Technology Support System and Review Process for a Decentralized

Clinical Trial: Trials@Home, RADIAL DCT as Case Study

Sten Hanke

1 a

, Dimitrios Giannikopoulos

, Hannes Hilberger

1,2 b

, Theresa Weitlaner

1 c

and Bernhard Neumayer

1 d

Institute of eHealth, University of Applied Sciences - FH Joanneum, Alte Poststraße 149, Graz, Austria

GSRC, Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria

BAYER AG, Wuppertal, Germany

Keywords:

Helpdesk, Technology Support System, Knowledge Base, Decentralised Clinical Trials.

Abstract:

Decentralized Clinical Trials (DCTs) revolutionize clinical research by leveraging digital technologies to de-

centralize various aspects inherent in the traditional clinical trial process like the need for patients’ physical

presence. DCTs integrate virtual and remote elements for assessments, data collection, and monitoring, pri-

oritizing convenience. However, the integration of diverse stakeholders and technologies poses challenges in

delivering timely and effective solutions across all trial sites. Addressing this requires the establishment of a

robust technology support system tailored to meet the unique demands of decentralization. This paper out-

lines the requirements for such a system and shares initial insights gained through the learning process. This

system combines a Wiki-like knowledge base with a ticketing system for handling support requests, enabling

the creation of topic-speciﬁc tickets and ensuring that queries are directed to the appropriate support agents

swiftly. The implemented helpdesk system in the RADIAL study exempliﬁes how combining a comprehen-

sive information resource with a responsive ticketing system not only streamlines supporting processes but

also signiﬁcantly enhances response efﬁciency and the overall user experience in DCTs. This integrated ap-

proach is pivotal in managing the complexities and dynamic nature of DCTs, ensuring that both patients and

stakeholders beneﬁt from the efﬁciency and adaptability of decentralized trials.

1 INTRODUCTION

Decentralized clinical trials (DCT) aim to elimi-

nate the need for study patients to be physically

present at the study site for investigations, contribut-

ing to increased efﬁciency, accessibility, and patient-

friendliness in clinical research. As technology ad-

vances, decentralized approaches are expected to play

a more signiﬁcant role in the future of clinical trials.

This approach broadens the pool of potential pa-

tients (de Jong et al., 2022), enhances patient adher-

ence (Jain et al., 2022), and reduces the study’s carbon

footprint (Subaiya et al., 2011; Holmner et al., 2014).

While these advancements are promising, the re-

duced on-site presence necessitates a robust support

system. This system should provide a continuously

https://orcid.org/0000-0003-3833-4252

https://orcid.org/0000-0003-3867-0651

https://orcid.org/0009-0005-7076-2929

https://orcid.org/0000-0002-4439-4799

accessible knowledge base and direct communica-

tion channels with professionals, ensuring stakehold-

ers are well-informed, up-to-date, and equipped to

handle hardware or other technical issues effectively.

Effective communication and tracking of techni-

cal and process issues are crucial for quality con-

trol. Integrating the technology provider’s support

in a timely and effective manner—from patients to

sites to Clinical Research Associates (CRAs) and ven-

dors—is imperative.

Although similar demands exist in conventional

clinical trials, DCTs introduce additional chal-

lenges due to the integration of different technology

providers and increased reliance on patients for using

technology. This raises expectations for the usability

and technical stability of apps and technologies.

In summary, a technology support system for

DCTs should not only promote seamless interaction

among stakeholders and technologies but also address

the challenge of providing timely solutions to various

sites.

638

Hanke, S., Giannikopoulos, D., Hilberger, H., Weitlaner, T. and Neumayer, B.

Technology Support System and Review Process for a Decentralized Clinical Trial: Trials@Home, RADIAL DCT as Case Study.

