Enhancing palliative care registration using an automated robotic process with clinician validation: A PRADA prospective cohort study.

Abstract

BACKGROUND: Ineffective care planning at the end of life carries high rates of unscheduled hospitalisation and avoidable deaths in hospital. Palliative care registration (PCR) and crucially, care planning, helps improve adverse outcomes. However, identification for registration often occurs late or not at all. AIM: To improve PCR accuracy and uptake by developing an automated digital tool, utilising palliative care process markers, combined with clinical judgement, to identify those with palliative care needs. DESIGN & SETTING: A primary care based prospective cohort study in Wolverhampton. METHOD: =39,079) were included. A robotic process tool (BOT) identified those not on the PCR using any of five palliative care process markers. BOT positive patients were assessed by GPs for the PCR. Performance metrics for prediction of subsequent 1 year mortality were determined. RESULTS: <0.001). The new combined PCR captured 220 (35.5%) of deaths, compared to 25.4% in the original PCR . A 'digital safety net' group, comprising those initially on the PCR and all BOT positive patients, accounted for 48.6% of deaths. CONCLUSION: We developed a robotic process technique combined with GP assessment that yielded higher PCR uptake and accuracy, identifying individuals at-risk for ongoing surveillance.

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