The Evolving Landscape of Clinical Trial Data

April, 2022
The Evolving Landscape of Clinical Trial Data

Over the last 50 years, the pharmaceutical industry has made some stunning advances. At the same time, the technologies used in healthcare have slowly but steadily been catching up to our digitised world, and transitioning from paper-based health records to Electronic Health Record (EHR) systems.

But, at times, the place where these two worlds come together – clinical trials – has felt like it was stuck in a time warp. Surveys going back as far as 2009 show that, according to hospitals, up to 50% of data collected in Electronic Data Capture (EDC) systems used for clinical trials is duplicated in the hospital’s EHR system.

Historically, with no effective solution for interoperability of these clinical trial systems, what has resulted is a painstakingly laborious manual process.

Current processes in clinical trials

The current methods for entering data into the EDC system for a clinical trial typically involve manual re-keying of data from EHR system to EDC system. For hours on end, someone will be employed to duplicate data from one system to another. Another manual check is carried out, known as Source Data Verification (SDV), where a sample of data is cross-checked for quality control. At this stage, it’s not unusual for the Clinical Research Associate (CRA) carrying out the SDV, to also be accompanied and observed by a hospital study coordinator.

In contrast to these methods, which have remained unchanged for years, studies themselves are becoming more and more complex. Recent studies have shown that, in a typical phase three oncology trial, an average of 3.6 million data points will be generated (three times the data collected by late stage trials 10 years ago). When each of these data points is copied in manually from another system, then cross-checked manually by up to two other people, you can see how the time and cost of this process quickly spirals.

Around 20% of the total costs of a study (which can translate to between $16M-24M) is allocated to duplicating and verifying data.

The financial cost of the existing processes is not the only issue. One of the noticeable impacts of the past few years is that research timeframes have been accelerated. The Covid-19 pandemic has highlighted the benefits of creating an environment where clinical trials can be progressed more quickly, and expectations – of clinicians and patients alike – have changed. Increasingly, people are not willing to wait the extended time that siloed systems clinical trials take. And pharmaceutical companies, to their credit, have been working harder to make things easier for clinicians and build more productive relationships with them.

A vision: interoperability and clinical trials

The inefficiencies of the current handling of data in clinical trials lead to an obvious question: Surely there must be a solution to this? Can’t we automate this process somehow?

Spoiler alert – yes, there is, and yes, we can. The solution is in achieving interoperability between the systems used in clinical trials, so that EHR systems can more easily ‘talk to’ each other, as well as to EDC systems. But it has been a long journey to get to this point. A few threads have been woven together over the years, to place us where we are today – at a point where we have the potential to revolutionise the way we do clinical trials.

Adoption of EHR systems

Over the last 50 years, a critical development has been the digitisation of health records themselves. Our blog on EHR systems takes you through a brief history of events, and introduces three of the key players in the industry.

The strides in moving from paper-based health records to electronic health records that have been made since the 60s (when the concept of EHRs was first introduced), have been made through considerable effort from healthcare providers and legislators alike.

Advances in EHR systems have largely been initiated in the US, though the rest of the world has followed. Initially, adoption began to spread thanks to the increased use and reduced costs of computers themselves, though the transition from paper-based records was still slow. Then, largely thanks to legislation aimed at driving up adoption, EHR systems experienced a sudden acceleration in adoption between 2009 and 2014. As of 2018, 98% of hospitals in the US either had an EHR or were planning for one.

Much of the rest of the world has been slower to adopt EHRs but is now beginning to catch up. In the UK, for instance, there has been something of a stop-start journey, as attempts at a national rollout programme faltered in 2011. Now, adoption of EHR systems in the UK is being driven largely by the more ambitious NHS Trusts, in particular, those that see that a sophisticated EHR system leads to eSource-readiness, and thus, a more attractive site for conducting clinical trials.

The drive for eSource

What eSource-readiness is and how it applies to clinical trials is a separate article. In brief, however, it describes the availability of health data in a digital format. From a regulatory perspective, this is preferable in clinical trials, in part because the information is easily readable (no translating doctors’ handwriting), attributable (with an audit trail of who has entered data, and when), and contemporaneous/current (as it facilitates real-time entry).

For hospitals and healthcare providers, the benefits to staff and patients of having an easy-to-use electronic system for managing and accessing patient data are clear. But, for those hospitals looking to make themselves a more attractive site for conducting clinical trials, eSource – and thus, an EHR – is now increasingly a must-have.


Yet, as we’ve already highlighted, the existence of even the most sophisticated EHR doesn’t mean plain sailing for clinical trials. Clinical trial sites, trial sponsors and regulators have long been aware that the benefits of having eSource data are significantly reduced when that data is then being manually transcribed into another system. That process, as well as being time-consuming and costly, is prone to human error.

