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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1264-1276 |
| Number of pages | 13 |
| Journal | Health Services Research |
| Volume | 52 |
| Issue number | 4 |
| DOIs | |
| State | Published - Aug 2017 |
| Externally published | Yes |
Funding
Joint Acknowledgment/Disclosure Statement: All authors meet the criteria for authorship and have read and approved the final manuscript. The authors disclose no conflicts of interest. This research was deemed exempt from review by the Emory University institutional review board. The authors acknowledge the financial support of the Emory University Rollins School of Public Health, Laney Graduate School, and the School of Medicine. Kenton Johnston also acknowledges the financial support of the Saint Louis University College for Public Health and Social Justice. Dislosure: None. Disclaimer: None.
Keywords
- Emergency department visit algorithm
- emergency department use
- health services research
ASJC Scopus subject areas
- Health Policy