DOI: 10.5220/0012433900003657

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2024) - Volume 2, pages 638-645

ISBN: 978-989-758-688-0; ISSN: 2184-4305

Trials@Home’s technology support system en-

compasses all aspects required for barrier-free partic-

ipation in the RADIAL clinical trial. Given the mul-

titude of stakeholders and roles (patients, site, CRA)

in the study, the support system integrates various ex-

isting solutions provided by project partners, ensuring

an optimized workﬂow.

Using the RADIAL study as an example, this pa-

per presents an exemplary approach to consolidate

available tools into one helpdesk system. The pa-

per details the system’s requirements, the RADIAL

implementation, the achievement of quality control

through automated Key Performance Indicator (KPI)

exports, and an issue-tracking process. It also sum-

marizes initial experiences from the study.

2 BACKGROUND

In contemporary clinical trial technology, the inte-

gration of Electronic Data Capture (EDC) and Clin-

ical Trial Management Systems (CTMS) has become

commonplace. Recent studies, such as the investiga-

tion conducted by Zhang et al. (Zhang et al., 2013),

underscore a signiﬁcant rise in electronic data collec-

tion facilitated by various self-developed, commer-

cially available, or open-source software solutions.

These technological advancements have prompted a

reevaluation of the interpretation of ICH E6 and the

Good Clinical Practice guidelines by sponsors (Bhatt,

2023).

ICH E6(R2) was amended in 2023 to encourage

the implementation of technological advances to en-

hance the efﬁciency of clinical trial conduct. The sub-

sequent update, E6(R3), has elevated the guidelines

for incorporating state-of-the-art technologies in man-

aging clinical trials (Bhatt, 2023).

The guidelines recommend adapting the use of

technology in clinical trial conduct to ﬁt patient’s at-

tributes and trial design speciﬁcs (Council, 2023).

The emphasis on technology within these guidelines

has broad implications for all aspects of trial conduct,

including quality, ethics, and stakeholder responsibil-

ities (Bhatt, 2023).

The relevance of these guidelines becomes partic-

ularly evident with the emergence of DCTs. While

the guidelines advocate technology use for various

processes, spanning from data acquisition to patient

interaction and consent processes, they do not specif-

ically address technology support for issue tracking

and helpdesk support involving different stakeholders

in DCTs.

In clinical trials, particularly in DCTs, such a sup-

port system can play a pivotal role in managing and

addressing the varied needs of patients and the in-

volved technologies. DCTs, often spanning different

countries and languages, encounter unique challenges

like language barriers as well as varying levels of IT

proﬁciency among patients and site users. To address

these, a comprehensive support system is essential.

One critical component is a ticketing system. This

system allows patients to raise queries, which are then

addressed by a dedicated support team. The unique-

ness of this system lies in its dual function. Besides

resolving individual queries, the support team also

contributes to a centralized knowledge base. When

a query is resolved, the team develops articles or con-

tent related to that issue, enhancing the knowledge

base. This proactive approach ensures that frequently

asked questions are readily available to all patients,

thereby reducing repetitive queries and streamlining

the support process.

Quality Assurance (QA) teams should monitor

these tickets to identify and mitigate any risks to pa-

tient safety or data integrity. This comprehensive

oversight ensures that the support system not only ad-

dresses current issues but also continuously evolves to

enhance the efﬁciency and safety of the clinical trial

process.

Quality assurance (QA) emerges as a pivotal pro-

cess for effecting quality improvements in the con-

text of technological enhancements. Zhang et al. in-

troduced the QA Issue Tracking System (QAIT), a

centralized platform for systematic information col-

lection and management to identify and correct QA

errors effectively (Zhang et al., 2013).

A streamlined process for tracking issues and fa-

cilitating communication, along with a comprehen-

sive knowledge repository accessible to various stake-

holders in DCTs, further enhances risk management.

