Stochastic models to enable tailoring of medications to patients with multiple morbidities

慢性非传染性疾病是一项重大的全球负担和公共卫生挑战。糖尿病、心血管疾病、癌症和慢性呼吸道疾病等非传染性疾病是全世界死亡的主要原因。英国国家健康与护理卓越研究所（NICE）记录的临床路径和指南构成了一个以证据为基础的知识库，提供了治疗慢性病的药物和替代方案的建议。然而，指南往往不能解决复杂慢性病患者的需求，在这些情况下，需要谨慎选择药物。患有多种疾病的患者需要接受多种治疗途径，并且对处方药物组合存在未被发现的不良反应的风险。在苏格兰，超过一半的慢性疾病患者有合并症。最近的一项调查表明，5%至17%的住院病例与药物有关，其中一半被认为是可以预防的。此外，这些与药物有关的事件中的大多数是由于众所周知的常用处方药的不良反应。该项目着眼于我们如何利用数据更好地理解和定制护理计划和治疗，认识到个人的多重疾病负担以及他们的预期寿命和从治疗中获益的能力（超过风险）。

Chronic non-communicable diseases (NCDs) constitute a major global burden and public health challenge. NCDs such as diabetes, cardiovascular disease, cancer, and chronic respiratory diseases are the leading cause of mortality worldwide. Clinical pathways and guidelines documented by the National Institute of Health and Care Excellence (NICE) in the UK constitute an evidence-based knowledge base with recommendations on the medications and alternatives available to treat chronic conditions. However, guidelines often do not address the needs of patients with complex cases of chronic conditions where medications need to be chosen with care. Patients with multimorbidity are subject to multiple treatment pathways and there is a risk of undetected adverse reactions to combinations of prescribed medications. In Scotland, over half of all people with chronic conditions have comorbidities. A recent survey indicates that medicines are implicated in 5-17% of hospital admissions, of which half are considered preventable. Furthermore, the majority of these medicine related occurrences are due to well-known adverse effects of commonly prescribed drugs. This project looks at how can we use data to better understand and tailor care planning and treatment cognisant of multimorbidity burden for an individual and their predicted life expectancy and ability to benefit from treatment (that outweigh the risks).