The inability to reliably identify individuals approaching the end of life presents challenges in providing efficient and high-quality palliative care. We developed an accurate, reliable, and automated tool based on the Hospital One-Year Mortality Risk (HOMR) algorithm that uses electronic health record (EHR) data to identify hospitalized patients at increased risk of death with unmet palliative needs.
In this study, we are implementing the HOMR tool in 20 Ontario hospitals. We developed a custom plan to integrate HOMR into the existing EHR and clinical workflows at each hospital. Patients flagged by HOMR are assessed for uncontrolled symptoms and their desire to engage in advance care planning. The clinical team then addresses any identified unmet needs.
Using hospital chart and provincial administrative data, we will examine the care received by patients identified by HOMR across care settings. We will also interview hospital teams to identify best practices for HOMR implementation; this will enable hospitals that implement HOMR in the future to learn from those that have already carried this out.
Recruitment to platform at one of the hubs
Consent and enrolment in platform
Collection of key data, minimizing participant burden for individual trials
Screening automatically for all trials taking place on the platform, maximizing options for patients and caregivers
Trials – patients and caregivers participate in trials they are eligible for
Ongoing check-ins – patients and caregivers are followed until they choose to stop participating or until patient death
Bereavement – we follow caregivers for up to three years and offer them bereavement interventions
By linking practice and research, the platform will improve care for patients and families affected by advanced cancer.
Practice
Clinicians, patients, and caregivers identify areas for improvement in care.
PCPCRC
Supports foundational research that identifies promising interventions.
Research Platform
Comprised of Phase 3 RCTs, Research Hubs, Data Strategy.
Evaluation of hub model and data strategy to optimize research.
Training and mentorship underlie and uphold all activities in the cycle.