A strategic evolution in clinical trial monitoring is

evident with the adoption of Risk-Based Monitoring

(RBM), as reported by Barnes et al. (Barnes et al.,

2021). Capitalizing on increased connectivity and

data analytics advances, RBM represents a targeted

approach to error detection. In complex trial work-

ﬂows, such as those encountered in DCTs, RBM faces

distinct challenges, especially when integrating new

technologies and coordinating with multiple stake-

holders.

For DCTs, which rely on diverse systems and

processes, the imperative, extending beyond conven-

tional clinical trials, is to ﬁnd mechanisms to reduce

costs and establish robust quality control and issue

tracking processes.

Agraﬁotis et al. demonstrated that centralized

monitoring activities have the potential to identify a

substantial proportion (95%) of the ﬁndings revealed

Technology Support System and Review Process for a Decentralized Clinical Trial: Trials@Home, RADIAL DCT as Case Study

639

by on-site monitoring visits (Agraﬁotis et al., 2018).

This underscores the importance of tracking issues

and documentation, particularly in mHealth and home

environment technologies, where diverse technolo-

gies and vendors are integrated into a singular setup.

This complexity heightens the importance of provid-

ing comprehensive helpdesk support and knowledge

bases for CRAs, sites, and other stakeholders.

DCTs, being relatively novel, present distinct

challenges necessitating specialized helpdesk sup-

port. The work of de Jong et al., involving interviews

with European regulators and assessors of clinical tri-

als, has shed light on challenges related to DCTs,

including the use of technical devices and measure-

ments in at-home situations (de Jong et al., 2022). In

response, the Trials@Home project has established

a knowledge base and a helpdesk technology sup-

port system. This system serves the dual purpose of

assisting CRAs and sites in navigating technology-

supported DCTs and providing a robust tool for qual-

ity control, issue tracking, and compliance monitor-

ing.

3 RADIAL CASE STUDY

3.1 The Trials@Home Project

Clinical trials have long been a cornerstone of

evidence-based medicine, yet the traditional model

poses challenges in terms of patients burden, ge-

ographical constraints, and data reliability. The

Trials@Home project emerges as an innovative re-

sponse, seeking to transform this landscape by intro-

ducing a decentralized approach to clinical research.

At its core, Trials@Home leverages state-of-the-

art digital technologies, mobile medical devices and a

Mobile App to facilitate remote data collection. Pa-

tients are empowered to contribute to research en-

deavors from their own residences, alleviating the lo-

gistical and time-related burdens associated with on-

site visits. The integration of mobile medical devices

enables continuous, real-time monitoring, ensuring

a comprehensive dataset while bolstering patient en-

gagement and compliance.

The patient-centric ethos underpinning the project

not only fosters inclusivity but also addresses dispar-

ities in access to healthcare resources. By harness-

ing the capabilities of mobile medical devices, Tri-

als@Home offers a dynamic platform for researchers

to gather high-ﬁdelity, ecologically valid data.

The project further aims to establish a framework

for seamless collaboration between clinical investiga-

tors, technologists, and patients, ensuring a cohesive

research experience.

Through the Trials@Home project, we anticipate

not only an evolution in the execution of clinical trials

but also a paradigm shift in how we approach patient

engagement and data collection in medical research.

This endeavor holds the potential to democratize ac-

cess to research opportunities, drive efﬁciency, and

ultimately, accelerate the development of innovative

healthcare solutions.

3.2 RADIAL Design

The RADIAL study, as part of the IMI’s Tri-

als@Home initiative, exempliﬁes the innovation in

DCTs. Distinguished by its ”bring-your-own-device”

(BYOD) methodology, the study integrates conven-

tional, hybrid, and entirely remote trial formats, cater-

ing to diverse technological needs. Study patients use

their own mobile phones to install the Clinpal® Mo-

bile App to access the study’s interfaces. Addition-

ally, patients use mobile medical devices in the form

of a Mallya smart cap for insulin injection

, an Ac-

coCheck glucometer to control blood sugar

, and a

blood pressure meter to measure blood pressure val-

ues. The study is designed to test three discrete clini-

cal trial approaches in two different study parts:

• Part A:

– Arm 1: Adopts a traditional model with exclu-

sively onsite patient interactions.

