Health Economics Unit, London, UK
School of Public Health, Imperial College London, London, UK.
BMJ Open. 2024 May 22;14(5):e067541. doi: 10.1136/bmjopen-2022-067541.
Assess understanding of impactibility modelling definitions, benefits, challenges and approaches.
Qualitative assessment.
Two workshops were developed. Workshop 1 was to consider impactibility definitions and terminology through moderated open discussion, what the potential pros and cons might be, and what factors would be best to assess. In workshop 2, participants appraised five approaches to impactibility modelling identified in the literature.
National Health Service (NHS) analysts, policy-makers, academics and members of non-governmental think tank organisations identified through existing networks and via a general announcement on social media. Interested participants could enrol after signing informed consent.
Descriptive assessment of responses to gain understanding of the concept of impactibility (defining impactibility analysis), the benefits and challenges of using this type of modelling and most relevant approach to building an impactibility model for the NHS.
37 people attended 1 or 2 workshops in small groups (maximum 10 participants): 21 attended both workshops, 6 only workshop 1 and 10 only workshop 2. Discussions in workshop 1 illustrated that impactibility modelling is not clearly understood, with it generally being viewed as a cross-sectional way to identify patients rather than considering patients by iterative follow-up. Recurrent factors arising from workshop 2 were the shortage of benchmarks; incomplete access to/recording of primary care data and social factors (which were seen as important to understanding amenability to treatment); the need for outcome/action suggestions as well as providing the data and the risk of increasing healthcare inequality.
Understanding of impactibility modelling was poor among our workshop attendees, but it is an emerging concept for which few studies have been published. Implementation would require formal planning and training and should be performed by groups with expertise in the procurement and handling of the most relevant health-related real-world data.
评估对影响性建模定义、益处、挑战和方法的理解。
定性评估。
开发了两个研讨会。研讨会 1 通过小组讨论来考虑影响性定义和术语，讨论潜在的优缺点，以及评估最佳因素是什么。在研讨会 2 中，参与者评估了文献中确定的五种影响性建模方法。
通过现有的网络和社交媒体上的一般公告，确定了 NHS 分析师、政策制定者、学者和非政府智库组织的成员。有兴趣的参与者在签署知情同意书后可以注册。
对反应的描述性评估，以了解影响性分析的概念、使用这种类型建模的益处和挑战，以及构建 NHS 影响性模型最相关的方法。
37 人以小组形式（最多 10 人）参加了 1 次或 2 次研讨会：21 人参加了 2 次研讨会，6 人仅参加了研讨会 1，10 人仅参加了研讨会 2。研讨会 1 的讨论表明，影响性建模的理解不明确，通常被视为识别患者的横断面方法，而不是通过迭代随访来考虑患者。研讨会 2 反复出现的因素是缺乏基准；不完全访问/记录初级保健数据和社会因素（被认为对理解治疗的适宜性很重要）；需要提供数据和行动建议，以及增加医疗保健不平等的风险。
我们的研讨会参与者对影响性建模的理解很差，但这是一个新兴概念，很少有研究对此进行过报道。实施将需要正式的规划和培训，并且应该由在采购和处理最相关的健康相关真实世界数据方面具有专业知识的团体来进行。
