Coded Chief Complaints – Automated Analysis of Free-text Complaints
- David A. Thompson 1
- David Eitel 2
- Christopher M B Fernandez 3
- Jesse M Pines 4
- James Amsterdam 2
- Steven J Davidson 5
1 Department of Emergency Medicine, MacNeal Hospital, Berwyn, IL
2 Health Services Engineering/Design (DE), Department of Emergency Medicine (JA), The York Hospital, York, PA
3 Department of Medicine, McMaster University, Hamilton, Ontario, Canada
4 Department of Emergency Medicine, Center for Education and Research in Therapeutics, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, Philadelphia, PA
5 Department of Emergency Medicine, Maimonides Medical Center, Brooklyn, NY
Objectives: To describe a new chief-complaint categorization schema, the development of a computer text-parsing algorithm to automatically classify free-text chief complaints into this schema, and use of these coded chief complaints to describe the case mix of a community emergency department (ED).
Methods: Coded Chief Complaints for Emergency Department Systems (CCC-EDS) is a new and untested schema of 228 chief complaints, grouped within dimensions of type and system. A computerized text-parsing algorithm for automatically reading and classifying free-text chief complaints into 1 of these 228 coded chief complaints was developed by using a consecutive derivation sample of 46,602 patients who presented to a community teaching-hospital ED in 2004. Descriptive statistics included frequency of patients presenting with the 228 coded chief complaints; percentage of free-text complaints not categorizable by the CCC- EDS; and admission rate, age, and gender differences by chief complaint.
Results: In the derivation sample, the text-parsing algorithm classified 87.5% of 45,329 ED visits with non- null free-text chief complaints into 1 of 194 coded chief complaints. The text-parsing algorithm successfully classified 87.3% of the free-text chief complaints in a validation sample. The five most common coded chief complaints were Abdominal Pain (3,734 visits), Fever (2,234), Chest Pain (2,183), Breathing Difficulty (2,030), and Cuts-Lacerations (2,028).
Conclusions: The CCC-EDS is a new comprehensive, granular, and useful classification schema for categorizing chief complaints in an ED. A CCC-EDS text-parsing algorithm successfully classified the majority of free-text chief complaints from an ED computer log. These coded chief complaints were used to describe the case mix of a community teaching-hospital ED.
Patients with respiratory complaints during the influenza season of 2004–2005. Squares represent all patients with a Coded Chief Complaint for Emergency Department Systems (CCC-EDS) complaint of Cough. The mean weekly number of ED visits for this complaint was 24 (SD 14). ED visits for this complaint continuously exceeded the mean for weeks 53 to 13. Triangles represent all patients with a CCC-EDS complaint of Respiratory Illness. The mean weekly number of ED visits for this complaint was 84 (SD 31). ED visits for this complaint continuously exceeded the mean for weeks 52 to 13. Bars represent positive influenza (A and B) isolates reported by the Centers for Disease Control for the East North Central region of the United States (Illinois, Indiana, Michigan, Wisconsin, and Ohio).
Citation: Thompson DA, Eitel D. Coded Chief Complaints – Automated Analysis of Free-Text Complaints. Fernandes CMB, Pines JM, Amsterdam J, Davidson SJ. Acad Emerg Med. 2006;13:774-782. PubMed Abstract.
- Thompson DA, Courtney DM, Malik S, Schmidt MJ, Weston V. Use of Natural Language Processing to Identify 414 Different Chief Complaints in Adult Emergency Department Patients. Acad Emerg Med. 2018;25 (Issue S1):S139. Abstract and Chart.
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