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. 2017 Aug;52(4):1264-1276.
doi: 10.1111/1475-6773.12638.

A "Patch" to the NYU Emergency Department Visit Algorithm

Kenton J Johnston  1 , Lindsay Allen  2 , Taylor A Melanson  2 , Stephen R Pitts  3   4
Affiliations

A "Patch" to the NYU Emergency Department Visit Algorithm

Kenton J Johnston et al. Health Serv Res. 2017 Aug.

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.

Keywords: Emergency department visit algorithm; emergency department use; health services research.

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Figures

Figure 1
Figure 1
NYU ED Algorithm, Percentage of Total Visits Yearly Average, 2006–2012
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References

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