Oral Presentations

O-4: Predicting Alternate Level of Care (ALC) Status in Acute Hospitals Based on Pre-morbid Home Care Client Characteristics

MrS. Stella Arthur

Stella Arthur, PhD(c)*,
John Hirdes, PhD

University of Waterloo
Aging, Health, and Wellbeing


Topic: Health Services, Geriatrics

Approximately 85% of all ALC patients are 65 years or older. This suggests that ALC patients in hospitals are mostly seniors and frail. Uncertainties surrounding care-coordination at care transitions inadvertently affect the flow of patients and health outcomes. Predicting Alternate Level of Care status using information prior to hospital admission can reduce Alternate Level of Care rates and improve the transition of patients across the healthcare continuum.

Patient records from the Home Care Reporting System were linked to their corresponding Discharge Abstract Database. Sample included 230,754 patients assessed between 2009 and 2015. Descriptive, bivariate and multivariate model analyses were computed in ascertaining predictive factors of Alternate Level of Care status. Independent variables were from the Resident Assessment Instrument for Home Care.

Factors that were predictive of ALC status included advanced age, poor social support, Parkinson’s, Alzheimer's disease and related dementias, morbid obesity, clinical instability, need for institution-based services, caregiver distress, increased difficulty in performing activities of daily living and instrumental activities of daily living, falls, and problematic behaviors such as wandering.

Using home care data to predict ALC status in hospitalized home care clients shows that pre-morbid patient data can be valuable to inform decision making in other sectors of the health system.

This establishes the urgent need for an integrated approach to sharing and using standardized patient assessments like the interRAI system. This will ensure that the patient remains central to the care planning process and will also improve quality of care across the continuum of care by allowing patients’ needs to be proactively identified and responded to in a timelier manner.