– Arm 2: A hybrid model, blending onsite inter-

actions with remote engagements.

• Part B:

– Arm 3: A fully remote, decentralized arm,

facilitating all patient interactions from their

homes, exemplifying the full potential of DCTs

in clinical research.

3.3 RADIAL Technology

The scope of RADIAL is facilitated by a range of

DCT technologies and devices. Table 1 presents

the vendors, DCT technologies utilized, installation

types, and their relevance to speciﬁc study parts.

3.4 Requirements

In the search for an effective technology support sys-

tem for a large-scale trial like RADIAL, several key

requirements have been identiﬁed. The requirements

https://biocorpsys.com/en/our-products/connected-d

evices/mallya/

https://www.accu-chek.at/

HEALTHINF 2024 - 17th International Conference on Health Informatics

640

Table 1: Vendors and DCT technologies applied within RADIAL.

Vendor Technology Component Installation Relevant Part(s)

AARDEX MEMS Adherence Software

(MEMS AS®)

Custom A (arm 2), B

AARDEX MEMS® Mobile App Custom A (arm 2), B

eClinical Health Radial Study App Custom All

eClinical Health Clinpal® Platform (branded as RA-

DIAL Study Portal)

Conﬁgured with custom

components

All

Investis Digital RADIAL Study Website Custom B

Signant Health Smart Signals Telemedicine® (pre-

viously ‘Virtrial Telemedicine’)

Conﬁgured with custom

components

Signant Health SmartSignals RTSM® Conﬁgured with custom

components

All

have partly been derived from ﬁndings in the liter-

ature (see Chapter 2) and the requirements needed

to serve the RADIAL study design. Several tools

have been tested based on this. The ﬁnal selection,

the UVdesk open-source helpdesk solution, fulﬁlls

most of the requirements, providing a comprehen-

sive ticketing system and knowledge base. Further-

more, it offers the ﬂexibility to adapt the solution

to our speciﬁc requirements. The ﬁnal requirements

are that the system shall offer a centralized reposi-

tory of information, including answers to frequently

asked questions (FAQs), and provide an adaptable

and extensible content management system (CMS).

Moreover, system users should be able to contact per-

sons with detailed knowledge on speciﬁc topics of

the study in a customer support and service-oriented

manner. Different roles with varying access permis-

sions to the helpdesk system, such as content cre-

ator, ticket agent, or administrator shall be possible

to be deﬁned. The requirements speciﬁcally identi-

ﬁed for RADIAL include consolidating information

and knowledge from various channels into a single

helpdesk system, exchanging training materials and

expertise through eLearning, and imposing restric-

tions on access to learning resources by requiring a

password for the website to prevent general availabil-

ity.

4 SELECTION OF SUPPORT

SYSTEM PLATFORM

RADIAL support system is built on UVdesk, an open-

source helpdesk solution

. UVdesk provides a fully

functional project package, which can be conﬁgured

to the speciﬁc needs of the trial:

• A customizable, user-friendly dashboard for easy

access and navigation.

https://www.uvdesk.com/en/opensource/

• A helpdesk knowledge base (KB) that can be de-

signed to RADIAL’s needs i.e., to support Clinical

Research Associates (CRAs) and site staff.

• Backend access for modifying and expanding the

knowledge base, using a Content Management

System (CMS).

• A dashboard for ticket agents to manage and re-

spond to support requests efﬁciently and effec-

tively.

Additionally, UVdesk’s database structure facilitates

the extraction of key performance indicators (KPIs)

such as request count, response frequency, and aver-

age resolution time, through SQL queries. These met-

rics can be compiled into a report thereby providing

valuable insights into the system’s performance and

efﬁciency.

