Predictors of 30-day mortality following hip/pelvis fractures

Introduction: With the cost of healthcare in the United States reaching $2.9 trillion in 2013 and expected to increase with a growing geriatric population, the Center for Medicare and Medicaid Services (CMS) and Hospital Quality Alliance (HQA) began publicly reporting 30-day mortality rates so that hospitals and physicians may begin to confront clinical problems and promote high-quality and patient-centered care. Though the 30-day mortality is considered a highly effective tool in measuring hospital performance, little data actually exists that explores the rate and risk factors for trauma-related hip and pelvis fractures. Therefore, in this study, we sought to explore the risk factors associated with 30-day mortality in trauma related hip and pelvic fractures. Materials and methods: Utilizing the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database, 341,062 patients undergoing orthopaedic procedures from 2005 to 2013 were identified through a Current Procedural Terminology (CPT) code search. A second CPT code search identified 24,805 patients who sustained a hip/pelvis fracture. Patient demographics, preoperative comorbidities, operative characteristics and postoperative complications were collected and compared using Chi-squared test, Wilcoxon-Mann-Whitney test and multivariate logistic regression analysis. Results: Preoperative and postoperative risk factors for 30-day mortality following a hip/pelvis fracture were found: ASA classification, ascites, disseminated cancer, dyspnea, functional status, history of congestive heart failure (CHF), history of chronic obstructive pulmonary disease (COPD), a recent blood transfusion, and the postoperative complications: pneumonia, myocardial infarction, stroke, and septic shock. Discussion: Several preoperative patient risk factors and postoperative complications greatly increased the odds for patient mortality following 30-days after initial surgery. Orthopaedic surgeons can utilize these predictive risk factors to better improve patient care. (C) 2016 Elsevier Masson SAS. All rights reserved.