Empirical Derivation of an Electronic Clinically Useful Problem Statement System

20 July 1999 | Volume 131 Issue 2 | Pages 117-126

Problem lists are tools to improve patient management. In the medical record, they connect diagnoses to therapy, prognosis, and psychosocial issues. Computer-based problem lists enhance paper-based approaches by enabling cost-containment and quality assurance applications, but they require clinically expressive controlled vocabularies. Because existing controlled vocabularies do not represent problem statements at a clinically useful level, we derived a new canonical problem statement vocabulary through semi-automated analysis and distillation of provider-entered problem lists collected over 6 years from 74 696 patients. We combined automated and manual methods to condense 891 770 problem statements entered by 1961 care providers at Grady Memorial Hospital in Atlanta, Georgia, to 15 534 Canonical Clinical Problem Statement System (CCPSS) terms. The nature and frequency of problem statements were characterized, interrelations among them were enumerated, and a database capturing the epidemiology of problems was created. The authors identified 23 503 problem relations (co-occurrences, sign-symptom complexes, and differential diagnoses) and 22 690 modifier words that further categorized "canonical" problems.

To assess completeness, CCPSS content was compared with that of the 1997 Unified Medical Language System Metathesaurus (containing terms from 44 clinical vocabularies). Unified Medical Language System terms expressed 25% of individual CCPSS terms exactly (71% of problems by frequency), 27% partially, and 48% poorly or not at all. Clinicians judged that CCPSS terms completely captured their clinical intent for 84% of 686 randomly selected free-text problem statements. The CCPSS represents clinical concepts at a level exceeding that of previous approaches. A similar national approach could create a standardized, useful, shared resource for clinical practice.

Author and Article Information

From Vanderbilt University and Veterans Affairs Medical Center, Nashville, Tennessee; Medical Systems Development Corp., Marietta, Georgia; and Emory University School of Medicine, Atlanta, Georgia.

Acknowledgments: The authors thank Dr. William W. Stead of Vanderbilt University, Ms. Betsy Humphreys of the National Library of Medicine, and Mr. Karl E. Liliestedt of Medical Systems Development Corp. for their contributions.

Grant Support: By National Library of Medicine grants 1 F38 LM00021-01A1 (Dr. Brown), LM06226-02 (Dr. Miller), 5 G08 LM05443 (Dr. Miller), and 1 R55 LM05779-01 (Dr. Guise).

Requests for Reprints: Steven H. Brown, MS, MD, Division of Biomedical Informatics, Room 402, Eskind Biomedical Library, 2209 Garland Avenue, Nashville, TN 37232-8340; e-mail, steven.brown{at}med.va.gov.

Current Author Addresses: Dr. Brown: Division of Biomedical Informatics, Room 402, Eskind Biomedical Library, 2209 Garland Avenue, Nashville, TN 37232-8340.

Dr. Miller: Division of Biomedical Informatics, Room 436, Eskind Biomedical Library, 2209 Garland Avenue, Nashville, TN 37232-8340.

Mr. Camp: Medical Systems Development Corp., 620 Village Trace, Marietta, GA 30067.

Dr. Guise: Division of Biomedical Informatics, Room 410, Eskind Biomedical Library, 2209 Garland Avenue, Nashville, TN 37232-8340.

Dr. Walker: Emory University Department of Medicine, 69 Butler Street, Atlanta, GA 30303.