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Accepted for/Published in: JMIR Formative Research

Date Submitted: Mar 8, 2022
Date Accepted: Jul 14, 2022
Date Submitted to PubMed: Jul 19, 2022

The final, peer-reviewed published version of this preprint can be found here:

Deployment of an End-to-End Remote, Digitalized Clinical Study Protocol in COVID-19: Process Evaluation

Zahradka N, Pugmire J, Lever Taylor J, Wolfberg A, Wilkes M

Deployment of an End-to-End Remote, Digitalized Clinical Study Protocol in COVID-19: Process Evaluation

JMIR Form Res 2022;6(7):e37832

DOI: 10.2196/37832

PMID: 35852933

PMCID: 9345299

Deployment of an End-to-End Remote, Digitalized Protocol in COVID-19: Process Evaluation.

  • Nicole Zahradka; 
  • Juliana Pugmire; 
  • Jessie Lever Taylor; 
  • Adam Wolfberg; 
  • Matt Wilkes

ABSTRACT

Background:

The SARS-CoV-2 (COVID-19) pandemic may accelerate the adoption of digital, decentralized clinical trials. Conceptual recommendations for digitalized and remote clinical studies and technology are available to enable digitalization. Fully remote studies may breakdown some of the participation barriers in traditional trials. However, they add logistical complexity, and offer fewer opportunities to intervene following a technical failure or adverse event. Our group designed an end-to-end digital clinical study protocol, using the FDA cleared Current Health (CH) remote monitoring platform to collect symptoms and continuous physiological data in individuals recently infected with COVID-19 in the community.

Objective:

The purpose of this work is to provide a detailed example of an end-to-end digitalized protocol implementation based on conceptual recommendations by describing the study setup in detail, evaluating its performance, and identifying points of success and failure.

Methods:

Primary recruitment was via social media and word of mouth. Informed consent was obtained during a virtual appointment, and the CH monitoring kit shipped directly to the participant. The wearable continuously recorded pulse rate, respiratory rate, oxygen saturation, skin temperature, and step count, while a tablet administered symptom surveys. Data were transmitted in real time to the CH cloud-based platform and displayed in the web-based dashboard, with alerts to the study team if the wearable was not charged or worn. Study duration was up to 30 days. The time to recruit, screen, consent, set up equipment, and collect data were quantified, and advertising engagement tracked with a web analytics service.

Results:

Five out of 13 different study advertisements were live on social media at any one time. Thirty-eight eligibility forms were completed, and 19 respondents met eligibility criteria. Of these, nine were contactable and eight gave informed consent. Deployment times ranged from 22 hours to 110 hours, and participants set up the equipment and started transmitting vital signs within 7.6 (6.3-10) hours of delivery. Wearable adherence was 70 ± 19 % and daily survey adherence was 88 ± 21 % for the eight participants. Vital signs were in normal ranges during study participation and symptoms decreased over time.

Conclusions:

Evaluation of the clinical study implementation is important to capture what works and what might need to be modified. A well-calibrated approach to online advertising and enrollment can remove barriers to recruitment and lower costs but remains the most challenging part of research. Equipment was effectively and promptly shipped to participants and removed risk of illness transmission associated with in-person encounters during a pandemic. Wearable technology incorporating continuous, clinical grade monitoring offered an unprecedented level of detail and ecological validity. However, study planning, relationship-building, and troubleshooting are more complex in the remote setting. The relevance of a study to potential participants remains key to its success.


 Citation

Please cite as:

Zahradka N, Pugmire J, Lever Taylor J, Wolfberg A, Wilkes M

Deployment of an End-to-End Remote, Digitalized Clinical Study Protocol in COVID-19: Process Evaluation

JMIR Form Res 2022;6(7):e37832

DOI: 10.2196/37832

PMID: 35852933

PMCID: 9345299

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© 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.

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