ZS is a management consulting and technology firm, focused on transforming healthcare and beyond. The firm works with some of the top pharmaceutical, medtech and life science companies globally and Qin Ye, a principal at ZS, leads its real-world evidence team. A trained physician and data scientist, Qin has over 20 years of health informatics and data analytics experience in both life sciences and healthcare. He has built a world-class, real-world evidence team at ZS, and has helped many top 40 pharma clients leverage the power of real-world data and data science.
Here, Qin tells us more about his background, and shares his insights on current clinical trial trends and the outlook for clinical trial data.
I set the goal to become a physician at an early age, largely because I got sick quite a lot and happened to see doctors and nurses more often than any other profession. I saw medicine as a career where I could really help other people. But over time, I also developed a genuine interest in data sciences and technology. When I was practising as a surgical resident, I felt I was at a crossroads. If I combined my two passions – medicine and data – it seemed that I could improve healthcare and tackle patient outcomes on a larger scale. This led me back to graduate school, training in informatics and outcome research, and since then I’ve worked in healthcare and life sciences throughout my whole career.
At ZS, our work in research and development is focused on this – how we can leverage data and improve efficiency, as well as generate scientific evidence proactively and systematically. When we partner with organisations, we have this big picture in mind – to enable innovation by understanding the needs of all the stakeholders in the ecosystem, always with the aim of improving healthcare and patient outcomes.
Where we’ve got to: Clinical Trial Trends
In the clinical research space, there are a few exciting trends we’re seeing that involve pharma, research sites and life sciences businesses constantly looking at better ways to conduct research.
Trend #1 – Increased focus on collaboration
We’re seeing a noticeable clinical trial trend in pharma, research sites and regulators increasingly looking at innovative ways of collaborating to accelerate drug development, while improving the reliability of regulatory approval. This is very encouraging, because not only can effective treatments reach patients faster, but ineffective treatments can fail faster, thus saving time, effort and money.
We’ve certainly seen a mindset shift across both senior executives in pharma companies and in healthcare settings, as they look at how they can collaborate more effectively. Up until this point, this has been largely on a one-off project basis. We hope this will grow into more comprehensive, at-scale collaboration across the industry.
Trend #2 – Leveraging digital technologies
We see all parties involved in clinical research – at research site and sponsor level – as being deeply interested in ways they can use digital technologies to reduce the reliance on manual operations. This is connected to trend #1, because all parties are also striving to look for better partnerships to accomplish this aim.
The current ways of conducting clinical trials include lots of duplicative, fragmented and manual processes. A clear example is the way that, typically, data is entered into Electronic Health Record (EHR), systems and then there is duplicate manual effort to enter the data into Electronic Data Capture (EDC) systems for a trial. There is a strong need to free up time for clinical researchers and physicians to help support a clinical trial, instead of them needing to spend time working with two completely different systems in this wasteful way.
It’s exciting to see the wider adoption of EHR systems in healthcare settings and, specifically, HL7 FHIR standards being embraced and adopted within EHRs. Healthcare entities are increasingly doing this to accomplish broader objectives, and for clinical trials in particular, this adoption brings the potential to increase efficiencies through the introduction of EHR-to-EDC data transfer.
I hope that this new bridge between EHR and EDC will also help drive further transformation of EHRs, so that they are increasingly designed with the collection of regulatory-grade data in mind. This data is needed to support scientific research, as well as for treatment and diagnostic decision-making. Coming back to trend #1 again, I also see real potential for this type of use of technology to be a catalyst for better, more reliable, and consistent collaboration between pharma companies and health systems.
Where we’re going
To enable the kind of accelerated adoption of technology that we really need to see to truly leverage the value of healthcare data, I strongly believe that the industry needs to take a more long-term approach.
The pharma industry needs to take a more forward-looking position, to be the enabler of digital technologies. And healthcare entities need to recognise the long-term benefits of improving their research infrastructure.
Too often, the focus is on seeing a return on investment today or tomorrow, but if we really want to drive change in clinical trial trends, both sides need a full-hearted adoption of the innovations that will bring long-term benefits to all. That will require financial commitments, as well as a true partnership and collaboration mentality across the whole industry.
If we can achieve this, the reward will be great. With this kind of approach, within five years, we could see the full convergence of patient care and clinical research trends:
* The lives of patients with cancer or rare diseases being saved while participating in clinical trials.
* A lot of the patient burden, with duplicated visits to healthcare entities, being reduced.
* The additional manual processes – on both the healthcare and sponsor side – being significantly reduced or eliminated.
* Truly effective, efficacious, and safe products coming to market much more quickly.
* The enablement of key healthcare players to eliminate certain diseases and improve patient outcomes across the board.
One further element that is key to ensuring this vision becomes a reality, is to really support and incentivise clinicians, so they can see the value of the healthcare data they capture.
Technologies such as artificial intelligence (AI) and natural language processing (NLP) could help improve the quality of data captured (especially where, currently, physicians’ workflows tend to favour unstructured note-taking). Then, the data itself being used beyond its current scope, for much broader meaningful use cases, would allow clinicians to further experience the added value it can bring.
Examples of how easy access to high quality, reliable data would save clinicians vast amounts of time, include longer term outcome measurement and safety monitoring. Voluntary follow-up studies, for example, are even more labour-intensive and inefficient than standard clinical trials. Advances that would see a more efficient use of data for these, would translate into significant tangible time-savings for clinicians.
To both clinical trial sponsors, and healthcare settings and physicians I would say – these are the benefits that are within our grasp. We just need to grab them.
ZS and IgniteData are partnering to transform patient data automation for clinical trials. In Feb 2022, we announced a multimillion dollar strategic partnership to improve the efficiency of clinical research through automation and use of real-world data. Key to this is our system-agnostic EHR to EDC solution, Archer.
A principal at management consulting and technology firm, ZS.
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