Developing and Validating a Pediatric Potentially Avoidable Transfer Quality Metric

Jennifer Rosenthal, Oluseun Atolagbe, Michelle Y. Hamline, Su-Ting Terry Li, Alexis Toney, Jessica Witkowski, Heather Mcknight, Daniel J Tancredi, Patrick S Romano

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
JournalAmerican Journal of Medical Quality
DOIs
StatePublished - Jan 1 2019

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Pediatrics
Confidence Intervals
Patient Transfer
Medical Records
Outcome Assessment (Health Care)
Physicians
Sensitivity and Specificity

Keywords

  • child
  • health care
  • health care transitions
  • hospitalization
  • patient transfer
  • quality indicators

ASJC Scopus subject areas

  • Health Policy

Cite this

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title = "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.",
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AU - Toney, Alexis

AU - Witkowski, Jessica

AU - Mcknight, Heather

AU - Tancredi, Daniel J

AU - Romano, Patrick S

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