Developing and Validating a Pediatric Potentially Avoidable Transfer Quality Metric. (March 2020)

• Record Type: Journal Article
• Authors: Rosenthal, Jennifer L.; Atolagbe, Oluseun; Hamline, Michelle Y.; Li, Su-Ting T.; Toney, Alexis; Witkowski, Jessica; McKnight, Heather; Tancredi, Daniel J.; Romano, Patrick S.
• Is Part Of: American journal of medical quality. Volume 35:Number 2(2020)
• Page Start: 163
• Page End: 170
• Publication Date: 2020-03
• Subjects: patient transfer -- child -- health care transitions -- hospitalization -- quality indicators -- health care; Medical care -- Quality control -- Periodicals; Medical care -- Evaluation -- Periodicals; Medical care -- Utilization review -- Periodicals; Medical care -- United States -- Periodicals; 362.1
• DOI: 10.1177/1062860619854535
• Languages: English
• ISSNs: 1062-8606

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.