Averaging length of stay (LOS) ignores patient complexity and is a poor metric for quality control in geriatric hip fracture programs. We developed a predictive model of LOS that compares patient complexity to the logistic effects of our institution's hip fracture care pathway.
A retrospective analysis was performed on patients enrolled into a hip fracture co-management pathway at an academic level I trauma center from 2014 to 2015. Patient complexity was approximated using the Charlson Comorbidity Index and ASA score. A predictive model of LOS was developed from patient-specific and system-specific variables using a multivariate linear regression analysis; it was tested against a sample of patients from 2016.
LOS averaged 5.95 days. Avoidance of delirium and reduced time to surgery were found to be notable predictors of reduced LOS. The Charlson Comorbidity Index was not a strong predictor of LOS, but the ASA score was. Our predictive LOS model worked well for 63% of patients from the 2016 group; for those it did not work well for, 80% had postoperative complications.
Predictive LOS modeling accounting for patient complexity was effective for identifying (1) reasons for outliers to the expected LOS and (2) effective measures to target for improving our hip fracture program.
From the Department of Orthopaedic Surgery and Rehabilitation, Loyola University Medical Center, Maywood, IL (Dr. Hecht), the Quality and Safety Department, University of California, Davis, Sacramento, CA (Ms. Slee), the Department of Orthopaedic Surgery, UCSF-Fresno, Fresno, CA (Dr. Goodell), the Clinical and Translational Science Center, University of California, Davis (Dr. Taylor), and the Department of Orthopedics, University of California, Davis, Sacramento, CA (Dr. Wolinsky).
Correspondence to Dr. Hecht: email@example.com
This investigation was performed at the University of California, Davis, Medical Center by the UC Davis Geriatric Fracture Program.
Dr. Wolinsky or an immediate family member is a member of a speakers' bureau or has made paid presentations on behalf of Zimmer Biomet and serves as a board member, owner, officer, or committee member of the American Academy of Orthopaedic Surgeons, the American College of Surgeons, the California Orthopaedic Association, and the Orthopaedic Trauma Association. None of the following authors or any immediate family member has received anything of value from or has stock or stock options held in a commercial company or institution related directly or indirectly to the subject of this article: Dr. Hecht, Ms. Slee, Dr. Goodell, and Dr. Taylor.
Statistical analysis of the project was supported by the National Center for Advancing Translational Sciences, National Institutes of Health, through grant number UL1 TR001860. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.