Clinical research has come a long way since using paper in the early nineties to maintain patient health records, keep track of their treatments, and report patient outcomes. Today, with the emergence of new technologies and advancements in care and treatment, the ability to capture, process, store, and mine patient-related data to extract meaningful information for clinical decision-making has improved greatly. Electronic health records (EHRs), for example, have created a major breakthrough in the research and development field. With their ability to streamline, enhance, and speed-up the data collection process, EHRs have become an important tool in clinical research. In addition to this, innovative study designs and evolving regulations for global data security and privacy have given rise to new trends in clinical development. A few notable ones include increasing use of electronic patient reported outcomes (ePROs) in studies; electronic health records’ integration with electronic data capture (EDC); eSource adoption; and growing use of de-identified healthcare data.
ePROs are increasingly becoming the most sought-after method for collecting data directly from patients. ePROs provide improved data capture, quality, and transparency, which result in faster and more efficient clinical trials. Study coordinators are also exempt from manual calculations, and from spending time reviewing or deciphering patients’ handwritten diaries. The wide acceptance of EHRs and EDC has inspirited forward-thinking clinicians and researchers to consider the possibility of a single system to collect both patient care and clinical research data. This system would improve the workflow and efficiency of the clinical research, eliminate errors from data transcription, reduce the costly and time-consuming process of source data verification, and accelerate the overall process of clinical trials.
Healthcare data de-identification is another trend that is gaining more prominence at the moment. De-identified data removes many—if not most—roadblocks leading up to a research project and increases the researchers’ odds for success. Research institutions are utilizing this data to suggest sources of potential patients for clinical trials. For example, epidemiologists in Utah have used de-identified patient data to help define optimal care strategies for post-traumatic stress disorder and congestive heart failure.
Today, a growing number of organizations are also moving toward a more direct-to-patient (DTP) clinical trial approach that eliminates the need for a patient to travel to an investigator site, leading to higher engagement and retention rates for the trial sponsor.
As the clinical research sector continues to be enriched by novel trends and technologies, there will be a constant need to balance medical progress and patient safety. Hence, organizations that adapt and adjust to these emerging trends will continue to grow and have a competitive edge in the market.