期刊
HEALTH SERVICES RESEARCH
卷 52, 期 4, 页码 1264-1276出版社
WILEY
DOI: 10.1111/1475-6773.12638
关键词
Emergency department visit algorithm; emergency department use; health services research
资金
- Emory University Rollins School of Public Health
- Emory University Laney Graduate School
- Emory University School of Medicine
- Saint Louis University College for Public Health and Social Justice
Objective. To document erosion in the New York University Emergency Department (ED) visit algorithm's capability to classify ED visits and to provide a patch to the algorithm. Data Sources. The Nationwide Emergency Department Sample. Study Design. We used bivariate models to assess whether the percentage of visits unclassifiable by the algorithm increased due to annual changes to ICD-9 diagnosis codes. We updated the algorithm with ICD-9 and ICD-10 codes added since 2001. Principal Findings. The percentage of unclassifiable visits increased from 11.2 percent in 2006 to 15.5 percent in 2012 (p < .01), because of new diagnosis codes. Our update improves the classification rate by 43 percent in 2012 (p < .01). Conclusions. Our patch significantly improves the precision and usefulness of the most commonly used ED visit classification system in health services research.
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