The utility of a shortened palliative care screening tool to predict death within 12 months – a prospective observational study in two south African hospitals with a high HIV burden

Abstract

Abstract Background Timely identification of people who are at risk of dying is an important first component of end-of-life care. Clinicians often fail to identify such patients, thus trigger tools have been developed to assist in this process. We aimed to evaluate the performance of a identification tool (based on the Gold Standards Framework Prognostic Indicator Guidance) to predict death at 12 months in a population of hospitalised patients in South Africa. Methods Patients admitted to the acute medical services in two public hospitals in Cape Town, South Africa were enrolled in a prospective observational study. Demographic data were collected from patients and patient notes. Patients were assessed within two days of admission by two trained clinicians who were not the primary care givers, using the identification tool. Outcome mortality data were obtained from patient folders, the hospital electronic patient management system and the Western Cape Provincial death registry which links a unique patient identification number with national death certificate records and system wide electronic records. Results 822 patients (median age of 52 years), admitted with a variety of medical conditions were assessed during their admission. 22% of the cohort were HIV-infected. 218 patients were identified using the screening tool as being in the last year of their lives. Mortality in this group was 56% at 12 months, compared with 7% for those not meeting any criteria. The specific indicator component of the tool performed best in predicting death in both HIV-infected and HIV-uninfected patients, with a sensitivity of 74% (68–81%), specificity of 85% (83–88%), a positive predictive value of 56% (49–63%) and a negative predictive value of 93% (91–95%). The hazard ratio of 12-month mortality for those identified vs not was 11.52 (7.87–16.9, p < 0.001). Conclusions The identification tool is suitable for use in hospitals in low-middle income country setting that have both a high communicable and non-communicable disease burden amongst young patients, the majority under age 60.