Predicting Those Who Are at Risk of Dying within Six to Twelve Months in Primary Care: A Retrospective Case-Control General Practice Chart Analysis
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Published on: September 27, 2024
Anne Woolfield1,2, Geoffrey Mitchell1, Srinivas Kondalsamy-Chennakesavan3
1Primary Care Clinical Unit, Faculty of Medicine, The University of Queensland, Brisbane, Australia.
Abstract:
With an aging population, and most deaths due to a nonmalignant cause, there is urgency to review the nature of end-of-life care (EoLC) to minimize gaps in service provision. Early introduction of EoLC benefits patient and carers, so identification of those at risk of dying 6 to 12 months before death is highly desirable. To identify the most predictive patient characteristics of a risk of death within 6 to 12 months as a precursor to developing a user-friendly primary care screening tool. Retrospective case-control study. Australian general practice. Cases were patients aged ≥70 years who died in the previous 5 years. Controls were matched for age and gender. Exclusion criteria were: no available practice records for the 18 months before death (cases) and data collection (controls); no corroborated evidence of death. Supportive and Palliative Care Indicators Tool (SPICT) indicators of deterioration in medical records. There were 215 deaths and 267 controls. The most predictive patient characteristics of a risk of death within 6 to 12 months are: deteriorating performance status, weight loss, persistent symptoms, request for palliative care or treatment withdrawal, impaired activities of daily living, falls ± fractured hip, neurological deterioration, advanced lung disease, and estimated glomerular filtration rate <30 mL/min/1.73 m2 with deteriorating health. Our predictive model has a sensitivity and specificity of 67% and 87%, respectively, with a predictive accuracy of 78%. This model predicts risk of death within 6 to 12 months with acceptable reliability in a general practice setting and has the potential to be incorporated into clinical practice and electronic records.
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