Bedside Benchmarks: Transparent Data to Reduce Variation in Postoperative Care

SummaryReducing variation in care delivery is a leading strategy to create value in health care. In complex conditions, standardizing carevia prescriptive protocols is challenging, time consuming, and costly. An alternative approach is to use existing data as benchmarks for targeted outcomes, providing teams a shared mental model of an expected trajectory of care. Congenital heart disease (CHD) represents a complex, high-cost condition supported by a robust database of clinical benchmarks. This project aimed to improve value in CHD care and reduce variation in outcomes by using transparent benchmarks at the bedside to create shared mental models of postoperative trajectories, targeting length of stay (LOS) among other quality metrics. Results of the study found a significant decrease in hospital LOS variability and average postoperative central line duration compared with prepilot data. The targets were transparent to patients and families, and family satisfaction improved throughout the project from 76% to 92%.