scholarly journals Patient Perspective of Blockchain Technology in Clinical Trial Management: A Proof of Concept Study (Preprint)

2019 ◽  
Author(s):  
Julia Feldman ◽  
Laura Pugliese ◽  
Katrina Mateo ◽  
Stan Kachnowski
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Patient Perspective ◽  
Health Data ◽  
Management Tool ◽  
Proof Of Concept ◽  
Trial Management ◽  
Concept Study ◽  
Blockchain Technology ◽  
Clinical Trial Management

BACKGROUND Blockchain is a technology that has emerged over the past 12 years with the potential to heighten security, data provenance, immutability and create a ‘patient centered experience’ when used in clinical trials. Although much of the recent literature discusses the potential for blockchain to benefit patients in these trials, no IRB-approved, independent study, has evaluated a blockchain-enabled clinical trial management tool from the patient perspective. OBJECTIVE The objective of this study was to determine the usability and feasibility of a blockchain-enabled clinical trials management platform with a connected activity tracker and blood pressure monitor through the perspective of patients. Specifically, this study aimed to assess the ability of the blockchain-enabled platform to support electronic consenting, participants’ engagement and compliance to study activities in the one-week period, and to assess the participants’ ability to successfully use and transmit health data via the connected devices. METHODS A rapid proof of concept study of a blockchain software platform used for patient eConsent, engagement and management in clinical trials was conducted. Participants were recruited using digital flyering on online forums (e.g. Craigslist) and by contacting participants from previous studies by the authors. To be eligible participants had to be native English speakers aged 18-75 who: 1) have been diagnosed with at least one chronic condition, and 2) possess an Android or iOS Smart Phone. Once enrolled, participants used the platform (webpage and smartphone app) and activity trackers (a Fitbit™ and iHealth™ devices) for a one-week period. Adherence data as well as perceptions of the platform were collected via semi-structured interviews and surveys at baseline and endline visits. Audio-recorded interviews were professionally transcribed and systematically coded. RESULTS 15 chronically ill individuals with a mean age of 37.7 participated. Themes on opinions of the key properties of the blockchain technology emerged. Participants expressed that they valued transparency features of the blockchain tool because it would make doctors more accountable and potentially more cautious about the care they provide, which was especially important for patients with many doctors. Participants valued the ability to easily access, share and collect data remotely via the app because it saves money and time. Participants were highly interested in sharing their health records for clinical trials or being “matched” into trials. The heightened security of blockchain did not emerge as a major value because most expressed that they weren’t worried about keeping their health data secure. CONCLUSIONS Testing highlighted participants’ overall positive experience with the tool and trust that it could support their adherence to activities in the clinical trial, and that they would recommend the application be used in future studies. Participants believed that blockchain can improve the quality of care in clinical trials and were open to adopting it.

scholarly journals Expedited Safety Reporting Through an Alert System for Clinical Trial Management at an Academic Medical Center: Retrospective Design Study (Preprint)

2019 ◽  
Author(s):  
Yu Rang Park ◽  
HaYeong Koo ◽  
Young-Kwang Yoon ◽  
Sumi Park ◽  
Young-Suk Lim ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
High Risk ◽  
Performance Indicators ◽  
Phase 1 ◽  
Low Risk ◽  
Alert System ◽  
Trial Management ◽  
Safety Reporting ◽  
Clinical Trial Management

