Brenner Maria, Weir Arielle, McCann Margaret, Doyle Carmel, Hughes Mary, Moen Anne, Ingvar Martin, Nauwelaerts Koen, Turk Eva, McCabe Catherine
School of Nursing and Midwifery, Trinity College Dublin, Dublin, Ireland.
HIQA, George's Court, Smithfield, Dublin, Ireland.
Digit Health. 2023 Jan 22;9:20552076231152160. doi: 10.1177/20552076231152160. eCollection 2023 Jan-Dec.
Digital health interventions offer new methods for delivering healthcare, with the potential to innovate healthcare services. Key performance indicators play a role in the evaluation, measurement, and improvement in healthcare quality and service performance. The aim of this scoping review was to identify current knowledge and evidence surrounding the development of key performance indicators for digital health interventions.
A literature search was conducted across ten key databases: AMED - The Allied and Complementary Medicine Database, CINAHL - Complete, Health Source: Nursing/Academic Edition, MEDLINE, APA PsycINFO, EMBASE, EBM Reviews - Cochrane Database of Systematic Reviews, EBM Reviews - Database of Abstracts of Reviews of Effects, EBM Reviews - Health Technology Assessment, and IEEE Xplore.
Five references were eligible for the review. Two were articles on original research studies of a specific digital health intervention, and two were overviews of methods for developing digital health interventions (not specific to a single digital health intervention). All the included reports discussed the involvement of stakeholders in developing key performance indicators for digital health interventions. The step of identifying and defining the key performance indicators was completed using various methodologies, but all centred on a form of stakeholder involvement. Potential options for stakeholder involvement for key performance indicator identification include the use of an elicitation framework, a factorial survey approach, or a Delphi study.
Few articles were identified, highlighting a significant gap in evidence-based knowledge in this domain. All the included articles discussed the involvement of stakeholders in developing key performance indicators for digital health interventions, which were performed using various methodologies. The articles acknowledged a lack of literature related to key performance indicator development for digital health interventions. To allow comparability between key performance indicator initiatives and facilitate work in the field, further research would be beneficial to develop a common methodology for key performance indicators development for digital health interventions.
数字健康干预提供了新的医疗保健提供方式,具有创新医疗服务的潜力。关键绩效指标在医疗质量和服务绩效的评估、衡量及改进中发挥作用。本范围综述的目的是确定围绕数字健康干预关键绩效指标发展的现有知识和证据。
在十个关键数据库中进行文献检索:联合与补充医学数据库(AMED)、护理学与健康领域数据库(CINAHL - Complete)、健康源:护理/学术版、医学期刊数据库(MEDLINE)、美国心理学会心理学文摘数据库(APA PsycINFO)、荷兰医学文摘数据库(EMBASE)、循证医学评论 - 系统评价 Cochrane 数据库、循证医学评论 - 效果评价文摘数据库、循证医学评论 - 卫生技术评估数据库以及电气和电子工程师协会数据库(IEEE Xplore)。
五篇参考文献符合综述要求。两篇是关于特定数字健康干预的原始研究文章,两篇是数字健康干预开发方法的综述(并非特定于单一数字健康干预)。所有纳入报告都讨论了利益相关者在数字健康干预关键绩效指标开发中的参与情况。确定和定义关键绩效指标的步骤使用了各种方法,但都以某种形式的利益相关者参与为核心。利益相关者参与关键绩效指标识别的潜在选项包括使用启发框架、因子调查方法或德尔菲研究。
识别出的文章很少,凸显了该领域循证知识的重大差距。所有纳入文章都讨论了利益相关者在数字健康干预关键绩效指标开发中的参与情况,这些开发采用了各种方法。文章承认缺乏与数字健康干预关键绩效指标开发相关的文献。为了使关键绩效指标计划具有可比性并促进该领域的工作,进一步研究将有助于为数字健康干预关键绩效指标开发制定通用方法。