As part of our series on clinical data collection and management, we asked a range of clinical professionals from pharma, CROs, technology providers and associations about the biggest challenges around clinical data they face. We gathered answers from nine of them here. Explore other posts from the clinical data series here.
Julianne Hull, CEO, WenStar Enterprises
'With wearables the volume of data collected could be enormous. How much will it cost to collect and manage this data? Do we have the ability to do this cost effectively yet? For electronic health records is there a way to access the information anonymously and will patients accept this? If we think of all the discussions over the past few weeks regarding Facebook, will patients be much more protective of their personal health data?
Clinical trials are getting more complex and increasing amounts of data are being collected. If there was a way of using electronic health records and wearables to have this data available and validated in real time this could really push clinical trials forward. Is this all a dream?'
Bruce Hellman, CEO/Co-Founder, uMotif
'When talking about challenges it’s worth keeping in mind that this approach is already proven to work at scale. Just taking uMotif as an example, we have captured over 65 million data points from over 20,000 participants with our platform across 21 conditions.
The challenges are not from a technology-readiness standpoint. The infrastructure exists and proven platforms are available. The challenge now is to ensure that patient-centric technology is seen as the essential core of a study, not an optional extra. Your favourite high street store no longer thinks in terms of ‘commerce’ and ‘e-commerce’ – both channels are part of their core business. Likewise, the time is now for digital patient experience to be seen as business-as-usual within clinical research.'
Read Bruce Hellman's full article on enabling Bring Your Own Device clinical data collection.
Dennis Salotti, Vice President of Operations, The Avoca Group
'The greatest challenge associated with EHRs is the fragmentation of healthcare data across paper and electronic systems, as well as across electronic systems that are not inter-operable, do not conform to a common standard and are kept in isolation from one another due to an absence of data-sharing agreements between organizations and governments. These barriers threaten delivery of high quality data through the risks of incomplete data and inaccurate translation of EHR data into the clinical trial database.
These are not, however, insurmountable challenges; we have seen standards emerge and organizations build collaborative structures to share data. For transformative influence on the clinical trials industry this must occur at a much greater scale. Consortia - pre-competitive collaboratives that unite Sponsors, CROs and the healthcare industry with a common purpose of establishing proactive approaches to managing data across the continuum of clinical research and clinical care - are an effective vehicle to realizing this opportunity for technological innovation to drive greater efficiency and higher quality in clinical trials.'
Yvonne Chan, MD, PHD, FACEP, Director, Center for Digital Health, Associate Professor, Genetics and Genomic Sciences & Associate Professor, Emergency Medicine at Icahn School of Medicine at Mount Sinai
'Data privacy, security, and transparency, collection, storage, and use are all challenges. Refining the informed consent process (including electronic informed consent) and cracking the nut on study retention are two other interesting areas to explore.'
Sheila Antonio, Sr. Director, Data Management of Precision for Medicine
'There is discussion about 21CFR Part 11 compliance issues, HIPAA, subject compliance, technical failure, technical support, device variability and a number of other unknowns.
When we look at the challenges we faced with data collection in the past, we also had to overcome those same issues, all resulting in success and progression. The future has promise and technological advancements in the clinical research industry are inevitable. It’s an exciting time to see what will evolve and how our method for collecting data will become more streamlined and accurate.'
Raphaela Schnurbus, PhD, Clinical Solutions Director, OPIS
'We still need to overcome the gap between what is possible thanks to new technology and what is currently implemented. New tech is not applicable everywhere and to everybody (eg older patient populations, dementia trials and paediatrics).
GDPR also brings new privacy issues for sure. Let’s hope that data standardization will really lead to more data sharing between all and that we aren’t creating an environment where fierce competition for data is going to push patient-centricity out the window again.'
Nick van Terheyden, MD (aka Dr Nick - @drnic1), Founder & CEO Incremental Healthcare
'We live in interesting and exciting times but there are still many obstacles and challenges to overcome that arise from the capture of so much data from so many different sources. Integrating this data will require significant effort and focus on the normalization of the data to allow for the accurate and reliable comparison of data derived from so many different sources, systems and devices.
As we integrate more data the presentation and visualization of this information will challenge our brain processing power and new techniques and tools will be essential to accelerate our understanding. Expect to see new tools that may automate the scientific process of teasing out the insights. At a minimum new tools will be required to present and manipulate information to present it in forms that our brains can see the causal connections.
For clinicians they will need to stop thinking in traditional terms and acting with yesterday’s logic and rather adapt and expect things to change, and quickly. This requires a change in the medical education system still anchored in old principles of didactic methods and the teaching, testing that relied on the individual to be the expert in the knowledge, care and decision making of medicine.
As Peter Drucker said, "In times of change the greatest danger is to act with yesterday’s logic".
For the clinical community there can be no pause or “wait and see”, for they risk being relegated to observers of the new age of medicine rather than key contributors and navigators of the exciting rapidly changing and hopeful new age of what is possible in medicine.'
Sarah Iqbal, Head of Digital Life Sciences, Biotaware
'Adoption of revolutionary advancements in healthcare has not been without challenges. Some of the major challenges that still need to be overcome are:
- Identifying and communicating the value that digital technologies offer
- Defining reimbursement models for these digital solutions from a payer, provider, or consumer perspective
- Challenging difficult for adopting organizations, especially sponsors, to determine which digital health company to partner with have done their due diligence to assure proper healthcare regulation compliance
- Digital health companies need to learn how to become certified in designing, developing, and validating data from unregulated devices in clinical trials since these companies are less familiar with the regulated industry
There are other easier challenges that need to be overcome, most with feasible solutions, including:
- Higher technical effort (therefore more expensive than paper)
- Not all investigators, study staff or patients are familiar with modern technology
- As with every electronic hardware or software, there can be failures and break-downs
- Online connectivity or wireless networks need to be available at all times
- Data breach in sensitive clinical and health data'
Anna Matranga, PhD, MBA, CA-AM, AMC Alliances & Consulting
'Some of the challenges being addressed as we move forwards are:
- Due diligence and selection of technology: The chosen data collection technologies must support the business strategy and enable the investigator site and patient engagement. Plus, the availability (internally and/or externally) of data analytics capabilities to demonstrate therapeutic value, personalised medicines and reimbursement potential.
- Implementation and integration: Is this R&D only or company-wide? What is the compatibility of these technologies with internal IT platform architecture and systems?
- Implementation management: There must be availability of adequate scientific and IT resources with relevant experience and competencies, plus flexibility in the management of fast changing technologies. This requires internal adaptation to new collection methods and the continuity of long-term data collection in clinical/post-marketing/observational studies.'
Explore other posts from our clinical data series here.