4.1 Customizing the Support System for

RADIAL

Figure 1 shows the landing page of the implemented

RADIAL helpdesk system after login. Users can

search for information and will be suggested related

articles containing the search key words in their meta-

data.

Figure 1 also outlines the structure designed for

RADIAL to provide an intuitive navigation, with the

ﬁrst level presenting topics as tiles for easy access.

The layout encourages self-service browsing through

various folders:

• Frequently Asked Questions (FAQs): Contains

categorized answers to common queries from

study sites and teams.

• Vendors: Hosts technical and speciﬁc documents

from organizations providing products or services

for RADIAL.

• Site/CRA Training: Includes materials speciﬁ-

cally for sites and CRAs, such as Site Initiation

Technology Support System and Review Process for a Decentralized Clinical Trial: Trials@Home, RADIAL DCT as Case Study

641

Visit (SIV) documents and technology manuals.

• Patient Training: Offers training resources for pa-

tients in different study arms, covering topics like

app usage and medical event reporting.

• Other Categories: Organizes information akin to

Site/CRA and Patient training in a topic-based

layout, including categories like Informed Con-

sent and Product & Logistics.

In addition, offers a quick search text box as well as

quick links to navigate directly to vendor, study, glos-

sary, and to the investigator meeting information.

The Tiles contain multiple categories, which in

turn include various articles, linkable across different

folders for relevance. Regular discussions in helpdesk

scrums also focus on enhancing the Knowledge Base,

especially the FAQs, based on emerging ticket issues.

4.2 Support System Roles

To streamline operations, we have established ﬁve

distinct user roles. Each subsequent role encompasses

the permissions of the preceding ones, plus additional

capabilities:

• Content Creators: Typically, CRAs and tech-

nical support staff, they organize and add to the

knowledge base. Published content appears on the

front-end (Figure 1), while drafts are for internal

use.

• Ticket Creators: CRAs and clinical site support

staff can create and edit tickets, with various types

like process or app-related issues. Ticket type, site

ID and patient ID are required for additional con-

text

• Ticket Agents: In addition to creating tickets,

they can respond, reassign, or modify ticket sta-

tus. They enjoy unrestricted ticket management.

• Administrators: Responsible for user manage-

ment, including adding, removing, and modifying

roles and permissions. This role is primarily held

by FHJ’s technical support staff.

• Account Owner: The initial system user, usually

an FHJ developer. This role has administrative

rights but uniquely, cannot be removed from the

system.

4.3 Workﬂow Integration

In conventional, hybrid, and decentralized clinical tri-

als, the support chain typically operates as follows:

1. Study patients approach clinical support staff or

Clinical Research Associates (CRAs) with in-

quiries.

2. Site personnel respond or direct their questions to

CRAs.

3. If an immediate answer isn’t available, both site

users and CRAs can utilize the Knowledge Base

(KB), either by browsing topic folders or using the

free text search ﬁeld, as illustrated in Figure 1.

4. While the KB encompasses comprehensive re-

sources like manuals, training materials, videos,

and guidelines, some queries may remain unre-

solved. In such instances, clinical site support

staff or CRAs initiate a ticket through the RA-

DIAL helpdesk.

5. Ticket agents then take responsibility for man-

aging these requests via the helpdesk’s ticketing

dashboard.

Ticket agents in the RADIAL trial’s support system,

adhering to the coverage plan, manage tickets through

the ticketing system efﬁciently. They either assign

tickets to themselves or to another more experienced

agent to address the speciﬁc issue. Upon assignment,

automated email notiﬁcations are sent to the respec-

tive agents.

Familiarity with the knowledge base content en-

ables agents to direct users to relevant informa-

tion or offer additional support. In scenarios where

the knowledge base lacks the required information,

agents have two options:

• discuss the issue in the weekly helpdesk scrum

and RADIAL core study team meeting, or

• consult with study team members involved in

protocol design, technology setup, or User Ac-

ceptance Testing (UAT). If necessary, they may

also seek assistance from the technology provider,

who will handle the issue in their ticketing system.

