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Published on: February 16, 2011
End-of-life care for patients with cancer: Clinical, geographical, and sociocultural differences
Rita Ostan1, Silvia Varani1, Francesco Pannuti2
1Training and Research Department, National Tumor Assistance (ANT), Bologna, Italy.
Objectives:
Timely, effective and personalized identification of the multidimensional needs in patients with advanced cancer are major goals of appropriate palliative care (PC) delivery. However, there is considerable variation in structures, processes, and patient demographics that might influence the intensity of end-of-life care. This study aims to characterize patterns in clinical and demographic characteristics at the inception point and their association with the intensity of care during the last month of life in advanced cancer patients assisted at home.
Methods:
Cancer patients entered in home PC during 2020 in Italy were considered. The association between home PC services during the last month of life (primary outcome) and demographic data, performance status (Karnofsky Performance Score [KPS]), symptoms, and therapies at the entry was explored in this retrospective study.
Results:
Among 1,721 consecutive patients (919 in Centre-North and 802 in Centre-South Italy), patients from Centre-South were younger (p < 0.001), had worse KPS (p < 0.001), and shorter survival (p = 0.010). Patient age was inversely associated with the number of total/physician/nurses services during the last month of life (p < 0.001, p = 0.001, and p = 0.008, respectively). Patients with severe symptoms (asthenia, pain, and anxiety) at inception needed more PC services at the end of life (p = 0.026, p = 0.008, and p = 0.038, respectively). The distribution of workload differed according to the geographical area, with higher number of PC services provided by physicians (p < 0.001) in Centre-North and by nurses (p = 0.002) in Centre-South.
Significance Of Results:
These findings highlight major disparity in access and nature of PC in a country with universal access to health services. Studies aimed at comparing PC models among different countries should pay attention to the local heterogeneity within each health-care system.
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