Abstract

Objective

The purpose of the study was to explore the theoretical underpinnings of effective clinical decision support (CDS) factors using the comparative effectiveness results.

Materials and Methods

We leveraged search results from a previous systematic literature review and updated the search to screen articles published from January 2017 to January 2020. We included randomized controlled trials and cluster randomized controlled trials that compared a CDS intervention with and without specific factors. We used random effects meta-regression procedures to analyze clinician behavior for the aggregate effects. The theoretical model was the Unified Theory of Acceptance and Use of Technology (UTAUT) model with motivational control.

Results

Thirty-four studies were included. The meta-regression models identified the importance of effort expectancy (estimated coefficient = −0.162; P = .0003); facilitating conditions (estimated coefficient = 0.094; P = .013); and performance expectancy with motivational control (estimated coefficient = 1.029; P = .022). Each of these factors created a significant impact on clinician behavior. The meta-regression model with the multivariate analysis explained a large amount of the heterogeneity across studies (R2 = 88.32%).

Discussion

Three positive factors were identified: low effort to use, low controllability, and providing more infrastructure and implementation strategies to support the CDS. The multivariate analysis suggests that passive CDS could be effective if users believe the CDS is useful and/or social expectations to use the CDS intervention exist.

Conclusions

Overall, a modified UTAUT model that includes motivational control is an appropriate model to understand psychological factors associated with CDS effectiveness and to guide CDS design, implementation, and optimization.

中文翻译：

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基于理论的影响临床决策支持采用和实施的因素的元回归

摘要

客观的

本研究的目的是利用比较有效性结果探索有效临床决策支持 (CDS) 因素的理论基础。

材料和方法

我们利用先前系统文献综述的搜索结果并更新搜索以筛选 2017 年 1 月至 2020 年 1 月发表的文章。我们纳入了随机对照试验和整群随机对照试验，它们比较了有和没有特定因素的 CDS 干预。我们使用随机效应元回归程序来分析临床医生行为的总体效应。理论模型是具有动机控制的技术接受和使用统一理论（UTAUT）模型。

结果

纳入了 34 项研究。元回归模型确定了努力预期的重要性（估计系数 = -0.162；P  = .0003 ）；便利条件（估计系数 = 0.094；P  = .013）；和动机控制的绩效预期（估计系数 = 1.029；P  = .022）。这些因素中的每一个都对临床医生的行为产生了重大影响。多变量分析的元回归模型解释了研究之间的大量异质性（R2 = 88.32%）。

讨论

确定了三个积极因素：使用难度低、可控性低以及提供更多基础设施和实施策略来支持 CDS。多变量分析表明，如果用户认为 CDS 有用和/或存在使用 CDS 干预的社会期望，则被动 CDS 可能是有效的。

结论

总体而言，包含动机控制的修正 UTAUT 模型是了解与 CDS 有效性相关的心理因素并指导 CDS 设计、实施和优化的合适模型。