Clinical predictors of protracted length of stay in Ontario Complex Continuing Care hospitals

TitleClinical predictors of protracted length of stay in Ontario Complex Continuing Care hospitals
Publication TypeJournal Article
Year of Publication2019
AuthorsTurcotte LA, Perlman CM, Fries BE, Hirdes JP
JournalBMC health services research
Volume19
Issue1
Pagination218-218
ISBN Number1472-6963
Accession Number30953489
KeywordsAdolescent, Adult, Aged, Aged, 80 and over, Child, Child, Preschool, Discharge planning, Female, HIV Infections/epidemiology/*therapy, Hospitals/statistics & numerical data, Humans, Infant, Infant, Newborn, length of stay, Length of Stay/*statistics & numerical data, Logistic Models, Long-Term Care/statistics & numerical data, Male, Middle Aged, Nursing Homes/statistics & numerical data, Ontario/epidemiology, Patient Discharge/statistics & numerical data, Patient flow, post-acute care, Retrospective Studies, Risk Factors, Subacute Care/statistics & numerical data, Young Adult
Abstract

BACKGROUND: Post-acute care hospitals are often subject to patient flow pressures because of their intermediary position along the continuum of care between acute care hospitals and community care or residential long-term care settings. The purpose of this study was to identify patient attributes associated with a prolonged length of stay in Complex Continuing Care hospitals. METHODS: Using information collected using the interRAI Resident Assessment Instrument Minimum Data Set 2.0 (MDS 2.0), a sample of 91,113 episodes of care for patients admitted to Complex Continuing Care hospitals between March 31, 2001 and March 31, 2013 was established. All patients in the sample were either discharged to a residential long-term care facility (e.g., nursing home) or to the community. Long-stay patients for each discharge destination were identified based on a length of stay in the 95th percentile. A series of multivariate logistic regression models predicting long-stay patient status for each discharge destination pathway were fit to characterize the association between demographic factors, residential history, health severity measures, and service utilization on prolonged length of stay in post-acute care. RESULTS: Risk factors for prolonged length of stay in the adjusted models included functional and cognitive impairment, greater pressure ulcer risk, paralysis, antibiotic resistant and HIV infection need for a feeding tube, dialysis, tracheostomy, ventilator or a respirator, and psychological therapy. Protective factors included advanced age, medical instability, a greater number of recent hospital and emergency department visits, cancer diagnosis, pneumonia, unsteady gait, a desire to return to the community, and a support person who is positive towards discharge. Aggressive behaviour was only a risk factor for patients discharged to residential long-term care facilities. Cancer diagnosis, antibiotic resistant and HIV infection, and pneumonia were only significant factors for patients discharged to the community. CONCLUSIONS: This study identified several patient attributes and process of care variables that are predictors of prolonged length of stay in post-acute care hospitals. This is valuable information for care planners and health system administrators working to improve patient flow in Complex Continuing Care and other post-acute care settings such as skilled nursing and inpatient rehabilitation facilities.

URLhttps://pubmed.ncbi.nlm.nih.gov/30953489https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6451230/
DOI10.1186/s12913-019-4024-2
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Short TitleBMC Health Serv ResBMC Health Serv Res
Alternate JournalBMC Health Serv Res