Patients want to be certain that they receive the best treatment available, and clinicians want to ensure they’re delivering optimal care. Unfortunately, in many cases, providers can’t be confident they are delivering care that will result in the best outcome because their treatment may not be current or informed by proven medical findings. Time is of the essence when it comes to care—and clinicians often lack sufficient time to research treatment best practices while treating patients.
Clinical research is an important component of patient care. Treatment should be based on the outcomes from clinical trials. However, evidence that is based on clinical trials is not always available to help providers recommend one medication or course of treatment over another.
The number of clinical trials is increasing significantly, but trials cannot be successful without enough participants to gather evidence. Recruiting participants can be challenging, and it can be difficult to match the right participants with studies. Approximately one out of three clinical trials fails to meet recruitment targets, so the sample size becomes too small to draw scientifically justified conclusions. The remaining two-thirds of trials recruit participants slowly. The effort becomes costly and time-consuming.
Recruitment failure in clinical trials is a major concern in the healthcare industry. It may seem unethical to ask trial participants for time and engagement and potentially expose them to some risk. However, if researchers are not successful in recruiting participants, they may never find answers to some of the most pressing medical research questions.
Big data eases recruitment pain points
New digital tools are starting to help researchers do a better job attracting, matching, and including appropriate clinical trial participants. Technology is also helping to facilitate and improve the patient recruitment process. One key is leveraging the Big Data that already exists in healthcare organizations.
Unfortunately, patient data is often unstructured and lives in disparate systems, so it’s difficult for researchers to identify potential participants. For instance, study nurses have traditionally helped identify subjects who fulfill research study criteria, but they have been held back by the need to sift through files of paper-based patient records. Technology enables researchers extract information from electronic medical records to quickly identify potential study participants.
Using data strategically can not only improve recruitment rates, but it also ensure that participants are a good fit with a particular study. Clinic physicians don’t always ask patients if they are interested in participating in clinical research because they lack the time or don’t have sufficient knowledge of specific trials. Now the records of prospective participants can be flagged, enabling clinicians to discuss the study with them during routine medical care.
Of course, the ultimate goal of clinical research is improving patient care and outcomes, and improving the clinical trial recruitment process helps do just that and more. Process optimization through automation of time-consuming patient screening improves collaboration, saves time, and facilitates the research process for all end users.
Automated patient recruitment benefits hospitals and healthcare systems and improves patient outcomes by increasing physicians’ awareness of clinical trials. It also benefits life science companies and contract research organizations (CROs) by optimizing trial design and protocol based on eligible patients and reducing research and development cycle time and costs.
Clinical trials set stage for better patient outcomes
Center for Biomarker Research in Medicine (CBmed) is working on an innovative software application to help researchers find and screen eligible patients for clinical trials. While the application is still under development, it aims to address common recruitment challenges.
CBmed and the University Hospital Graz are looking into a trial data model that can store all relevant information, create a trial manually or import details from clinicaltrials.gov to reduce manual intervention, automatically match patient data from electronic medical records, and enter criteria tolerance to improve eligible patient screening results. More information on the CBmed project, Innovative Use of Information for Clinical Care, and Biomarker Research (IICCAB) can be found here.
I began working in clinical research because I wanted to find answers to the questions patients ask every day about their own care. Technological innovation is enabling faster, better clinical trials by improving the participant recruitment process, and it will ultimately lead to evidence-based, life-changing, and life-saving treatments for patients.
For more on how technology can help improve patient outcomes, see Patient Engagement: Key To High-Value Care.