Key result
Mixed-methods protocol proposes machine learning to predict delayed discharge and co-design community care packages.
Why the study?
Delayed hospital discharge is a persistent care quality issue that can cause physical and cognitive decline, but how community resources can be leveraged to avoid admissions and delayed discharges remains to be explored.
This mixed-methods research protocol outlines an approach using machine learning on administrative data and qualitative co-design to identify and support older adults at risk of delayed hospital discharge.
Protocol for ML prediction of delayed discharge in older adults; leaves open real-world effectiveness pending prospective validation.
INTRODUCTION: Delayed hospital discharge is a persistent care quality issue experienced across health systems worldwide and remains a priority area to be addressed in Canada. Often associated with a decrease in services while waiting to leave the hospital, delayed discharge from hospital can lead to increased frailty, physical and cognitive decline, and caregiver burnout. Optimizing availability of and timely access to community-based health and social care are avenues that could reduce initial admissions to the hospital and length of hospital stay, and facilitate hospital discharges. METHODS: This research will explore the ways in which community resources could be leveraged to potentially avoid hospitalization and delayed hospital discharge for older adults using sequential mixed-methods including co-design. To better understand the characteristics and needs of older adults, the research team will first identify sub-populations of older adults (65 years old or older) at risk of hospitalization and delayed discharge using comprehensive, longitudinal administrative health data. From these health data, risk profiles and personas will be created and then shared with key partners (e.g., older adults, caregivers, healthcare providers, healthcare decision-makers), who will be engaged to identify, leverage, and create targeted care solutions. The barriers and facilitators to the implementation of these care solutions will then be explored. DISCUSSION: Delayed hospital discharge has been a critical care quality issue across Canada for decades. The current research will provide health system leaders with an approach to better allocate services to older adults in order to avoid delayed hospital discharge and identify gaps in health and social care resources based on the characteristics, needs, and preferences of older adults, their caregivers, and providers.
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Kuluski et al. (2024) studied Delayed hospital discharge (n=1,800,000). Machine learning predictive models and co-designed care packages was evaluated on Risk of delayed-discharge hospitalization. A mixed-methods research protocol was designed to predict the risk of delayed hospital discharge using machine learning and to co-design community care packages for older adults.
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