Analytical frameworks and outcome measures in economic evaluations of digital health interventions: a methodological systematic review

Abstract

Background
Digital health interventions (DHIs) can improve the provision of healthcare services. To fully account for their effects in economic evaluations, traditional methods based on measuring health-related quality of life may not be appropriate, as non-health and process outcomes are likely to be relevant too.
Purpose
This systematic review identifies, assesses and synthesises the arguments on the analytical frameworks and outcome measures used in the economic evaluations of DHIs. The results informed recommendations for future economic evaluations.
Data Sources
We ran searches on multiple databases, complemented by grey literature, backward and forward citation searches.
Study Selection
We included records containing theoretical and empirical arguments associated with the use of analytical frameworks and outcome measures for economic evaluations of DHIs. Following title/abstract and full-text screening, our final analysis included 15 studies.
Data extraction
The arguments we extracted related to analytical frameworks (14 studies), generic outcome measures (5 studies), techniques used to elicit utility values (3 studies), disease-specific outcome measures and instruments to collect health states data (both from 2 studies).
Data synthesis
Rather than assessing the quality of the studies, we critically assessed and synthesised the extracted arguments. Building on this synthesis, we developed a three-stage set of recommendations where we encourage the use of impact matrices and analyses of equity impacts to integrate traditional economic evaluation methods.
Limitations
Our review and recommendations explored but not fully covered other potentially important aspects of economic evaluations which were outside our scope.
Conclusions
This is the first systematic review that summarises the arguments on how the effects of DHIs could be measured in economic evaluations. Our recommendations will help design future economic evaluations.