JMIR Publications

ABSTRACT

Background:

Digital clinical measures, such as smartphones, smartwatches, wearables, ingestibles, and implantables, are increasingly used by individuals and clinicians to capture health outcomes and/or behavioral and physiological characteristics of individuals. Although academia is taking an active role in evaluating digital sensing products, academic contributions to advancing the safe, effective, ethical, and equitable use of digital clinical measures are poorly characterized.

Objective:

We performed a systematic review to characterize the nature of academic research on digital clinical measures and to compare and contrast the types of sensors used and the sources of funding support for specific sub-areas of this research.

Methods:

We conducted a PubMed search using a range of search terms to retrieve peer-reviewed articles reporting US-led academic research on digital clinical measures between January 2019 and February 2021. We screened each publication against specific inclusion and exclusion criteria. We then identified and categorized research studies based on the types of academic research, sensors used, and funding sources. Finally, we compared and contrasted the funding support for these specific sub-areas of research and sensor types.

Results:

The search retrieved 4,240 articles of interest. Following screening, 295 articles remained for data extraction and categorization. The top five research sub-areas included operations research (research analysis) (76%), analytical validation (59%), usability and utility (data visualization) (42%), verification (32%), and clinical validation (28%). The three most underrepresented areas of research into digital clinical measures were ethics (0%), security (0.5%), and data rights and governance (0.5%). Movement and activity trackers were the most commonly studied sensor type, and physiological-mechanical sensors were the least frequently studied. We found that government agencies are providing the most funding for research on digital clinical measures (65% of studies), followed by independent foundations (37%), and industry (19%), with the remaining 12% of these studies completely unfunded.

Conclusions:

Specific subareas of academic research related to digital clinical measures are not keeping pace with the rapid expansion and adoption of digital sensing products. An integrated and coordinated effort is required across academia, academic partners, and academic funders to establish the field of digital clinical measures as an evidence-based field worthy of our trust.