By Jim Rogers, CEO, Nextrials
The number of clinical studies has increased dramatically, from a mere 4,000 in 2000 to almost 200,000 today. In the U.S., nearly 20 percent of these studies are classified as registry (or observational) studies. While randomized clinical trials (RCTs) are often considered best for guiding clinical decision making, they have limitations in some areas, such as giving researchers the ability to make observations over longer periods of time and with wider audiences. Observational or registry studies are one way to obtain this critical data, and, while the gold standard randomization factor is not used, these studies do allow researchers to discover complex patterns and statistically significant results in low-frequency outcomes.
But as with all things, there is room for improvement in how these studies manage data and identify appropriate study participants for enrollment. Registry studies have been largely inefficient in utilizing and integrating existing patient data from electronic health records (EHRs), something easily overcome by implementing an effective electronic data capture (EDC)/EHR integration tool. At the very least, this would provide cost efficiencies by facilitating faster study starts through an increased population pool and eliminate duplicate data entry.
But perhaps the greatest gain could come in the form of data quality. Hospitals and clinics collect patient data in the same format as clinical researchers, just using a different form (more on that below). By integrating EHRs with EDC platforms, researchers could more accurately compile standard of care data and supplement with study-specific data as needed. Surprisingly, one hindrance to wider adoption of this practice is the fact that healthcare has been slow to adopt big data analytics and advanced EHRs.
According to an article published recently by Business Insider, only 78 percent of physicians currently use some form of EHR, 59 percent use an advanced form of EHR, and only 48 percent of hospitals use an advanced form of EHR.
“On average, we collect only 100MB of data per patient per year in healthcare,” says Dale Sanders, senior vice president of strategy at Health Catalyst. “A Boeing 767, on the other hand, collects about 500GB of flight and aircraft health data in a single six-hour flight. The resolution of the camera on my smartphone is 16MB. By taking just seven pictures, I am collecting more data than my healthcare system collects on me in an entire year. We cannot fully understand the complete picture of patient health and outcomes until we expand our data collection vision and tools into these socio-economic, environmental, and lifestyle areas, and include the collection of data on healthy patients, not just those who have or are seeking treatment.”
Based on the industry discussions I have had over the years, I think you could make the case that there are hospitals and clinics in the U.S. that would like to contribute to the research arena – and observational studies would provide a gentle entry ramp to allow them to participate in the advancement of pharmaceutical knowledge. But unfortunately, many of those hospitals and clinics are fighting an uphill battle with some of the physicians they work with.
“We know that when some physicians adopt EHR systems, they are worse off – slower, less efficient, struggling to provide high-quality care,” Julia Adler-Milstein, a University of Michigan professor, recently testified to Congress. “But for others, the experience is very different: They see big gains in productivity and the quality of care they provide.
Why do some do so well with technology while others struggle?,” she mused. “The answers are not as simple as age or tech savviness. It’s likely much more about how the IT is used, and the context in which it is used.”
Adler-Milstein touches on a key point in this discussion. If this were simply a discussion about EHR adoption, we could just present the data that clearly shows its advantages. But this discussion is focused on how EDC and EHR integration enhances registry studies, and Adler-Milstein’s context is relevant. Perhaps in everyday medicine, EHRs are a hinderance for some, but they are hugely beneficial to the registry study.
Registry studies typically collect standard of care data — data that is already included in the patient’s EHR. By implementing a proven data collection tool, researchers in registry trials could skip the time-consuming step of reentering the data into the research database. A site survey (eClinical Forum site survey 2011) said 70 to 100 percent of needed clinical data is already in the EHR. From the researchers standpoint, getting data directly from EHR not only saves them precious time, it also increases the quality of the data because it eliminates transcription errors – the data is simply exported.
There are other benefits to implementing proven data collection tools and EHR systems into a registry study:
The growth of registry studies has increased the need for researchers to improve data entry techniques and data quality, yet the lack of integration between EDC and EHR systems has hampered the development of a solution. The Meaningful Use Stage 3 criteria for EHR systems includes data sharing standards that would further enable integration with clinical research systems, but adoption of Stage 3 is subject to possible delays beyond its 2018 implementation target.
Regardless, we continue to press forward. The FDA, often thought of as a conservative, risk-adverse agency, recently announced it is seeking demonstration projects to analyze how EHRs integrated with EDC platforms could bolster clinical research.
In the notice, the FDA said it is looking to support demonstration projects to analyze how a single-point, end-to-end EHR-to-EDC approach would perform in clinical research settings. Specifically, the demonstration projects would test standards-based technology as a way to facilitate the collection of health and clinical research data within one system and workflow.
The healthcare and pharmaceutical research industries are rapidly changing, and technological advances such as EDC/EHR integration will cause disruption – either by forced or embraced adoption. Researchers and healthcare practitioners will need to continue to work together to develop potentially better methodologies such as this one for improving research data and patient outcomes, potentially with a single, integrated tool.