Upon resolution, the third-party vendor informs

the RADIAL helpdesk, ensuring proper documen-

tation and closure of the ticket.

Ticket agents have the capability to include listed con-

tacts as collaborators on a ticket. When agents re-

spond to a query, their response is automatically dis-

patched to both the user’s and collaborators’ emails.

Users or collaborators can conveniently respond back

directly through their email. Each response triggers

an automatic email notiﬁcation to the agent, ensuring

they are promptly informed. The ticketing dashboard

facilitates seamless communication, allowing agents

to view and reply to user responses. This interac-

tive process, featuring email notiﬁcations to all par-

ties, continues until the ticket creator’s inquiries are

fully resolved.

HEALTHINF 2024 - 17th International Conference on Health Informatics

642

Figure 1: Start page of the RADIAL helpdesk knowledge base.

4.4 Help Desk Tickets and Issues

Review and Classiﬁcation

To effectively manage help desk tickets in the RA-

DIAL study, a comprehensive approach is adopted.

All help desk tickets, regardless of their status, are

exported into a global issues tracker. This tracker

undergoes tier review by the technology governance

team, overseeing the technological aspects of RA-

DIAL, and the Quality Assurance team, focusing

on patient and data risk management. Operational

teams also contribute to this process, thereby ensur-

ing all technology-related issues are centralized in this

tracker. The Governance team classiﬁes issues into

distinct categories, as outlined in Table 2. The classi-

ﬁcation determines the subsequent handling process.

”Bugs and Errors” are given high priority, potentially

triggering immediate or scheduled software updates

based on impact and risk analysis. ”Process-related”

tickets are important and are communicated to clin-

ical operations. ”Technical support” issues may en-

hance the Knowledge Base and other published ma-

terials. ”User Access and Permissions” span a range

from straightforward issues, addressed with prepared

responses, to complex ones necessitating detailed re-

view or vendor escalation. Lastly, ”General Inquiries

and Information” cover non-technical questions and

those not ﬁtting into other categories, ensuring a com-

prehensive and structured approach to ticket manage-

ment.

5 OVERSIGHT

5.1 KPIs and Reports

As articulated in the work of (Bertram et al., 2010),

issue trackers within the helpdesk context exhibit var-

ied perspectives among stakeholders. Notably, project

managers tend to focus on high-level summaries,

while the quality assurance group categorises cases

by project area or type. Enhancing existing knowl-

edge assets necessitates the establishment of key per-

formance indicators (KPIs). A survey conducted by

(Rastogi et al., 2013) examined the signiﬁcance of

those indicators, soliciting ratings from two compa-

nies and distinguishing between the expectations of

different roles, such as bug reporters and bug owners.

Currently, foundational metrics such as the number

of high-priority bugs, assigned bugs, or resolved bugs

serve as the basis for RADIAL KPIs. Additionally,

metrics like Priority Weighted Fixed Issues (PWFI),

which not only quantify the number but also consider

the priority of bugs per owner, are under consideration

for analysis pending the availability of more data.

The following KPIs for Issue Tracking are actively

employed in RADIAL:

• Number of Issues per day per month

• Number of Issues by Type

• Number of Issues by Status

• Number of Issues by Priority

• Number of Issues by Replies

Technology Support System and Review Process for a Decentralized Clinical Trial: Trials@Home, RADIAL DCT as Case Study

643

Table 2: Issue classiﬁcation like performed by Governance team.

Issue class Description

Bugs and Errors This category includes all issues related to software or system bugs, glitches, and

errors. It covers problems that result from defects in code or applications.

Process-Related Issues falling under this category are related to business processes, workﬂow, or pro-

cedures that may need improvement, clariﬁcation, or adjustment. These issues are not

necessarily technical but affect how tasks are executed.