BACKGROUND Early detection or notification of adverse event (AE) occurrences during clinical trials is essential to ensure patient safety. Clinical trials take advantage of innovative strategies, clinical designs, and state-of-the-art technologies to evaluate efficacy and safety, however, early awareness of AE occurrences by investigators still needs to be systematically improved. OBJECTIVE This study aimed to build a system to promptly inform investigators when clinical trial participants make unscheduled visits to the emergency room or other departments within the hospital. METHODS We developed the Adverse Event Awareness System (AEAS), which promptly informs investigators and study coordinators of AE occurrences by automatically sending text messages when study participants make unscheduled visits to the emergency department or other clinics at our center. We established the AEAS in July 2015 in the clinical trial management system. We compared the AE reporting timeline data of 305 AE occurrences from 74 clinical trials between the preinitiative period (December 2014-June 2015) and the postinitiative period (July 2015-June 2016) in terms of three AE awareness performance indicators: onset to awareness, awareness to reporting, and onset to reporting. RESULTS A total of 305 initial AE reports from 74 clinical trials were included. All three AE awareness performance indicators were significantly lower in the postinitiative period. Specifically, the onset-to-reporting times were significantly shorter in the postinitiative period (median 1 day [IQR 0-1], mean rank 140.04 [SD 75.35]) than in the preinitiative period (median 1 day [IQR 0-4], mean rank 173.82 [SD 91.07], <i>P</i>≤.001). In the phase subgroup analysis, the awareness-to-reporting and onset-to-reporting indicators of phase 1 studies were significantly lower in the postinitiative than in the preinitiative period (preinitiative: median 1 day, mean rank of awareness to reporting 47.94, vs postinitiative: median 0 days, mean rank of awareness to reporting 35.75, <i>P</i>=.01; and preinitiative: median 1 day, mean rank of onset to reporting 47.4, vs postinitiative: median 1 day, mean rank of onset to reporting 35.99, <i>P</i>=.03). The risk-level subgroup analysis found that the onset-to-reporting time for low- and high-risk studies significantly decreased postinitiative (preinitiative: median 4 days, mean rank of low-risk studies 18.73, vs postinitiative: median 1 day, mean rank of low-risk studies 11.76, <i>P</i>=.02; and preinitiative: median 1 day, mean rank of high-risk studies 117.36, vs postinitiative: median 1 day, mean rank of high-risk studies 97.27, <i>P</i>=.01). In particular, onset to reporting was reduced more in the low-risk trial than in the high-risk trial (low-risk: median 4-0 days, vs high-risk: median 1-1 day). CONCLUSIONS We demonstrated that a real-time automatic alert system can effectively improve safety reporting timelines. The improvements were prominent in phase 1 and in low- and high-risk clinical trials. These findings suggest that an information technology-driven automatic alert system effectively improves safety reporting timelines, which may enhance patient safety.

scholarly journals Utilization of a Clinical Trial Management System for the Whole Clinical Trial Process as an Integrated Database: System Development (Preprint)

2017 ◽  
Author(s):  
Yu Rang Park ◽  
Young Jo Yoon ◽  
HaYeong Koo ◽  
Soyoung Yoo ◽  
Chang-Min Choi ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Management System ◽  
Medical Center ◽  
Academic Medical Center ◽  
Trial Management ◽  
Privacy And Security ◽  
Academic Medical ◽  
Asan Medical ◽  
Clinical Trial Management

BACKGROUND Clinical trials pose potential risks in both communications and management due to the various stakeholders involved when performing clinical trials. The academic medical center has a responsibility and obligation to conduct and manage clinical trials while maintaining a sufficiently high level of quality, therefore it is necessary to build an information technology system to support standardized clinical trial processes and comply with relevant regulations. OBJECTIVE The objective of the study was to address the challenges identified while performing clinical trials at an academic medical center, Asan Medical Center (AMC) in Korea, by developing and utilizing a clinical trial management system (CTMS) that complies with standardized processes from multiple departments or units, controlled vocabularies, security, and privacy regulations. METHODS This study describes the methods, considerations, and recommendations for the development and utilization of the CTMS as a consolidated research database in an academic medical center. A task force was formed to define and standardize the clinical trial performance process at the site level. On the basis of the agreed standardized process, the CTMS was designed and developed as an all-in-one system complying with privacy and security regulations. RESULTS In this study, the processes and standard mapped vocabularies of a clinical trial were established at the academic medical center. On the basis of these processes and vocabularies, a CTMS was built which interfaces with the existing trial systems such as the electronic institutional review board health information system, enterprise resource planning, and the barcode system. To protect patient data, the CTMS implements data governance and access rules, and excludes 21 personal health identifiers according to the Health Insurance Portability and Accountability Act (HIPAA) privacy rule and Korean privacy laws. Since December 2014, the CTMS has been successfully implemented and used by 881 internal and external users for managing 11,645 studies and 146,943 subjects. CONCLUSIONS The CTMS was introduced in the Asan Medical Center to manage the large amounts of data involved with clinical trial operations. Inter- and intraunit control of data and resources can be easily conducted through the CTMS system. To our knowledge, this is the first CTMS developed in-house at an academic medical center side which can enhance the efficiency of clinical trial management in compliance with privacy and security laws.

