Application of the NICE Evidence Standards Framework for Digital Health Technologies in assessing mobile-delivered technologies for the self-management of type 2 diabetes mellitus: a scoping review
ABSTRACT
Background:
There is a growing role for digital health technologies in the management of chronic health conditions, and specifically type 2 diabetes. It is increasingly important that health technologies meet evidence standards for healthcare settings. In 2019, the National Institute for Health and Care Excellence (NICE) published the “NICE Evidence Standards Framework for Digital Health Technologies (DHTs)”. This provides guidance for evaluating the effectiveness and economic value of DHTs in a UK health and care setting.
Objective:
To assess whether scientific articles on digital healthcare technologies (DHTs) for self-management of type 2 diabetes mellitus (T2DM) report the evidence suggested for implementation in clinical practice, as described in the NICE Evidence Standards Framework for DHTs.
Methods:
We performed a scoping review of published articles, searching five databases to identify systematic reviews and then primary studies of mobile device-delivered DHTs that provide self-management support for adults with T2DM. The evidence reported within articles was assessed against standards described in the NICE framework.
Results:
The database search yielded 715 systematic reviews, of which 45 were relevant, and together included 59 eligible primary studies. Within these there were 39 unique technologies. Using the NICE framework, 13 technologies met ‘Best practice’ standards, 3 met ‘Minimum’ standards only and 23 technologies did not meet ‘Minimum’ standards.
Conclusions:
On the assessment of peer reviewed publications, over half of the DHTs identified did not appear to meet the minimum evidence standards recommended by the NICE framework. The most common reasons for studies of DHTs not meeting these evidence standards included: an absence of a comparator group, no prior justification of sample size, no measurable improvement in condition-related outcomes and a lack of statistical data analysis. This report provides information that will enable researchers and digital health developers to address these limitations when designing, delivering, and reporting digital health technology research going forward.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.