Hum Allyn, Kaur Palvinder, Goh Wen Yang, Tay Riyin, Neo Han Yee, Koh Mervyn Yong Hwang, Ali Noorhazlina Binte, Lim Wee Shiong, Tan Yu-Ling Jackie, Wu Huei Yaw, Kannapiran Palvannan, Tan Hwee Teng Robyn, Sun Yan, Ong Chin Ee, Sachdev Ravinder Singh, Low Zhi Jun, Tey Lee Hung, Tan Woan Shin, Ding Yew Yoong
Department of Palliative Medicine, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, Novena, 308433, Singapore.
Palliative Care Centre for Excellence in Research and Education, 1 Tan Tock Seng Link, Novena, 307382, Singapore.
BMC Geriatr. 2025 May 2;25(1):303. doi: 10.1186/s12877-025-05955-0.
People with dementia receive differential access to palliative care services despite suffering from a significant burden of the disease in the advanced stage. Professional and familial caregivers may not view dementia as a terminal illness and are less likely to engage in end-of-life care discussions. Healthcare providers also face challenges coordinating palliative care in the community for dementia, demonstrating a lack of understanding of the needs of patients living with advanced dementia, and resources available to support them within the community.
The aim of this study is to implement a transmural model of care in a tertiary care setting where patients living with advanced dementia (PLAD) at risk of deterioration in one year are identified early to receive tailored palliative care interventions using a predictive algorithm.
METHODS/DESIGN: The updated medical research council (MRC) framework for complex interventions is used to guide the development and implementation of the transmural model which incorporates a predictive algorithm in clinical practice, with interventions tailored for at risk PLAD both within, and beyond the tertiary care setting. The PROgnostic Model for Advanced DEmentia (PRO-MADE) developed to predict one-year all-cause mortality in PLAD presenting to an acute care hospital was embedded into the electronic health records of the tertiary care setting as a mathematical equation. Predictive modeling markup language in the digital records platform is used to calculate the risk score for PLAD by inputting the predictors. The clinical team is alerted of at risk PLAD through timed directive prompts, with advice on management given through tailored care bundles. The study will adopt a mixed methods approach in a Type 1 effectiveness-implementation study design to concurrently study the effectiveness of the transmural model in practice, and the barriers and facilitators to its implementation.
The implementation of a transmural model of early palliative care for patients with advanced dementia requires the coordination between clinicians in the tertiary care setting and community, together with health information technologists. This study protocol describes its development and implementation, and the study design to evaluate its outcomes.
尽管晚期痴呆症患者承受着巨大的疾病负担，但他们获得姑息治疗服务的机会却存在差异。专业护理人员和家庭护理人员可能不认为痴呆症是一种绝症，因此不太可能参与临终护理讨论。医疗保健提供者在为社区中的痴呆症患者协调姑息治疗方面也面临挑战，这表明他们对晚期痴呆症患者的需求以及社区中可用于支持他们的资源缺乏了解。
本研究的目的是在三级医疗机构中实施一种跨壁护理模式，通过预测算法早期识别出一年内有病情恶化风险的晚期痴呆症患者（PLAD），以便为其提供量身定制的姑息治疗干预措施。
方法/设计：更新后的医学研究理事会（MRC）复杂干预框架用于指导跨壁护理模式的开发和实施，该模式在临床实践中纳入了预测算法，并针对三级医疗机构内外有风险的PLAD患者量身定制干预措施。为预测入住急性护理医院的PLAD患者的一年全因死亡率而开发的晚期痴呆症预后模型（PRO-MADE）作为一个数学方程嵌入到三级医疗机构的电子健康记录中。数字记录平台中的预测建模标记语言用于通过输入预测因素来计算PLAD的风险评分。通过定时指令提示提醒临床团队注意有风险的PLAD患者，并通过量身定制的护理包提供管理建议。本研究将在1型有效性-实施研究设计中采用混合方法，同时研究跨壁护理模式在实践中的有效性以及实施该模式的障碍和促进因素。
为晚期痴呆症患者实施早期姑息治疗的跨壁护理模式需要三级医疗机构的临床医生与社区以及健康信息技术人员之间进行协调。本研究方案描述了其开发和实施过程，以及评估其结果的研究设计。
