An Electronic Tool to Support Patient-Centered Broad Consent: A Multi-Arm Randomized Clinical Trial in Family Medicine

Personalized and longitudinal electronic informed consent in clinical trials: How to move the needle?

Changes in the clinical trials landscape have been driven by advancements in digital technology. The use of electronic informed consent to inform research participants and to obtain their consent electronically has the potential to improve participant-researcher interactions over time, facilitate clinical trial participation, and increase efficiency in clinical trial conduct. A personalized electronic informed consent platform that enables long-term interactions with the research team could function as a tool to empower participant engagement in clinical trials. However, significant challenges persist impeding successful and widespread implementation. This Perspective provides insights into the opportunities and challenges for the implementation of electronic informed consent in clinical trials. It sets out key recommendations to promote the implementation of this innovative approach to the informed consent process, including the creation of uniform electronic informed consent platforms at regional and national level.

Comparative Effectiveness of eConsent: Systematic Review

BACKGROUND

Providing informed consent means agreeing to participate in a clinical trial and having understood what is involved. Flawed informed consent processes, including missing dates and signatures, are common regulatory audit findings. Electronic consent (eConsent) uses digital technologies to enable the consenting process. It aims to improve participant comprehension and engagement with study information and to address data quality concerns.

OBJECTIVE

This systematic literature review aimed to assess the effectiveness of eConsent in terms of patient comprehension, acceptability, usability, and study enrollment and retention rates, as well as the effects of eConsent on the time patients took to perform the consenting process ("cycle time") and on-site workload in comparison with traditional paper-based consenting.

METHODS

The systematic review was conducted and reported in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Ovid Embase and Ovid MEDLINE were systematically searched for publications reporting original, comparative data on the effectiveness of eConsent in terms of patient comprehension, acceptability, usability, enrollment and retention rates, cycle time, and site workload. The methodological validity of the studies that compared outcomes for comprehension, acceptability, and usability across paper consent and eConsent was assessed. Study methodologies were categorized as having "high" validity if comprehensive assessments were performed using established instruments.

RESULTS

Overall, 37 publications describing 35 studies (13,281 participants) were included. All studies comparing eConsenting and paper-based consenting for comprehension (20/35, 57% of the studies; 10 with "high" validity), acceptability (8/35, 23% of the studies; 1 with "high" validity), and usability (5/35, 14% of the studies; 1 with "high" validity) reported significantly better results with eConsent, better results but without significance testing, or no significant differences in overall results. None of the studies reported better results with paper than with eConsent. Among the "high" validity studies, 6 studies on comprehension reported significantly better understanding of at least some concepts, the study on acceptability reported statistically significant higher satisfaction scores, and the study on usability reported statistically significant higher usability scores with eConsent than with paper (P<.05 for all). Cycle times were increased with eConsent, potentially reflecting greater patient engagement with the content. Data on enrollment and retention were limited. Comparative data from site staff and other study researchers indicated the potential for reduced workload and lower administrative burden with eConsent.

CONCLUSIONS

This systematic review showed that compared with patients using paper-based consenting, patients using eConsent had a better understanding of the clinical trial information, showed greater engagement with content, and rated the consenting process as more acceptable and usable. eConsent solutions thus have the potential to enhance understanding, acceptability, and usability of the consenting process while inherently being able to address data quality concerns, including those related to flawed consenting processes.

Patient Perspectives and Preferences for Consent in the Digital Health Context: State-of-the-art Literature Review

BACKGROUND

The increasing integration of digital health tools into care may result in a greater flow of personal health information (PHI) between patients and providers. Although privacy legislation governs how entities may collect, use, or share PHI, such legislation has not kept pace with digital health innovations, resulting in a lack of guidance on implementing meaningful consent. Understanding patient perspectives when implementing meaningful consent is critical to ensure that it meets their needs. Consent for research in the context of digital health is limited.

OBJECTIVE

This state-of-the-art review aimed to understand the current state of research as it relates to patient perspectives on digital health consent. Its objectives were to explore what is known about the patient perspective and experience with digital health consent and provide recommendations on designing and implementing digital health consent based on the findings.

METHODS

A structured literature search was developed and deployed in 4 electronic databases-MEDLINE, IEEE Xplore, Scopus, and Web of Science-for articles published after January 2010. The initial literature search was conducted in March 2021 and updated in March 2022. Articles were eligible for inclusion if they discussed electronic consent or consent, focused on the patient perspective or preference, and were related to digital health or digital PHI. Data were extracted using an extraction template and analyzed using qualitative content analysis.

