Volume 52 | Number 4 | August 2017

Abstract List

Kenton J. Johnston Ph.D., Lindsay Allen M.A., Taylor A. Melanson B.A., Stephen R. Pitts M.D., M.P.H.


To document erosion in the New York University Emergency Department () visit algorithm's capability to classify 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 ‐9 diagnosis codes. We updated the algorithm with ‐9 and ‐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 ( < .01), because of new diagnosis codes. Our update improves the classification rate by 43 percent in 2012 ( < .01).


Our patch significantly improves the precision and usefulness of the most commonly used visit classification system in health services research.