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Clinical trials have changed significantly in the past decade with increasingly large and complex global studies. Multi-center, multinational trials are common, with complicated treatment protocols, large staffs, and huge data sets muddling the clinical trial processes. With years of development time and millions in R&D invested in a new treatment before it reaches the trial stage, there is incredible pressure on investigators to deliver quality data.
Clinical trials have changed significantly in the past decade with increasingly large and complex global studies. Multi-center, multinational trials are common, with complicated treatment protocols, large staffs, and huge data sets muddling the clinical trial processes. With years of development time and millions in R&D invested in a new treatment before it reaches the trial stage, there is incredible pressure on investigators to deliver quality data. In addition, the US Food and Drug Administration’s (FDA) demand for robust trial data to ensure patient safety highlights the need for accurate clinical trial data.
Yet, investigators and their staff face a heavy burden. Electronic Medical Records (EMR) system data is not entirely usable from a research perspective, so trial investigators must also enter the information into an Electronic Data Capture (EDC) system. In fact, according to a recent CenterWatch report conducted in partnership with the Association of Clinical Research Professionals, investigative sites typically use an average of 12 different systems to collect data for clinical trials. Study coordinators and investigators noted that incompatible systems resulted in increased workloads for sites, greater operational inefficiencies, and lower productivity. A key example cited is the lack of integration between EHRs, EMRs, and other eSource systems – used by clinicians to record patient data – and EDC systems – administered by sponsors and CROs. This has perpetuated a cumbersome, double data-entry, see-saw between systems, creating significant delays.1
This constant back and forth between systems to record information accurately and in the right place over the life of a trial leads to significant inefficiencies and risk of human error.
Research published in Current Oncology Reports states, “Submission of data into clinical trial electronic data capture (EDC) systems currently requires redundant entry of data that already exist in the electronic medical record (EMR). Integration between the EMR and EDC would enable more accurate and efficient collection of clinical trial data, particularly in multi-site trials. Being able to automatically transfer data from the EMR to the EDC would save many hours of arduous effort, especially for multi-site, data-intensive oncology trials.”2EDC Systems Cause Complexity
Traditional EDC systems add to this complexity − as well as cost − by requiring site staff to spend an unnecessary amount of time managing clinical data. System set-up, ongoing maintenance, inflexibility, and a lack of integration interfere and slow down investigators’ ability to get clean data and quickly make informed decisions during trials. Since 2000, the volume of data in a Phase III trial has risen by more than 50% and more companies are conducting trials (for the same drug) concurrently in multiple countries, making it harder for investigators to accurately capture patient data.3
Many physicians running trials work with an EMR system and, therefore, must enter data electronically. However, data logged into an EMR is not structured properly for use in research, and it’s often not inclusive of certain key variables needed for research. For instance, a physician may need a patient in a trial to have his or her blood pressure taken three times in 10-minute, intermittent intervals (and then record the average of the three), per the trial protocol. However, an EMR system can only capture blood pressure once. To compensate, physicians often resort to rudimentary measures such as writing these blood pressure readings on sticky notes and entering them into the EDC system later.
Despite the risk of error, this is a common scenario. Data required for clinical trials but not required in clinical care need different supporting technology. The reverse holds true in clinical care – there is data that primary care doctors need, such as insurance information and diagnosis codes, that is unnecessary in clinical trials. In order to ensure complete and accurate data capture, a bridge between systems is crucial.
A Technology Bridge to Speed Trials
Technology can help eliminate these bottlenecks and prevent busy investigators from seesawing back and forth between systems. But, which technology – the EMR or EDC?
Many advocate extending the capabilities of either the EMR or EDC. There’s a better option: A bridge. Rather than trying to tack-on capabilities to one system or the other, clinical trial sponsors can bridge both solutions using common data standards. Such a connected solution that crosses systems yields the crucial level of reliable, high-quality data needed to make faster, informed decisions throughout the life of the study. It also reduces the complexity of trials by eliminating cumbersome, manual, paper-based processes. No longer needing to transcribe patient data into multiple systems – which can take days or weeks after the patient visit – also cuts costly, time-consuming source data verification by clinical monitors. All told, the benefits of a technology bridge reduce the heavy burden on investigators.
One seamless, electronic clinical research model can meet investigators’ needs for both clinical trials and clinical care. Now, even, imagine a software bridge that is also intelligent enough to know what data points are needed for trials versus diagnoses. Data is captured once and automatically flows into the right system, totally removing human error from the process. This has the power to speed clinical trials in many ways such as by pre-identifying sites with appropriate patients and facilitating patient randomization.
The Time Is Now
Now’s the time to employ technology to achieve this investigator-friendly solution that will remove the complexity of data entry and keep physicians focused on taking care of patients and executing clinical research in a safe and effective manner.
“The integration of clinical practice and clinical research data, next-generation eClinical technology solutions that unify end-to-end clinical processes, and improvements in protocol design execution feasibility will all be critical success factors in driving higher levels of efficiency, performance, and data quality,” said Ken Getz, associate professor and director at Tufts University School of Medicine.
Why wait? External pressure on the industry is driving the creation of common data standards meant to make healthcare and pharmaceutical systems work together and a technology bridge possible. The potential benefits could be far-reaching. Human data entry errors would be reduced. No more capturing information on post-it notes. Moreover, data would ultimately be in all the right places, without added burden on clinical researchers and caregivers.
Henry Levy is chief strategy officer at Veeva Systems. He can be reached at firstname.lastname@example.org.