Patient Acuity as a Predictor of Length of Hospital Stay and Discharge Disposition After Open Colorectal Surgery

Abstract

Major areas of concern within the US healthcare system today include the quality and cost of healthcare. Open colorectal surgery patients have a higher prevalence of prolonged length of hospital stay (LOS) than most other types of surgery patients and are likely to be discharged to home care or other healthcare settings (DHCS), both of which contribute to increased costs. The ability to predict which patients are at risk for these outcomes early after open colorectal surgery could prompt nursing interventions aimed at improving quality of care and reducing healthcare costs. Radwin and Fawcett’s Refined Quality Health Outcomes Model served as the conceptual framework for this study. In this retrospective cross sectional study of adult open colorectal surgery patients (N=789), nursing documentation in the electronic health record (EHR) was reused to examine the relationships among patient acuity, LOS, and discharge disposition (DD). At the large Midwest healthcare system where this study took place, a patient acuity software system generated real-time patient acuity scores from discrete nursing assessment data fields in the EHR. This information was being used by unit nurse managers to guide nurse staffing decisions. Patient data were stratified by three discharge diagnostic-related groups (DRG) for colorectal surgeries, DRG 329, 330, and 331, to provide some control for comorbidities and post-operative complications. Multiple regression analysis for each DRG examined how patient acuity and select patient characteristics predicted prolonged LOS. Findings included that having a high patient acuity score on Day 2 or 3 after open colorectal surgery was a significant predictor of prolonged LOS for subjects in each DRG (DRG 329: B=1.985, p Implications for nursing include the need for further research to examine the use of patient acuity information to support evidence-based clinical decision making to improve healthcare quality and contain costs.