A "Patch" to the NYU Emergency Department Visit Algorithm. (August 2017)

• Record Type: Journal Article
• Authors: Johnston, Kenton J.; Allen, Lindsay; Melanson, Taylor A.; Pitts, Stephen R.
• Is Part Of: Health services research. Volume 52:Number 4(2017)
• Page Start: 1264
• Page End: 1276
• Publication Date: 2017-08
• Subjects: Emergency department visit algorithm -- emergency department use -- health services research; Medical care -- Periodicals; Medical care -- Evaluation -- Periodicals; Hospital care -- Periodicals; Health services administration -- Periodicals; 362
• DOI: 10.1111/1475-6773.12638
• Languages: English
• ISSNs: 0017-9124

Abstract

Abstract : 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.