We all know that real-world data (RWD) from electronic health records (EHR) could boost clinical trial efficiency and improve patient outcomes – so what’s holding us back?
It’s been more than two decades since the ground-breaking potential of using electronic health records (EHR) to inform clinical research was first mooted.
Since then, progress has been slow, but the industry now has everything it needs to close the feedback loop between science, evidence, and care, said speakers at a recent Conference Forum webinar.
The key, according to Ryan Mogg, senior director of real-world data and clinical research at Cerner; Michael Ibara, chief data officer at Elligo; and Andy Stankus, general manager of real-world evidence at Kantar Health, was collecting and connecting the right data, and supporting sites to get involved.
More than a technology problem
We have known the potential of real-world data (RWD), captured by EHRs, for decades, said Ibara, highlighting a quote from the late 1990s paper, The Evolution in Healthcare Records in the Era of the Internet.
It pointed to the “many advantages” of the EHR when carrying out clinical research, such as eliminating the manual task of extracting data from charts and “making research data collection a by-product of routine clinical record keeping”.
Said Ibara: “If you compare the progress your phone has made since 1998, and the progress we have made in using healthcare data for clinical research, there’s a dramatic difference. If it were just a technology problem, we would have solved it by now. There are other factors involved.”
There are a number of things industry needs to do to “make this innovation stick”, and the first is changing the way it approaches study recruitment.
“In today’s clinical research areas, with the complexity of regulations, clinical trials, and the types of drugs we are trying to bring to market, we need a lot of patients,” he said. “But with our traditional methods, every site is their own fisherman: they set out their pole and they wait for the fish to come by.”
It’s an approach that makes enrolment a lengthy “trickle down” process that often contributes to delayed study initiation or even study discontinuation.
But access to large-scale EHR data can streamline the whole process by allowing researchers to quickly locate and identify patients with the right inclusion criteria, and then enrol them all at once.
There are barriers to this approach, not least the recent “data land grab” that means no one vendor or organisation has access to all the patients needed for a clinical trial. This is particularly true when looking at rare diseases or personalised medicines, said Ibara, adding: “We have to partner to find that scale.”
Capturing possible inclusion data is only part of the puzzle, he went on, explaining there was a need to “bridge the gap between data and humans”.
“Our goal is placing humans in clinical trials, so just capturing the data isn’t enough. We need to convert the sites, but also provide the infrastructure they need,” he said.
Mogg said that most healthcare systems wanted to take part in research, but simply did not have the wherewithal to do so.
“There is a lot of interest in clinical trials, but maybe not the administrative staff to handle them, or the training around things like GCP,” he said.
There are often concerns around how to comply with regulatory filings and submissions, or a lack of familiarity with the research environment. Sites often also need to be able to demonstrate a steady stream of clinical trial work to justify the investment.
Collaborative projects, such as the Cerner Learning Health Network, which all three companies are involved, offer the support willing sites and healthcare systems need to take part.
“It is a nationwide network of provider organisations who have agreed to allow access to their data, and who are ready and willing to accept clinical trial, quality improvement, and outcomes research opportunities,” said Mogg.
“It really minimises the lift on the parts of all parties, and accelerates their opportunity to participate, even if they haven’t historically been a research organisation.”
Ultimately, it’s about making sure the sites that hold the data have everything they need to make use of it, from the right software to a principal investigator.
Closing the feedback loop
Harnessing the power of RWD from EHRs is not a one-way street: the sector also needs to ensure insights from routine care can be used to guide future research.
Stankus said: “Typically, we take a linear view that science drives evidence, and that this evidence leads to care… unfortunately, we see a lot of missed opportunities, waste, and harm throughout the process. The patient experience often doesn’t feed back into science and evidence.
“What we need to move forward is an integrated clinical care programme… where we are continuing to learn and evolve, and to understand the best thing for patients, as well as for clinicians, clinical workflows, and communities.”
Barriers to this approach include a lack of data quality and data completeness in some EHR systems, he told delegates.
“Research studies are designed to understand specific data, they have data dictionaries that are standardised across sites, and they collect all the information for the outcomes.
“EHR, on the other hand, was originally designed for billing; there are time pressures that clinicians are under, there are unstructured formats, and varying data coding between health systems. All this makes it challenging to extract useful information,” he said.
Greater standardisation of data fields and codes, as suggested by the FDA, could help to shift this dial, and ensure insights are not wasted.
“There are many data that aren’t captured in EHR systems that could really enhance their value, whether it’s understanding certain symptoms, severity, or the worsening of control in certain situations.
“Patient reported outcomes, as an overall umbrella, is an area where EHR could really build capacity and understanding on how people, throughout the process, are experiencing their health conditions, not just as a patient, but frankly, as a whole person.”
Aligning the data
It has been a long time coming, but now, with the right technology and outlook, the industry is at a “tipping point” in terms of harnessing RWD to improve patient outcomes, said Stankus.
But the answer does not lie solely in technology – success will depend on working together to build and provide access to the right datasets, as well as ensuring everyone who needs them has the right tools in the right hands.
About the author
Amanda Barrell is a freelance health and medical education journalist, editor and copywriter. She has worked on projects for pharma, charities, and agencies, and has written extensively for patients, HCPs and the public.
This post was originally published on Source Link