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Developing and Validating a Pediatric Potentially Avoidable Transfer Quality Metric.


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.

SUBMITTER: Rosenthal JL 

PROVIDER: S-EPMC6901803 | biostudies-literature | 2020 Mar/Apr

REPOSITORIES: biostudies-literature

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Developing and Validating a Pediatric Potentially Avoidable Transfer Quality Metric.

Rosenthal Jennifer L JL   Atolagbe Oluseun O   Hamline Michelle Y MY   Li Su-Ting T ST   Toney Alexis A   Witkowski Jessica J   McKnight Heather H   Tancredi Daniel J DJ   Romano Patrick S PS  

American journal of medical quality : the official journal of the American College of Medical Quality 20190610 2


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 <i>c</i>-statistic, and (4) validate this optimized metric definition using a separate sample. The initial metric usi  ...[more]

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