Effectiveness of transmural team-based palliative care in prevention of hospitalizations in patients at the end of life: A systematic review and meta-analysis

Abstract

Background: Team-based palliative care interventions have shown positive results for patients at the end of life in both hospital and community settings. However, evidence on the effectiveness of transmural, that is, spanning hospital and home, team-based palliative care collaborations is limited. Aim: To systematically review whether transmural team-based palliative care interventions can prevent hospital admissions and increase death at home. Design: Systematic review and meta-analysis. Data sources: MEDLINE (Ovid), Embase (Ovid), CINAHL (Ebsco), PsychINFO (Ovid), and Cochrane Library (Wiley) were systematically searched until January 2021. Studies incorporating teams in which hospital and community professionals co-managed patients, hospital-based teams with community follow-up, and case-management interventions led by palliative care teams were included. Data was extracted by two researchers independently. Results: About 19 studies were included involving 6614 patients, of whom 2202 received an intervention. The overall pooled odds ratio of at least one hospital (re)admissions was 0.46 (95% confidence interval (CI) 0.34–0.68) in favor of the intervention group. The highest reduction in admission was in the hospital-based teams with community follow-up: OR 0.21 (95% CI 0.07–0.66). The pooled effect on home deaths was 2.19 (95% CI 1.26–3.79), favoring the intervention, with also the highest in the hospital-based teams: OR 4.77 (95% CI 1.23–18.47). However, studies had high heterogeneity regarding intervention, study population, and follow-up time. Conclusion: Transmural team-based palliative care interventions, especially hospital-based teams that follow-up patients at home, show an overall effect on lowering hospital admissions and increasing the number of patients dying at home. However, broad clinical and statistical heterogeneity of included studies results in uncertainty about the effect size.