OP58 Developing An Evaluation Based Taxonomy For mHealth Apps. (2019)

• Record Type: Journal Article
• Authors: Goddard, Kate; Erskine, Jamie
• Is Part Of: International journal of technology assessment in health care. Volume 35(2019)Supplement 1
• Page Start: 14
• Page End: 15
• Publication Date: 2019
• Subjects: Medical technology -- Periodicals; Technology assessment -- Periodicals; 610.28
• DOI: 10.1017/S0266462319001211
• Languages: English
• ISSNs: 0266-4623

Abstract

Abstract : Introduction: Mobile Health (mHealth) apps offer potential to promote greater public engagement in health, improve efficiency and open up new care pathways and models of care. However, the volume and heterogeneity of apps has led to uncertainty and lack of standardization around app definitions. Some mobile apps carry minimal risks to consumers, but others can carry significant risks. Work has been carried out to develop a framework for assessment (for example, for the NHS app library [beta version]). We discuss work helping to inform a preliminary framework of categorizing mHealth apps for proportionate assessment and validation, and the challenges involved. Methods: A literature review was carried out to identify different types of categorizations used to define health apps and the most important dimensions for their assessment. A taxonomy of apps and a process for routing them towards appropriate methods of evaluation was developed through iterative review, discussion and refinement. Results: Fourteen types of mHealth apps were established which were categorized by app function and by the potential risk involved with use. Subsequently, this research suggested a method of routing apps towards the most appropriate and proportionate method of evaluation, by using four example dimensions of impact (population size, disease burden, priority of clinical condition, and innovation), and four levels of risk. Conclusions: The outcome of an evaluation framework should be to enable healthcare professionals and patients to select and use safe and effective mHealth apps with greater confidence. A preliminary taxonomy and method of routing apps towards appropriate assessment are presented. Both need larger scale discussion, iterative testing and refining. This research faced significant challenges, including a high volume of heterogeneous apps with poorly standardized app definitions and associated nomenclature.