So, over the last decade or so, a number of pan-European projects have looked into the potential for taking better advantage of the digitised data already in EHRs for the purposes of clinical research. A few of those projects and activities include:

  • The Electronic Health Records Systems for Clinical Research (EHR4CR) project (2011-16). Under the umbrella of Innovative Medicines Initiative (IMI), this project involved numerous research institutions and companies including AstraZeneca, GlaxoSmithKline, Merck and Sanofi. It aimed to tap into the emerging opportunities from the digitisation of patient records for clinical study design and recruitment. It resulted in a proof of concept for remotely and securely querying EHRs, as well as a cost-benefit study that highlighted the financial benefits to be gained by the pharmaceutical sector.
  • The European Institute for Innovation through Health Data (i~HD) was formed in 2016. i~HD shares good practices and tools and brings together stakeholders in the industry to encourage cooperation in the trustworthy use of high-quality health data. They also provide training, education and certification programmes to ensure the quality and good governance of organisations handling health data.
  • The EIT Health EHR2EDC consortium was formed in 2017. This moved things on from clinical trial design and recruitment – the focus of the EHR4CR project – to study conduct. It was a collaborative effort driven by Sanofi and i~HD, industry partners, hospital partners, and technology providers, and has developed standards, mapping, and validation for the use of automatic data capture from hospital records into EDCs.
  • The TransFAIR study ran from 2018-19. Sanofi, AstraZeneca, Jansen and UCB worked with four hospitals in four different European countries to define requirements and plug in technology to run mirror studies of real-world clinical trials. The study demonstrated 37% of the necessary data was successfully transferred from EHR to EDC.

These studies and activities successfully proved the concept of an automated transfer of data – EHR2EDC – as well as highlighting the very tangible benefits that using this approach could have. Between them, they showed substantial financial benefits to be had: up to $6M per trial (for a 400-patient oncology trial) from the cost savings in reduced time spent on data entry and validation, and, additionally, up to $2516.8M in gains for the oncology sector as a whole, due to the expected faster time to market for drugs. Whilst no-one would suggest that these savings should result in hospitals being paid less for their work conducting trials, the added efficiencies for hospitals would free up staff for more valuable work and, potentially, operating more studies per study site.

The technology that allows for interoperability

While the work looking at and promoting the possibilities that EHR2EDC could bring has created an appetite in the clinical trial world, the technology that would allow for interoperability between the systems needed to catch up.

It is within the last eight years that technologies paving the way for interoperability have been introduced. HL7 FHIR and SMART on FHIR are the new tools at our disposal that allow for an effective, scalable solution for EHR2EDC.

HL7 FHIR is a set of standards that allows software developers to make sure the data held in their system is securely and easily accessible. And SMART on FHIR is an Application Programming Interface (API) that allows for EHRs using HL7 FHIR to ‘talk to’ other systems more easily. In 2020, legislation made it compulsory for all EHR systems being developed in the US to use HL7 FHIR and include SMART on FHIR.

This has been a major turning point, as all the widely-used EHR systems now employ this technology (or are implementing it in due course). It means that all EHRs will have a standard way of packaging up and storing their data, as well as a standard way to ‘plug in’ to this data – the systems talk the same ‘language’, if you will – a crucial change to the potential to introduce interoperability of clinical trial systems.

Piloting interoperability

It’s through these changes to the landscape of clinical trials, that we are able to now grasp the possibility of clinical trials without the layered inefficiencies of a manual EHR to EDC copying process. With increasing numbers of hospitals boasting eSource-readiness, and EHR systems speaking the language of FHIR, the groundwork has been laid for a tool that can bridge the gap between the EHR and the EDC. Achieving an automated transfer of this data would, in the process, save thousands of hours of work, and millions of dollars, per trial.

At IgniteData, our EHR2EDC software Archer, takes full advantage of the growth in adoption of EHRs, the appetite for EHR2EDC created by past studies, and the new possibilities for interoperability created by HL7 FHIR and SMART on FHIR. Archer is designed to use any EHR’s SMART on FHIR API to allow for an automated, but controlled and secure transfer of data to an EDC system.

In 2021, our collaboration with AstraZeneca was formed to pilot the use of Archer in clinical trials. Running Archer in parallel with traditional methods at University College London Hospitals NHS Foundation Trust (UCLH), the pilot uses synthetic non-sensitive patient data in a mirror of a real study. It has been testing and measuring the efficiencies gained in time, cost and effort, before scaling to roll out the solution across other hospitals in the UK and Europe. The results of this pilot will be published soon, but we can, for now, say that the results are very promising!

Realising the potential of real-world data

In addition to the promise that these developments will bring to traditional clinical trials, the drive for better interoperability opens up many exciting possibilities for how we use real world data in health care. There is already a growing trend for using real world data – that is, data that is captured from the real world, rather than under trial conditions. As the adoption of EHR systems continues to grow, and health data is increasingly recorded digitally in ‘real-time’ – whether by direct input into the EHR by clinicians, or through being captured on smart devices – we will have a growing body of real-world data at our fingertips. This data will increasingly be used to design more intelligent research and drive clinical trial efficiencies.  By combining that wealth of information with increased interoperability between systems, and adding in the use of predictive AI models and analytics tools, there is endless potential to enhance our understanding of diseases and support more complex and innovative clinical trials.

Are you new to IgniteData?

IgniteData is the company shaping the future of clinical trials. Through our innovative digihealth platform, Archer, we are enhancing interoperability between Electronic Health Records (EHR) and key research applications such as Electronic Data Capture (EDC). Find out more about Archer – the world’s first truly agnostic, scalable EHR2EDC solution – here.

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