Strengthening the evidence base for mHealth in clinical practice: Conducting research with standalone or interoperable systems - a viewpoint

DIGITAL HEALTH(2023)

引用 0|浏览0
暂无评分
摘要
ObjectiveThe aim of this viewpoint is to inform mobile health (mHealth) evidence development in using standalone or interoperable systems in hospital practice.MethodsThere is a gap between mHealth research and its widespread uptake in clinical practice. Evidence generation is not keeping up with the introduction and implementation of technologies. This is partly a consequence of the technology characteristics and the way research is conducted in a clinical setting. Research and development of mHealth technology can be conducted standalone in a laboratory like setting, standalone in a clinical setting or interoperable with already existing technology in hospital practice.ResultsStandalone systems operate relatively independent from an organizations' existing infrastructure. Using laboratory settings does not reflect the complexity of real-life, but in clinical practice this may be suitable for research assessing usability, feasibility or even clinical and process outcomes at a small scale. Realizing research and development on interoperable mHealth technology solutions, especially with operational EMR systems, is a challenging, time- and resource intensive process and requires large(r) investments, as it is often complicated by a myriad of interfering factors. Interoperable systems are however a more sustainable option in the long run, and generated evidence reflects the real hospital care setting and this option may therefore facilitate dissemination. Choosing either a standalone or interoperable setting affects the research design, the implementation pace and ultimately widespread adoption of the mHealth technology.ConclusionWe recommend to include these technology characteristics in implementation frameworks and think of evaluation research designs in an early phase.
更多
查看译文
关键词
Information technology,technology,mHealth,eHealth,healthcare,research
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要