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Developing and Validating a Pediatric Potentially Avoidable Transfer Quality Metric

Authors :
Jennifer L. Rosenthal
Oluseun O. Atolagbe
Michelle Y. Hamline
Su-Ting Terry Li
Daniel J. Tancredi
Patrick S Romano
Alexis Toney
Jessica Witkowski
Heather McKnight
Source :
American journal of medical quality : the official journal of the American College of Medical Quality, vol 35, iss 2, Am J Med Qual
Publication Year :
2020
Publisher :
eScholarship, University of California, 2020.

Abstract

This study aimed to evaluate a quality metric that identifies pediatric potentially avoidable transfers from diagnosis and procedure codes. Using physician medical record review as the gold standard, the following steps were used: (1) develop the initial metric definition, (2) estimate initial metric definition operating characteristics, (3) refine this definition to optimize the c-statistic, and (4) validate this optimized metric definition using a separate sample. The initial metric using Sample A patient transfers had a c-statistic of 0.63 (95% confidence interval = 0.53-0.73). Following 22 revisions, the optimized metric definition was a transfer discharged within 24 hours that did not receive any of a select list of 60 268 specialized diagnoses or procedures. The optimized metric on Sample B demonstrated a sensitivity of 80.6%, specificity of 85.7%, and c-statistic of 0.83 (95% confidence interval = 0.75-0.91). The quality metric developed and validated in this study demonstrated satisfactory operating characteristics, providing a feasible means to measure this important outcome.

Details

Database :
OpenAIRE
Journal :
American journal of medical quality : the official journal of the American College of Medical Quality, vol 35, iss 2, Am J Med Qual
Accession number :
edsair.doi.dedup.....48add5a455003c5d4b8026b85c3b7b25