Daphne Cockwell School of Nursing, Faculty of Community Services, Toronto Metropolitan University, 350 Victoria Street, Toronto, ON, M5B 2K3, Canada.
Division of Respirology, Department of Medicine, Women's College Hospital, 76 Grenville Street, Toronto, ON, M5S 1B2, Canada.
BMC Med Inform Decis Mak. 2023 Oct 18;23(1):226. doi: 10.1186/s12911-023-02273-6.
Computerized clinical decision support systems (CDSSs) can improve care by bridging knowledge to practice gaps. However, the real-world uptake of such systems in health care settings has been suboptimal. We sought to: (1) use the Theoretical Domains Framework (TDF) to identify determinants (barriers/enablers) of uptake of the Electronic Asthma Management System (eAMS) CDSS; (2) match identified TDF belief statements to elements in the Guideline Implementation with Decision Support (GUIDES) Checklist; and (3) explore the relationship between the TDF and GUIDES frameworks and the usefulness of this sequential approach for identifying opportunities to improve CDSS uptake.
In Phase 1, we conducted semistructured interviews with primary care physicians in Toronto, Canada regarding the uptake of the eAMS CDSS. Using content analysis, two coders independently analyzed interview transcripts guided by the TDF to generate themes representing barriers and enablers to CDSS uptake. In Phase 2, the same reviewers independently mapped each belief statement to a GUIDES domain and factor. We calculated the proportion of TDF belief statements that linked to each GUIDES domain and the proportion of TDF domains that linked to GUIDES factors (and vice-versa) and domains.
We interviewed 10 participants before data saturation. In Phase 1, we identified 53 belief statements covering 12 TDF domains; 18 (34.0%) were barriers, and 35 (66.0%) were enablers. In Phase 2, 41 statements (77.4%) linked to at least one GUIDES factor, while 12 (22.6%) did not link to any specific factor. The GUIDES Context Domain was linked to the largest number of belief statements (19/53; 35.8%). Each TDF domain linked to one or more GUIDES factor, with 6 TDF domains linking to more than 1 factor and 8 TDF domains linking to more than 1 GUIDES domain.
The TDF provides unique insights into barriers and enablers to CDSS uptake, which can then be mapped to GUIDES domains and factors to identify required changes to CDSS context, content, and system. This can be followed by conventional mapping of TDF domains to behaviour change techniques to optimize CDSS implementation. This novel step-wise approach combines two established frameworks to optimize CDSS interventions, and requires prospective validation.
计算机化临床决策支持系统（CDSS）可以通过弥合知识与实践差距来改善医疗服务。然而，在医疗保健环境中，此类系统的实际应用效果并不理想。我们旨在：（1）使用理论领域框架（TDF）来确定电子哮喘管理系统（eAMS）CDSS 采用的决定因素（障碍/促进因素）；（2）将确定的 TDF 信念陈述与指南实施与决策支持（GUIDES）清单的要素相匹配；（3）探索 TDF 和 GUIDES 框架之间的关系，以及这种逐步方法识别提高 CDSS 采用机会的有用性。
在第 1 阶段，我们对加拿大多伦多的初级保健医生进行了半结构化访谈，了解他们对 eAMS CDSS 的采用情况。使用内容分析，两位编码员根据 TDF 独立分析访谈记录，生成代表 CDSS 采用障碍和促进因素的主题。在第 2 阶段，相同的评审员独立地将每个信念陈述映射到 GUIDES 领域和因素。我们计算了与每个 GUIDES 领域和因素（反之亦然）以及领域链接的 TDF 信念陈述的比例。
在数据饱和之前，我们采访了 10 名参与者。在第 1 阶段，我们确定了 53 个信念陈述，涵盖了 12 个 TDF 领域；18 个（34.0%）是障碍，35 个（66.0%）是促进因素。在第 2 阶段，41 个陈述（77.4%）至少与一个 GUIDES 因素相关联，而 12 个陈述（22.6%）与任何特定因素都不相关联。GUIDES 背景领域与最多数量的信念陈述相关联（19/53；35.8%）。每个 TDF 领域都与一个或多个 GUIDES 因素相关联，其中 6 个 TDF 领域与多个因素相关联，8 个 TDF 领域与多个 GUIDES 领域相关联。
TDF 提供了对 CDSS 采用障碍和促进因素的独特见解，然后可以将其映射到 GUIDES 领域和因素，以确定对 CDSS 背景、内容和系统进行更改的必要性。接下来可以对 TDF 领域进行常规映射，以优化 CDSS 的实施。这种新颖的逐步方法结合了两个成熟的框架，以优化 CDSS 干预措施，需要前瞻性验证。
