title: Healthcare Analytics: Creating a Prioritized Improvement System with Performance Benchmarking.
abstract: The importance of healthcare improvement is difficult to overstate. This article describes our collaborative work with experts at Seattle Children's to create a prioritized improvement system using performance benchmarking. We applied analytics and modeling approaches to compare and assess performance metrics derived from U.S. News and World Report benchmarking data. We then compared a wide range of departmental performance metrics, including patient outcomes, structural and process metrics, survival rates, clinical practices, and subspecialist quality. By applying empirically simulated transformations and imputation methods, we built a predictive model that achieves departments' average rank correlation of 0.98 and average score correlation of 0.99. The results are then translated into prioritized departmental and enterprise-wide improvements, following a data to knowledge to outcomes paradigm. These approaches, which translate data into sustainable outcomes, are essential to solving a wide array of healthcare issues, improving patient care, and reducing costs.
authors.affiliation: 1 Bioinformatics and High-throughput Analysis Laboratory, Seattle Children's Research Institute, University of Washington , Seattle, WA, USA .|2 Predictive Analytics, Seattle Children's, University of Washington , Seattle, WA, USA .|3 Departments of Biomedical Informatics & Medical Education and Pediatrics, University of Washington , Seattle, WA, USA .|4 Data-Enabled Life Sciences Alliance (DELSA Global), University of Washington , Seattle, WA, USA .
authors.forename: Eugene
authors.initials: E
authors.lastname: Kolker
authors.affiliation: 4 Data-Enabled Life Sciences Alliance (DELSA Global), University of Washington , Seattle, WA, USA .|5 Foster School of Business, University of Washington , Seattle, WA, USA .
authors.forename: Evelyne
authors.initials: E
authors.lastname: Kolker