Dataset Information

A "Patch" to the NYU Emergency Department Visit Algorithm.

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.

SUBMITTER: Johnston KJ

PROVIDER: S-EPMC5517669 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A "Patch" to the NYU Emergency Department Visit Algorithm.

Johnston Kenton J KJ Allen Lindsay L Melanson Taylor A TA Pitts Stephen R SR

Health services research 20170801 4

<h4>Objective</h4>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.<h4>Data sources</h4>The Nationwide Emergency Department Sample.<h4>Study design</h4>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.<h4 ...[more]

PMID: 28726238

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Dataset Information

A "Patch" to the NYU Emergency Department Visit Algorithm.

Objective

Data sources

Study design

Principal findings

Conclusions

Publications

A "Patch" to the NYU Emergency Department Visit Algorithm.

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