ArticleBMJ open2026
Discharge outcomes and associated patient-level factors in Ontario's remote care monitoring programme: a population-based survival analysis.
Article in BMJ open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectivesThis study examined discharge outcomes and their predictors among patients enrolled in remote patient monitoring (RPM) support in Ontario, Canada.
designA 6-month competing risk survival analysis.
settingCommunity-dwelling patients in Ontario, Canada.
participantsPatients enrolled between 1 April 2024 and 27 February 2025.
interventionsRPM programme patients are provided with wearable smart devices to monitor falls, medication non-adherence and wandering. Alerts from these devices trigger a response from the programme team, ranging from just a call back to further escalation support channels. PRIMARY AND SECONDARY OUTCOME MEASURES: Four competing discharge outcomes were analysed: (1) positive discharge, (2) death, (3) admission to long-term care (LTC) or hospice and (4) discontinuation due to functional incompatibility with devices.
resultsWithin 6 months, 208 (2.2%) patients died, 118 (1.2%) were admitted to an LTC/hospice, and 82 (0.9%) discontinued due to device unsuitability, while 185 (1.9%) achieved 'positive service discontinuation'. A dementia diagnosis at enrolment was consistently associated with all negative discharge outcomes: positive discharge (HR 0.00, 95% CI 0.00 to 0.00), admission to LTC or hospice (HR 1.95, 95% CI 1.25 to 3.04) and mortality (HR 0.62, 95% CI 0.39 to 1.12). And unsurprisingly, a cancer diagnosis at enrolment was associated with higher hazards of death (HR 2.5, 95% CI 1.77 to 3.52), while language spoken and escalation events were associated with discharge outcomes.
conclusionsMost RPM programme patients remain in the programme 6 months after enrolment, while a few achieve positive discontinuation. Discharge outcomes were influenced by several factors, most notably dementia diagnosis at enrolment. By leveraging predictive factors such as diagnosis at enrolment, escalation events and referral contexts, RPM programmes can optimise interventions to enhance patient transitions and improve outcomes.
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