1995PubMedRequires access

Computer-prompted diagnostic codes.

Kimberly S. H. Yarnall, J. Lloyd Michener, W E Broadhead, W. Ed Hammond, Chiu Kit Tse

Open publisher page 13 citations

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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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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Available 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.

Key concepts: Medical diagnosis, Medicine, Diagnosis code, Coding (social sciences), Chart, Medical record, Medical classification, Medical emergency

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