TY  - JOUR
AU  - Shandhi, Md Mobashir Hasan
AU  - Goldsack, Jennifer C
AU  - Ryan, Kyle
AU  - Bennion, Alexandra
AU  - Kotla, Aditya V
AU  - Feng, Alina
AU  - Jiang, Yihang
AU  - Wang, Will Ke
AU  - Hurst, Tina
AU  - Patena, John
AU  - Carini, Simona
AU  - Chung, Jeanne
AU  - Dunn, Jessilyn
PY  - 2021
DA  - 2021/9/15
TI  - Recent Academic Research on Clinically Relevant Digital Measures: Systematic Review
JO  - J Med Internet Res
SP  - e29875
VL  - 23
IS  - 9
KW  - digital clinical measures
KW  - academic research
KW  - funding
KW  - biosensor
KW  - digital measures
KW  - digital health
KW  - health outcomes
AB  - Background: Digital clinical measures collected via various digital sensing technologies such as smartphones, smartwatches, wearables, ingestibles, and implantables are increasingly used by individuals and clinicians to capture health outcomes 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 subareas 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 subareas of research and sensor types. Results: The search retrieved 4240 articles of interest. Following the screening, 295 articles remained for data extraction and categorization. The top five research subareas included operations research (research analysis; n=225, 76%), analytical validation (n=173, 59%), usability and utility (data visualization; n=123, 42%), verification (n=93, 32%), and clinical validation (n=83, 28%). The three most underrepresented areas of research into digital clinical measures were ethics (n=0, 0%), security (n=1, 0.5%), and data rights and governance (n=1, 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 (n=192, 65%), followed by independent foundations (n=109, 37%) and industries (n=56, 19%), with the remaining 12% (n=36) 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. 
SN  - 1438-8871
UR  - https://www.jmir.org/2021/9/e29875
UR  - https://doi.org/10.2196/29875
UR  - http://www.ncbi.nlm.nih.gov/pubmed/34524089
DO  - 10.2196/29875
ID  - info:doi/10.2196/29875
ER  -