PURPOSE: The purpose of this study was to identify factors associated with at-home death among patients with advanced cancer and create a decision-making model for discharging patients from an acute-care hospital. PATIENTS AND METHODS: We conducted an observational cohort study to identify the association between place of death and the clinical and demographic characteristics of patients with advanced cancer who received care from a palliative home care team (PHCT) and of their primary caregivers. We used logistic regression analysis to identify the predictors of at-home death. RESULTS: We identified 380 patients who met the study inclusion criteria; of these, 245 patients (64%) died at home, 72 (19%) died in an acute-care hospital, 60 (16%) died in a palliative care unit, and three (1%) died in a nursing home. Median follow-up was 48 days. We included the 16 variables that were significant in univariate analysis in our decision-making model. Five variables predictive of at-home death were retained in the multivariate analysis: caregiver's preferred place of death, patients' preferred place of death, caregiver's perceived social support, number of hospital admission days, and number of PHCT visits. A subsequent reduced model including only those variables that were known at the time of discharge (caregivers' preferred place of death, patients' preferred place of death, and caregivers' perceived social support) had a sensitivity of 96% and a specificity of 81% in predicting place of death. CONCLUSION: Asking a few simple patient- and family-centered questions may help to inform the decision regarding the best place for end-of-life care and death.
PURPOSE: The purpose of this study was to identify factors associated with at-home death among patients with advanced cancer and create a decision-making model for discharging patients from an acute-care hospital. PATIENTS AND METHODS: We conducted an observational cohort study to identify the association between place of death and the clinical and demographic characteristics of patients with advanced cancer who received care from a palliative home care team (PHCT) and of their primary caregivers. We used logistic regression analysis to identify the predictors of at-home death. RESULTS: We identified 380 patients who met the study inclusion criteria; of these, 245 patients (64%) died at home, 72 (19%) died in an acute-care hospital, 60 (16%) died in a palliative care unit, and three (1%) died in a nursing home. Median follow-up was 48 days. We included the 16 variables that were significant in univariate analysis in our decision-making model. Five variables predictive of at-home death were retained in the multivariate analysis: caregiver's preferred place of death, patients' preferred place of death, caregiver's perceived social support, number of hospital admission days, and number of PHCT visits. A subsequent reduced model including only those variables that were known at the time of discharge (caregivers' preferred place of death, patients' preferred place of death, and caregivers' perceived social support) had a sensitivity of 96% and a specificity of 81% in predicting place of death. CONCLUSION: Asking a few simple patient- and family-centered questions may help to inform the decision regarding the best place for end-of-life care and death.
Authors: C Peruselli; P Di Giulio; F Toscani; M Gallucci; C Brunelli; M Costantini; M Tamburini; E Paci; G Miccinesi; J M Addington-Hall; I J Higginson Journal: Palliat Med Date: 1999-05 Impact factor: 4.762
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Authors: Charmaine L Blanchard; Oluwatosin Ayeni; Daniel S O'Neil; Holly G Prigerson; Judith S Jacobson; Alfred I Neugut; Maureen Joffe; Keletso Mmoledi; Mpho Ratshikana-Moloko; Paul E Sackstein; Paul Ruff Journal: J Pain Symptom Manage Date: 2019-01-30 Impact factor: 3.612