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Impact on place of death in cancer patients: a causal exploration in southern Switzerland

机译:对癌症患者死亡地点的影响:瑞士南部的因果探索

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Most terminally ill cancer patients prefer to die at home, but a majority die in institutional settings. Research questions about this discrepancy have not been fully answered. This study applies artificial intelligence and machine learning techniques to explore the complex network of factors and the cause-effect relationships affecting the place of death, with the ultimate aim of developing policies favouring home-based end-of-life care. A data mining algorithm and a causal probabilistic model for data analysis were developed with information derived from expert knowledge that was merged with data from 116 deceased cancer patients in southern Switzerland. This data set was obtained via a retrospective clinical chart review. Dependencies of disease and treatment-related decisions demonstrate an influence on the place of death of 13%. Anticancer treatment in advanced disease prevents or delays communication about the end of life between oncologists, patients and families. Unknown preferences for the place of death represent a great barrier to a home death. A further barrier is the limited availability of family caregivers for terminal home care. The family’s preference for the last place of care has a high impact on the place of death of 51%, while the influence of the patient’s preference is low, at 14%. Approximately one-third of family systems can be empowered by health care professionals to provide home care through open end-of-life communication and good symptom management. Such intervention has an influence on the place of death of 17%. If families express a convincing preference for home care, the involvement of a specialist palliative home care service can increase the probability of home deaths by 24%. Concerning death at home, open communication about death and dying is essential. Furthermore, for the patient preference for home care to be respected, the family’s decision for the last place of care seems to be key. The early initiation of family-centred palliative care and the provision of specialist palliative home care for patients who wish to die at home are suggested.
机译:大多数患病的癌症患者宁愿在家里死亡,但大多数死于机构环境。关于这种差异的研究尚未完全回答。本研究适用于人工智能和机器学习技术来探索复杂的因素网络和影响死亡地点的造成关系,终极目标是制定有利于家庭生活终生护理的政策。数据挖掘算法和数据分析的因果概率模型是通过从瑞士南部116名已故癌症患者的数据与来自116名已故癌症患者的数据合并的专家知识而产生的信息。该数据集是通过回顾性临床图表审查获得的。疾病和治疗有关的决定的依赖性表现出对13%的死亡地点的影响。晚期疾病中的抗癌治疗可防止或延迟肿瘤学家,患者和家庭之间生活结束的沟通。对死亡地点的未知偏好代表了家庭死亡的巨大障碍。另一个屏障是终端家庭护理的家庭护理人员的有限可用性。家庭对最后一个护理地点的偏好对51%的死亡地方产生了很高的影响,而患者偏好的影响较低,14%。卫生保健专业人员可以通过开放的生活端通信和良好的症状管理提供大约三分之一的家庭系统。这种干预对17%的死亡地方产生了影响。如果家庭表达了令人信服的家庭护理偏好,专业姑息家庭护理服务的参与可以将家庭死亡的可能性增加24%。关于家里的死亡,开放关于死亡和死亡的沟通至关重要。此外,对于患者偏爱家庭护理被尊重,家庭对最后一个护理的决定似乎是关键。建议,为希望在家死亡的患者提供家庭中心的姑息治疗的早期开始和提供专业姑息家庭护理。

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