error rates were 11.5% (SE +/- 2.2) and 7.5% (SE +/- 1.9) respectively. For coding diagnoses and procedures, they were 11.4% (SE +/- 1.5) and 1.3% (SE +/- 0.5) respectively. For data entry on the computerized data base, the error rate was 2% (SE +/- 0.5) and 0.2% (SE +/- 0.05). Quality control must be performed regularly because it demonstrates the degree of participation from health care teams and the coherence of the database.(ABSTRACT TRUNCATED AT 250 WORDS)

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Year:  1994        PMID: 7795964     DOI: 10.1093/intqhc/6.3.275

Source DB:  PubMed          Journal:  Int J Qual Health Care        ISSN: 1353-4505            Impact factor:   2.038


  5 in total

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Authors:  Danielle L Scher; Brett D Owens; Rodney X Sturdivant; Jennifer Moriatis Wolf
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4.  Coding medical information: classification versus nomenclature and implications to the Israeli medical system.

Authors:  D A Vardy; R P Gill; A Israeli
Journal:  J Med Syst       Date:  1998-08       Impact factor: 4.460

5.  Systemic factors of errors in the case identification process of the national routine health information system: a case study of Modified Field Health Services Information System in the Philippines.

Authors:  Shinsuke Murai; Leizel P Lagrada; Julita T Gaite; Naruo Uehara
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  5 in total

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