Technical Support Technical issues that require help desk assistance or technical support team fall into

this category. It includes hardware, software, network, and other technology-related

problems.

User Access and Per-

missions

This category encompasses issues related to user access, permissions, authentication,

and authorization. It includes requests for access changes and password resets.

General Inquiries

and Information

For non-technical questions or general inquiries that don’t ﬁt into the other categories

Not relevant for RA-

DIAL

Tickets not related to RADIAL

• Number of Issues by Agent

• Average Age of Issue

The process for generating those KPIs can be de-

scribed into three phases which are shown in Figure

Phase 1: Export data from the Issue Tracking

Database. The initial step involves extracting data

from the relational SQL database to create a spread-

sheet, facilitating further processing for reporting pur-

poses. Variables such as ID, status, priority, type,

replies, last reply, issue age, and agent-customer as-

sociations are included.

Phase 2: Development of a Python Web applica-

tion for KPIs. Subsequently, a Python Dash web

application was designed to transform the spreadsheet

into a comprehensible report of KPIs. This phase also

entails additional preprocessing including the calcu-

lation of the average issue age and replies.

Phase 3: Expansion of the Web Application for the

Knowledge Base. In this phase, the existing appli-

cation is expanded to incorporate top search keywords

for the current month as well as for all-time. This aug-

mentation aims to identify prevalent issues and con-

tribute to a more robust understanding of recurring

problems.

6 CONCLUSIONS

DCTs offer several advantages over conventional tri-

als, including reduced patient travel burden, enhanced

study accessibility, and the potential for less biased

Figure 2: Phases for generating statistics of the RADIAL

Issue Tracking System and the Knowledge Base.

and more diverse cohorts by accessing clinical studies

globally. However, designing studies with remote and

virtual components, such as telemedicine and mobile

health devices, poses challenges. Ensuring technolog-

ical stability and user self-sufﬁciency is crucial. Addi-

tionally, effective communication is required among

stakeholders from different sites and countries, in-

cluding site members and CRAs, while managing var-

ious technology providers with different service level

agreements and helpdesk availabilities.

We introduced a system for the RADIAL study

to address these challenges, comprising a helpdesk

ticketing system for multiple stakeholders and a Wiki-

like knowledge base documenting technology usage,

study procedures, training materials, and FAQs.

The system is currently undergoing testing and

evaluation, with additional results and insights to be

published. While supporting the RADIAL study,

the system facilitates clear process linking between

study personnel and different technology providers.

However, it has been observed that situations de-

manding immediate support, such as direct patient

phone interactions, may encounter challenges due to

HEALTHINF 2024 - 17th International Conference on Health Informatics

644

the extended communication chain involving multiple

stakeholders.

The helpdesk is restricted to a limited number of

users and will be enhanced in the future to increase

its scalability. Caching mechanisms and daily server

snapshots for backup purposes are currently being im-

plemented to speed up the user experience. If the

helpdesk experiences performance issues over time,

vertical scaling can be employed to boost the existing

capabilities (e.g. CPU, RAM) of the server. In the fu-

ture, the helpdesk will evolve by implementing load

balancing strategies across multiple servers. This will

efﬁciently distribute incoming requests, balancing the

network load and ensuring high availability by utiliz-

ing multiple servers in case of a server failure.

Despite challenges, documenting various issues

during the study for quality control and risk man-

agement is essential. The implemented system al-

lows for the collection and processing of technical

bugs, process-related issues, and facilitates updates

like new software releases.

Furthermore, the KB extends beyond the RA-

DIAL study and could potentially beneﬁt similar stud-

ies in the future. Patient access to the KB, currently

unavailable, could empower patients, aligning with

the trend of patient engagement. As Language Model

technologies like ChatGPT emerge, the KB may serve

as a domain-speciﬁc knowledge repository, enabling

the training of LLMs for helpdesk chatbots. This ad-

vancement could provide more speciﬁc and straight-

forward support, eliminating the need for users to

search diverse documents themselves.

