What Factors Increase Odds of Long-Stay Delayed Discharge in Alternate Level of Care Patients?

Abstract

The objective of this study was to determine the factors that increase the odds of long-stay delayed discharge in alternate level of care (ALC) patients using data collected from the Ontario Wait Time Information System (WTIS) database. Retrospective cohort study utilizing data from Niagara Health's WTIS database. WTIS includes individuals admitted to any of the Niagara Health sites that have been designated as ALC. Sample consisted of 16,429 ALC patients who received care in Niagara Health hospitals from September 2014 to September 2019 and were recorded in the WTIS database. ALC designation of 30 or more days was used as the threshold for a long-stay delayed discharge. This study used binary logistic regression modeling to analyze sex, age, admission source, and discharge destination as well needs/barriers requirements to assess the likelihood of a long-stay delayed discharge among acute care (AC) and post-acute care (PAC) patients given the presence of each variable. Sample sizes calculations and receiver operating characteristic curves were used to verify the validity of the regression model. Overall, 10.2% of the sample were considered long-stay ALC patients. Both AC and PAC long-stay ALC patients were more likely to be male [OR= 1.23, (1.06-1.43); OR= 1.28, (1.03-1.60)] and have a discharge destination of a long-term care bed [OR= 28.68, (22.83-36.04); OR= 6.22, (4.75-8.15)]. AC patients had bariatric [OR= 7.16, (3.45-14.83)], behavioral [OR= 1.89, (1.22-2.91)], infection (isolation) [OR= 2.31, (1.63-3.28)], and feeding [OR= 6.38, (1.82-22.30)] barriers hindering discharge. PAC patients had no significant barriers hindering patient discharge. Shifting the focus from ALC patient designation to short- vs long-stay ALC patients allowed this study to focus on the subset of patients that are disproportionately affecting delayed discharges. Understanding the importance of specialized patient requirements in addition to clinical factors can help hospitals become more prepared in preventing delayed discharges.