RESULTS

In total, 75 articles were included for analysis. Most studies were published within the last 5 years (58/75, 77%) and conducted in a clinical care context (33/75, 44%) and in the United States (48/75, 64%). Most studies aimed to understand participants' willingness to share PHI (25/75, 33%) and participants' perceived usability and comprehension of an electronic consent notice (25/75, 33%). More than half (40/75, 53%) of the studies did not describe the type of consent model used. The broad open consent model was the most explored (11/75, 15%). Of the 75 studies, 68 (91%) found that participants were willing to provide consent; however, their consent behaviors and preferences were context-dependent. Common patient consent requirements included clear and digestible information detailing who can access PHI, for what purpose their PHI will be used, and how privacy will be ensured.

CONCLUSIONS

There is growing interest in understanding the patient perspective on digital health consent in the context of providing clinical care. There is evidence suggesting that many patients are willing to consent for various purposes, especially when there is greater transparency on how the PHI is used and oversight mechanisms are in place. Providing this transparency is critical for fostering trust in digital health tools and the innovative uses of data to optimize health and system outcomes.

METORY: Development of a Demand-Driven Blockchain-Based Dynamic Consent Platform Tailored for Clinical Trials

The recent advent of the dynamic consent concept intensified the data integrity issue in clinical trials. Incorporating blockchain technology into a dynamic consent platform can be a feasible solution. Due to various clinical trial settings, a demand-driven development strategy is required. We developed a blockchain-based dynamic consent platform named METORY tailored for clinical trials. The platform consisted of three parts: web and mobile application user interface, study management platform, and blockchain platform. Hyperledger Fabric, an enterprise-grade private blockchain framework, was used to integrate blockchain into the study consent platform. We conducted user acceptance tests and applied feedback to the improvement of the platform. Identity and role-based access control was constructed by combining mobile-application-based certificate system and access control functionalities in Hyperledger fabric. Data were encrypted using SHA-256 prior to transmission to blockchain server and TLS protocol was used for in-transit encryption. File-system level encryption was separated implemented within the security measures from Amazon RDS. Users' experience in the clinical trial was acceptable in the ease and usefulness of the platform.

Knowledge and Attitudes of Research Participants in China Toward Electronic Informed Consent in Clinical Trials: A Cross Sectional Study

This study aims to investigate the knowledge and attitudes of participants and potential participants in clinical trials toward electronic informed consent. We conducted a survey-based cross-sectional study in Hunan Province, China in March 2021. A total of 547 respondents were included in this study. All questions in an 8-item survey section assessing participants' knowledge of electronic informed consent received correct answers from at least 70% of participants. In terms of attitude scores, most participants (86.3%) believed that electronic informed consent is more convenient than the paper-based version, and more than half (51.2%) believed that electronic informed consent could completely replace the paper-based version. Responses indicated that common concerns about electronic informed consent were its security and confidentiality, legal benefits, and implications for rights protection.

An Integrated, Scalable, Electronic Video Consent Process to Power Precision Health Research: Large, Population-Based, Cohort Implementation and Scalability Study

BACKGROUND

Obtaining explicit consent from patients to use their remnant biological samples and deidentified clinical data for research is essential for advancing precision medicine.

OBJECTIVE

We aimed to describe the operational implementation and scalability of an electronic universal consent process that was used to power an institutional precision health biobank across a large academic health system.

METHODS

The University of California, Los Angeles, implemented the use of innovative electronic consent videos as the primary recruitment tool for precision health research. The consent videos targeted patients aged ≥18 years across ambulatory clinical laboratories, perioperative settings, and hospital settings. Each of these major areas had slightly different workflows and patient populations. Sociodemographic information, comorbidity data, health utilization data (ambulatory visits, emergency room visits, and hospital admissions), and consent decision data were collected.

RESULTS

The consenting approach proved scalable across 22 clinical sites (hospital and ambulatory settings). Over 40,000 participants completed the consent process at a rate of 800 to 1000 patients per week over a 2-year time period. Participants were representative of the adult University of California, Los Angeles, Health population. The opt-in rates in the perioperative (16,500/22,519, 73.3%) and ambulatory clinics (2308/3390, 68.1%) were higher than those in clinical laboratories (7506/14,235, 52.7%; P<.001). Patients with higher medical acuity were more likely to opt in. The multivariate analyses showed that African American (odds ratio [OR] 0.53, 95% CI 0.49-0.58; P<.001), Asian (OR 0.72, 95% CI 0.68-0.77; P<.001), and multiple-race populations (OR 0.73, 95% CI 0.69-0.77; P<.001) were less likely to participate than White individuals.

CONCLUSIONS

This is one of the few large-scale, electronic video-based consent implementation programs that reports a 65.5% (26,314/40,144) average overall opt-in rate across a large academic health system. This rate is higher than those previously reported for email (3.6%) and electronic biobank (50%) informed consent rates. This study demonstrates a scalable recruitment approach for population health research.