CONTEXT: Few randomized controlled trials of advance care planning with a decision aid (DA) show an effect on patient preferences for end-of-life (EOL) care over time, especially in racial/ethnic settings outside the United States.
OBJECTIVES: The objective of this study was to examine the effect of a decision aid consisting of a video and an advance care planning (ACP) booklet for end-of-life (EOL) care preferences among patients with advanced cancer.
METHODS: Using a computer-generated sequence, we randomly assigned (1:1) advanced cancer patients to a group that received a video and workbook that both discussed either ACP (intervention group) or cancer pain control (control group). At baseline, immediately post-intervention, and at 7 weeks, we evaluated the subjects' preferences. The primary outcome was preference for EOL care (active treatment, life-prolonging treatment, or hospice care) on the assumption of a fatal disease diagnosis and the expectation of death 1) within 1 year, 2) within several months, and 3) within a few weeks. We used Bonferroni correction methods for multiple comparisons with an adjusted p level of 0.005.
RESULTS: From August 2017 to February 2018, we screened 287 eligible patients, of whom 204 were enrolled to the intervention (104 patients) or the control (100 patients). At post-intervention, the intervention group showed a significant increase in preference for active treatment, life-prolonging treatment, and hospice care on the assumption of a fatal disease diagnosis and the expectation of death within 1 year (p<0.005). Assuming a life expectancy of several months, the change in preferences was significant for active treatment and hospice care (p<0.005) but not for life-prolonging treatment. The intervention group showed a significant increase in preference for active treatment, life-prolonging treatment, and hospice care on the assumption of a fatal disease diagnosis and the expectation of death within a few weeks (p<0.005). From baseline to 7 weeks, the decrease in preference in the intervention group was not significant for active treatment, for life-prolonging treatment, and for hospice care in the intervention group in the subset expecting to die within 1 year, compared with the control group. Assuming a life expectancy of several months and a few weeks, the change in preferences was not significant for active treatment and for life-prolonging treatment, but was significantly greater for hospice care in the intervention group (p<0.005).
CONCLUSION: ACP interventions that included a video and an accompanying book improved preferences for EOL care.
PURPOSE: Understanding the concept of a "good death" is crucial to end-of-life care, but our current understanding of what constitutes a good death is insufficient. Here, we investigated the components of a good death that are important to the general population, cancer patients, their families, and physicians.
METHODS: We conducted a stratified nationwide cross-sectional survey of cancer patients and their families from 12 hospitals, physicians from 12 hospitals and the Korean Medical Association, and the general population, investigating their attitudes toward 10 good-death components.
FINDINGS: Three components-"not be a burden to the family," "presence of family," and "resolve unfinished business"-were considered the most important components by more than 2/3 of each of the three groups, and an additional three components-"freedom from pain," "feel that life was meaningful," and "at peace with God"-were considered important by all but the physicians group. Physicians considered "feel life was meaningful," "presence of family," and "not be a burden to family" as the core components of a good death, with "freedom from pain" as an additional component. "Treatment choices' followed, "finances in order," "mentally aware," and "die at home" were found to be the least important components among all four groups.
CONCLUSION: While families strongly agreed that "presence of family" and "not be a burden to family" were important to a good death, the importance of other factors differed between the groups. Health care providers should attempt to discern each patient's view of a good death.
BACKGROUND: In this study, we aimed to develop and validate an instrument that could be used by patients with cancer to evaluate their quality of palliative care.
METHODS: Development of the questionnaire followed the four-phase process: item generation and reduction, construction, pilot testing, and field testing. Based on the literature, we constructed a list of items for the quality of palliative care from 104 quality care issues divided into 14 subscales. We constructed scales of 43 items that only the cancer patients were asked to answer. Using relevance and feasibility criteria and pilot testing, we developed a 44-item questionnaire. To assess the sensitivity and validity of the questionnaire, we recruited 220 patients over 18 years of age from three Korean hospitals.
RESULTS: Factor analysis of the data and fit statistics process resulted in the 4-factor, 32-item Quality Care Questionnaire-Palliative Care (QCQ-PC), which covers appropriate communication with health care professionals (ten items), discussing value of life and goals of care (nine items), support and counseling for needs of holistic care (seven items), and accessibility and sustainability of care (six items). All subscales and total scores showed a high internal consistency (Cronbach alpha range, 0.89 to 0.97). Multi-trait scaling analysis showed good convergent (0.568-0.995) and discriminant (0.472-0.869) validity. The correlation between the total and subscale scores of QCQ-PC and those of EORTC QLQ-C15-PAL, MQOL, SAT-SF, and DCS was obtained.
CONCLUSION: This study demonstrates that the QCQ-PC can be adopted to assess the quality of care in patients with cancer.