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Developing and Validating a Pediatric Potentially Avoidable Transfer Quality Metric
Author(s) -
Rosenthal Jennifer L.,
Atolagbe Oluseun,
Hamline Michelle Y.,
Li Su-Ting T.,
Toney Alexis,
Witkowski Jessica,
McKnight Heather,
Tancredi Daniel J.,
Romano Patrick S.
Publication year - 2020
Publication title -
american journal of medical quality
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.592
H-Index - 53
eISSN - 1555-824X
pISSN - 1062-8606
DOI - 10.1177/1062860619854535
Subject(s) - metric (unit) , medicine , statistic , confidence interval , gold standard (test) , medical diagnosis , quality (philosophy) , sample (material) , statistics , mathematics , operations management , radiology , philosophy , chemistry , epistemology , chromatography , economics
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.

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