Literature DB >> 7876783

Computer-prompted diagnostic codes.

K S Yarnall1, J L Michener, W E Broadhead, W E Hammond, C K Tse.   

Abstract

BACKGROUND: The purpose of this study was to develop and evaluate a computer system that would translate patient diagnoses noted by a physician into appropriate International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes and maintain a patient-specific up-to-date problem list.
METHODS: The intervention consisted of a computerized list (dictionary) of diagnoses, including practice-specific synonyms and abbreviations, linked to their corresponding ICD-9-CM codes. To record the diagnoses for the office visit before the intervention, physicians used International Classification of Health Problems in Primary Care (ICHPPC-2) codes. After the intervention, physicians used their own words or checked previously identified diagnoses on the computer-generated problem list. The computer then identified the correct ICD-9-CM code. Accuracy of coding was compared before and after the new computerized system was implemented.
RESULTS: Visits in which all diagnoses matched increased from 58% to 76% (P < .001) with use of the computer system. Visits in which no computer diagnoses matched the chart decreased from 22% to 8% (P < .001). Errors of omission declined from 38% to 18% (P < .001). Errors of commission decreased from 19% to 11% (P = .006). Overall accuracy increased from 62% to 82% (P < .001).
CONCLUSIONS: Outpatient medical diagnosis coding can be simplified and accuracy improved by using a computerized dictionary of practice-specific diagnoses and synonyms linked to appropriate ICD-9-CM codes. Such a system provides a computer-generated problem list that accurately reflects the chart and assists with prompted coding on subsequent visits.

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Mesh:

Year:  1995        PMID: 7876783

Source DB:  PubMed          Journal:  J Fam Pract        ISSN: 0094-3509            Impact factor:   0.493


  3 in total

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2.  Evaluating a computerized tool for coding patient information.

Authors:  C Bouchet; F Empereur; F Kohler
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Review 3.  Accuracy of data in computer-based patient records.

Authors:  W R Hogan; M M Wagner
Journal:  J Am Med Inform Assoc       Date:  1997 Sep-Oct       Impact factor: 4.497

  3 in total

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