scholarly journals The first step to the powers for clinical trials: a survey on the current and future Clinical Trial Management System

2018 ◽  
Vol 26 (2) ◽  
pp. 86
Author(s):  
Jin-Sol Park ◽  
Seol Ju Moon ◽  
Ji-Hyoung Lee ◽  
Ji-Young Jeon ◽  
Kyungho Jang ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Management System ◽  
Future Clinical Trial ◽  
Trial Management ◽  
Clinical Trial Management

scholarly journals Using Blockchain Technology to Manage Clinical Trials Data: A Proof-of-Concept Study

10.2196/11949 ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. e11949 ◽  
Author(s):  
David M Maslove ◽  
Jacob Klein ◽  
Kathryn Brohman ◽  
Patrick Martin
Keyword(s):  
Clinical Trials ◽  
Proof Of Concept ◽  
Concept Study ◽  
Blockchain Technology

scholarly journals Expedited Safety Reporting to Sponsors Through the Implementation of an Alert System for Clinical Trial Management at an Academic Medical Center: Retrospective Design Study

10.2196/14379 ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. e14379
Author(s):  
Yu Rang Park ◽  
HaYeong Koo ◽  
Young-Kwang Yoon ◽  
Sumi Park ◽  
Young-Suk Lim ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
High Risk ◽  
Performance Indicators ◽  
Phase 1 ◽  
Low Risk ◽  
Alert System ◽  
Trial Management ◽  
Safety Reporting ◽  
Clinical Trial Management

Background Early detection or notification of adverse event (AE) occurrences during clinical trials is essential to ensure patient safety. Clinical trials take advantage of innovative strategies, clinical designs, and state-of-the-art technologies to evaluate efficacy and safety, however, early awareness of AE occurrences by investigators still needs to be systematically improved. Objective This study aimed to build a system to promptly inform investigators when clinical trial participants make unscheduled visits to the emergency room or other departments within the hospital. Methods We developed the Adverse Event Awareness System (AEAS), which promptly informs investigators and study coordinators of AE occurrences by automatically sending text messages when study participants make unscheduled visits to the emergency department or other clinics at our center. We established the AEAS in July 2015 in the clinical trial management system. We compared the AE reporting timeline data of 305 AE occurrences from 74 clinical trials between the preinitiative period (December 2014-June 2015) and the postinitiative period (July 2015-June 2016) in terms of three AE awareness performance indicators: onset to awareness, awareness to reporting, and onset to reporting. Results A total of 305 initial AE reports from 74 clinical trials were included. All three AE awareness performance indicators were significantly lower in the postinitiative period. Specifically, the onset-to-reporting times were significantly shorter in the postinitiative period (median 1 day [IQR 0-1], mean rank 140.04 [SD 75.35]) than in the preinitiative period (median 1 day [IQR 0-4], mean rank 173.82 [SD 91.07], P≤.001). In the phase subgroup analysis, the awareness-to-reporting and onset-to-reporting indicators of phase 1 studies were significantly lower in the postinitiative than in the preinitiative period (preinitiative: median 1 day, mean rank of awareness to reporting 47.94, vs postinitiative: median 0 days, mean rank of awareness to reporting 35.75, P=.01; and preinitiative: median 1 day, mean rank of onset to reporting 47.4, vs postinitiative: median 1 day, mean rank of onset to reporting 35.99, P=.03). The risk-level subgroup analysis found that the onset-to-reporting time for low- and high-risk studies significantly decreased postinitiative (preinitiative: median 4 days, mean rank of low-risk studies 18.73, vs postinitiative: median 1 day, mean rank of low-risk studies 11.76, P=.02; and preinitiative: median 1 day, mean rank of high-risk studies 117.36, vs postinitiative: median 1 day, mean rank of high-risk studies 97.27, P=.01). In particular, onset to reporting was reduced more in the low-risk trial than in the high-risk trial (low-risk: median 4-0 days, vs high-risk: median 1-1 day). Conclusions We demonstrated that a real-time automatic alert system can effectively improve safety reporting timelines. The improvements were prominent in phase 1 and in low- and high-risk clinical trials. These findings suggest that an information technology-driven automatic alert system effectively improves safety reporting timelines, which may enhance patient safety.

