Australian Institute of Health Innovation, Macquarie University, 75 Talavera Road, Sydney 2113, Australia.
Australian Institute of Health Innovation, Macquarie University, 75 Talavera Road, Sydney 2113, Australia.
Int J Med Inform. 2019 Mar;123:1-10. doi: 10.1016/j.ijmedinf.2018.12.003. Epub 2018 Dec 12.
The act of predicting clinical endpoints and patient trajectories based on past and current states is on the precipice of a technological revolution. This systematic review summarises the available evidence describing healthcare provider opinions and preferences with respect to the use of clinical prediction rules. The primary goal of this work is to inform the design and implementation of future systems, and secondarily to identify gaps for the development of clinician education programs.
Five databases were systematically searched in May 2016 for studies collecting empirical opinions of healthcare providers regarding clinical prediction rule usage. Reference lists were scanned for additional eligible materials and an update search was made in August 2017. Data was extracted on high-level study features, before in-depth thematic analysis was performed.
45 articles were identified from 9 countries. Most studies utilised surveys (28) or interviews (14). Fewer employed focus groups (9) or formal usability testing (4). Three high-level themes were identified, which form the basis of healthcare provider opinions of clinical prediction rules and their implementation - utility, credibility and usability.
Some of the objections and preferences stated by healthcare providers are inherent to the nature of the clinical problem addressed, which may or may not be within the designer's capacity to change; however, others (in particular - actionability, validation, integration and provision of high quality education materials) should be considered by prediction rule designers and implementation teams, in order to increase user acceptance and improve uptake of these tools. We summarise these findings across the clinical prediction rule lifecycle and pose questions for the rule developers, in order to produce tools that are more likely to successfully translate into clinical practice.
基于过去和现在的状态预测临床终点和患者轨迹的行为正处于技术革命的边缘。本系统评价总结了现有描述医疗保健提供者对使用临床预测规则的意见和偏好的证据。这项工作的主要目的是为未来系统的设计和实施提供信息，其次是确定开发临床医生教育计划的差距。
2016 年 5 月，系统地搜索了五个数据库，以收集有关医疗保健提供者对临床预测规则使用的实证意见的研究。扫描参考文献列表以获取其他合格的材料，并于 2017 年 8 月进行了更新搜索。在进行深入的主题分析之前，提取了关于高级研究特征的数据。
从 9 个国家确定了 45 篇文章。大多数研究采用了调查（28 篇）或访谈（14 篇）。较少的研究采用了焦点小组（9 篇）或正式可用性测试（4 篇）。确定了三个高级主题，这是医疗保健提供者对临床预测规则及其实施的意见的基础 - 实用性、可信度和可用性。
医疗保健提供者提出的一些反对意见和偏好是所解决临床问题性质固有的，这可能在设计师的能力范围内，也可能不在设计师的能力范围内；然而，其他（特别是 - 可操作性、验证、集成和提供高质量的教育材料）应被预测规则设计者和实施团队考虑，以提高用户接受度并提高这些工具的使用率。我们总结了这些发现跨越了临床预测规则的生命周期，并为规则开发者提出了一些问题，以便开发出更有可能成功转化为临床实践的工具。
