208209 Testing the Sensitivity of the New York University Emergency Department Algorithm to Detect Changes in Emergency Department Usage Patterns

Tuesday, November 10, 2009

Kari Jones, PhD , Quantitative Health Research, Inc., Elberton, GA
Reidar Hagtvedt, PhD , Department of Finance and Management Science, University of Alberta, Edmonton, AB, Canada
Hannah D. Paxton, RN, BSN , Community Health & Health Studies, Lehigh Valley Hospital, Allentown, PA
William Bond, MD , Division of Education, Lehigh Valley Health Network, Allentown, PA
Jeff Etchason, MD , Dept. of Community Health and Health Studies, Lehigh Valley Hospital and Health Network, Allentown, PA
Background/Purpose: The Emergency Department Algorithm (EDA) is a tool developed by New York University Center for Health and Public Service Research that uses administrative discharge data to categorize emergency department (ED) visits by need for emergent care. Our analysis explains why various EDA users have observed EDA-generated outputs that do not change significantly with significant changes in patient populations and/or conditions in the associated healthcare system. Methods: Mathematical simulation was used to estimate EDA outcomes across all possible (hypothetical) patient populations; sensitivity analysis was used to demonstrate the changes in EDA outcomes for changes in a real-world baseline patient population. The baseline population consists of all ED cases from a community hospital's administrative database that did not result in inpatient admission and for which discharge ICD-9s (the input into the EDA) were available (n = 276,862). Results/Outcomes: The vast majority of possible EDA outputs do not differ significantly from one another. Thus, the vast majority of possible EDA outputs from the algorithm are so concentrated that they do not significantly differ even with significant changes to inputs to the algorithm. Using an actual patient population, the most extreme hypothetical increases in high-probability non-emergent, primary care treatable, or preventable visits would produce only a 9% decrease in EDA-estimated emergent cases. Conclusions: The EDA is being used nationally to assess ED usage; however, it is insufficiently sensitive to changes in ED use patterns to be of use to policymakers or hospital administrators in addressing possibly unnecessary ED use.

Learning Objectives:
Describe the Emergency Department Algorithm (EDA) developed at New York University for detecting changes in emergency department usage patterns. Discuss limitations in using the EDA for measuring changes in emergency department usage patterns.

Keywords: Emergency Department/Room, Service Delivery

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I was involved in all steps of this project, including developing it into an APHA presentation.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.