mHOMR: a prospective observational study of an automated mortality prediction model to identify patients with unmet palliative needs

Autor: Carl van Walraven, Pete Wegier, Allison M Kurahashi, Jeff Myers, Ellen Koo, Leah Steinberg, Stephanie Saunders, Bhadra Lokuge, James Downar
Rok vydání: 2020
Předmět:
Zdroj: BMJ supportivepalliative care.
ISSN: 2045-4368
Popis: ObjectiveIdentification of patients with shortened life expectancy is a major obstacle to delivering palliative/end-of-life care. We previously developed the modified Hospitalised-patient One-year Mortality Risk (mHOMR) model for the automated identification of patients with an elevated 1-year mortality risk. Our goal was to investigate whether patients identified by mHOMR at high risk for mortality in the next year also have unmet palliative needs.MethodWe conducted a prospective observational study at two quaternary healthcare facilities in Toronto, Canada, with patients admitted to general internal medicine service and identified by mHOMR to have an expected 1-year mortality risk of 10% or more. We measured patients’ unmet palliative needs—a severe uncontrolled symptom on the Edmonton Symptom Assessment Scale or readiness to engage in advance care planning (ACP) based on Sudore’s ACP Engagement Survey.ResultsOf 518 patients identified by mHOMR, 403 (78%) patients consented to participate; 87% of those had either a severe uncontrolled symptom or readiness to engage in ACP, and 44% had both. Patients represented frailty (38%), cancer (28%) and organ failure (28%) trajectories were admitted for a median of 6 days, and 94% survived to discharge.ConclusionsA large majority of hospitalised patients identified by mHOMR have unmet palliative needs, regardless of disease, and are identified early enough in their disease course that they may benefit from a palliative approach to their care. Adoption of such a model could improve the timely introduction of a palliative approach for patients, especially those with non-cancer illness.
Databáze: OpenAIRE