ACKNOWLEDGEMENTS

This work has received support from the EU/EFPA In-

novative Medicines Initiative Joint Undertaking Tri-

als@Home (grant No. 831458). The Innovative

Medicines Initiative (IMI) website can be accessed

through the following link: www.imi.europa.eu.

DISCLAIMER

The research leading to these results was conducted

as part of the Trials@Home consortium. This paper

only reﬂects the personal view of the stated authors

and neither IMI nor the European Union, EFPIA, or

any Associated Partners are responsible for any use

that may be made of the information contained herein.

REFERENCES

Agraﬁotis, D. K., Lobanov, V. S., Farnum, M. A., Yang, E.,

Ciervo, J., Walega, M., Baumgart, A., and Mackey,

A. J. (2018). Risk-based Monitoring of Clinical Tri-

als: An Integrative Approach. Clinical Therapeutics,

40(7):1204–1212.

Barnes, B., Stansbury, N., Brown, D., Garson, L., Gerard,

G., Piccoli, N., Jendrasek, D., May, N., Castillo, V.,

Adelﬁo, A., Ramirez, N., McSweeney, A., Berlien, R.,

and Butler, P. J. (2021). Risk-Based Monitoring in

Clinical Trials: Past, Present, and Future. Therapeutic

Innovation and Regulatory Science, 55(4):899–906.

Bertram, D., Voida, A., Greenberg, S., and Walker, R.

(2010). Communication, collaboration, and bugs: The

social nature of issue tracking in small, collocated

teams. In Proceedings of the 2010 ACM Conference

on Computer Supported Cooperative Work, CSCW

’10, page 291–300, New York, NY, USA. Association

for Computing Machinery.

Bhatt, A. (2023). The revamped Good Clinical Practice E6

( R3 ) guideline : Profound changes in principles and

practice ! 6:167–171.

de Jong, A. J., van Rijssel, T. I., Zuidgeest, M. G. P.,

van Thiel, G. J. M. W., Askin, S., Fons-Mart

ınez,

J., Smedt, T. D., de Boer, A., Santa-Ana-Tellez, Y.,

and and, H. G. (2022). Opportunities and challenges

for decentralized clinical trials: European regulators’

perspective. Clinical Pharmacology & Therapeutics,

112(2):344–352.

Holmner,

A., Ebi, K. L., Lazuardi, L., and Nilsson, M.

(2014). Carbon footprint of telemedicine solutions -

unexplored opportunity for reducing carbon emissions

in the health sector. PLoS ONE, 9(9):e105040.

Jain, B., Bajaj, S. S., and Stanford, F. C. (2022). Random-

ized clinical trials of weight loss: Pragmatic and digi-

tal strategies and innovations. Contemporary Clinical

Trials, 114:106687.

Rastogi, A., Gupta, A., and Sureka, A. (2013). Samiksha:

Mining issue tracking system for contribution and per-

formance assessment. In Proceedings of the 6th In-

dia Software Engineering Conference, ISEC ’13, page

13–22, New York, NY, USA. Association for Comput-

ing Machinery.

Subaiya, S., Hogg, E., and Roberts, I. (2011). Reducing

the environmental impact of trials: a comparison of

the carbon footprint of the CRASH-1 and CRASH-2

clinical trials. Trials, 12(1).

Zhang, Y., Sun, W., Gutchell, E. M., Kvecher, L., Kohr,

J., Bekhash, A., Shriver, C. D., Liebman, M. N., Mu-

ral, R. J., and Hu, H. (2013). QAIT: A quality assur-

ance issue tracking tool to facilitate the improvement

of clinical data quality. Computer Methods and Pro-

grams in Biomedicine, 109(1):86–91.

Technology Support System and Review Process for a Decentralized Clinical Trial: Trials@Home, RADIAL DCT as Case Study

645