scholarly journals Leveraging Blockchain Technology for Informed Consent Process and Patient Engagement in a Clinical Trial Pilot

2021 ◽  
Author(s):  
Baldwin C. Mak ◽  
Bryan T. Addeman ◽  
Jia Chen ◽  
Kim A. Papp ◽  
Melinda J. Gooderham ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Patient Empowerment ◽  
Visit Time ◽  
Trial Management ◽  
Trial Quality ◽  
Blockchain Technology ◽  
Monitoring Visit ◽  
Clinical Trial Management ◽  
The Impact ◽  
Trial Cost

Objective: Despite the implementation of quality assurance procedures, current clinical trial management processes are time-consuming, costly, and often susceptible to error. This can result in limited trust, transparency, and process inefficiencies, without true patient empowerment. The objective of this study was to determine whether blockchain technology could enforce trust, transparency, and patient empowerment in the clinical trial data management process, while reducing trial cost. Design: In this proof of concept pilot, we deployed a Hyperledger Fabric-based blockchain system in an active clinical trial setting to assess the impact of blockchain technology on mean monitoring visit time and cost, non-compliances, and user experience. Using a parallel study design, we compared differences between blockchain technology and standard methodology. Results: A total of 12 trial participants, seven study coordinators and three clinical research associates across five sites participated in the pilot. Blockchain technology significantly reduces total mean monitoring visit time and cost versus standard trial management (475 to 7 min; P = 0.001; €722 to €10; P = 0.001 per participant/visit, respectively), while enhancing patient trust, transparency, and empowerment in 91, 82 and 63% of the patients, respectively. No difference in non-compliances as a marker of trial quality was detected. Conclusion: Blockchain technology holds promise to improve patient-centricity and to reduce trial cost compared to conventional clinical trial management. The ability of this technology to improve trial quality warrants further investigation.

Clinical Trial Management and Remote Data Entry on the Internet

1999 ◽  
Vol 33 (4) ◽  
pp. 1061-1065 ◽  
Author(s):  
Roberto Scognamillo ◽  
Carlo Strozzi ◽  
Beatrice Vincenzi ◽  
Giuseppe Recchia
Keyword(s):  
Clinical Trial ◽  
Data Entry ◽  
The Internet ◽  
Trial Management ◽  
Clinical Trial Management ◽  
Remote Data

scholarly journals Collecting standardised oral health data via mobile application: A proof of concept study in the Netherlands

PLoS ONE ◽  
2018 ◽  
Vol 13 (2) ◽  
pp. e0191385 ◽  
Author(s):  
Joost C. L. den Boer ◽  
Ward van Dijk ◽  
Virginie Horn ◽  
Patrick Hescot ◽  
Josef J. M. Bruers
Keyword(s):  
Oral Health ◽  
The Netherlands ◽  
Mobile Application ◽  
Health Data ◽  
Proof Of Concept ◽  
Concept Study

scholarly journals Hemophilia gene therapy: ushering in a new treatment paradigm?

Hematology ◽  
2021 ◽  
Vol 2021 (1) ◽  
pp. 226-233
Author(s):  
Lindsey A. George
Keyword(s):  
Clinical Trial ◽  
Gene Therapy ◽  
Clinical Trials ◽  
Hemophilia A ◽  
Full Potential ◽  
Proof Of Concept ◽  
Aav Vector ◽  
Treatment Paradigm ◽  
Clinical Trial Enrollment ◽  
New Treatment

Abstract After 3 decades of clinical trials, repeated proof-of-concept success has now been demonstrated in hemophilia A and B gene therapy. Current clinical hemophilia gene therapy efforts are largely focused on the use of systemically administered recombinant adeno-associated viral (rAAV) vectors for F8 or F9 gene addition. With multiple ongoing trials, including licensing studies in hemophilia A and B, many are cautiously optimistic that the first AAV vectors will obtain regulatory approval within approximately 1 year. While supported optimism suggests that the goal of gene therapy to alter the paradigm of hemophilia care may soon be realized, a number of outstanding questions have emerged from clinical trial that are in need of answers to harness the full potential of gene therapy for hemophilia patients. This article reviews the use of AAV vector gene addition approaches for hemophilia A and B, focusing specifically on information to review in the process of obtaining informed consent for hemophilia patients prior to clinical trial enrollment or administering a licensed AAV vector.

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