Clinical research nurses (CRNs) play a vital role in clinical trials, such as caring for trial patients, preparing trial protocols and other documentation, dealing with data collection, and improving patient recruitment and retention. Due to the broad nature of the role, there are significant improvements to be made in several aspects of the clinical trial process, to reduce the heavy burden on nurses.
While CRNs are vital in running clinical trials successfully, equipping them with tools to increase the efficiency and reduce their workload has been less than successful, partly due to the lack of tool availability and hesitancy in using new technology (1). At Neucruit we aim to challenge and change this hesitancy.
Following Neucruit’s interview with Kelly, a CRN working for Imperial College London and Cancer Research UK, some surprising pain-points and promising technological advancements were discussed.
Firstly, nurses often have highly emotional conversations discussing clinical trial eligibility with patients diagnosed with difficult-to-treat cancers, which leads to patient excitement at the prospect of novel drug trial, only to be told by nurses that they are no longer eligible for a study for reasons beyond anyone’s control (e.g., tumour growth).
Explaining this further, Kelly noted that there is a “small window of opportunity” when patients are at a certain stage of their disease. For instance, patients with metastatic cancer may become eligible for different lines of treatment depending on the location(s) and rate of the metastasis. However, Kelly noted that clinical trial treatment options are not being offered fast enough to patients – in her opinion this is largely due to clerical delays. Hence, patients become ineligible for a specific trial treatment, resulting in these emotionally-heavy and difficult conversations with CRNs.
Kelly suggested that the aforementioned issues could be largely avoided through advances in technology and automating data input for nurses. When using Neucruit, these patients could be flagged much earlier based on their pre-screening information, matched to eligible trials for treatments which could improve individual outcome and also contribute to research breakthroughs (2). Kelly was very open to the suggestion of using automated services to stratify patients more efficiently.
Another pain point for CRN nurses that Neucruit aims to solve, is the recruitment of patients. For some studies there are very few eligible patients, making recruitment even more strenuous and challenging – an issue nurses are aware of from the beginning of the trial design. Often, recruitment relies on collaborations ‘with hospitals or shared multidisciplinary teams in order to suggest eligible patients”, but sometimes there is “competition” for patients between hospitals which also hinders the pace at which eligible patients can be screened and onboarded on the trial. This not only adds to the limitations of biased and non-diverse sampling, but recruitment also becomes dependent on maintaining connections with hospitals and unspoken agreements between trial sites and hospitals or other patient-centred services.
The backlog of patients and the overwhelmed healthcare system does not always give the opportunity to clinicians to get involved with trials, and they might forget to refer eligible participants to clinical trials. According to Kelly, when they do so, they might refer certain demographics only, adding onto the issues of small and non-diverse clinical trial samples (3).
Kelly was extremely eager and open to the idea of using Neucruit’s API after we explained how our tool would work behind the scenes, and how it could benefit nurses and clinicians working with clinical trial teams. Specifically, we suggested that by automating some of the recruitment steps such as matching large patient databases to researchers and pre-screening large volumes of patients much faster and more efficiently, there would be more time for nurses to focus on patient care and on the research itself. This could provide a more positive outcome for nurses and patients in trials too.
Using Neucruit’s natural language processing (NLP) tools too (a tool we are currently in the process of incorporating), patients would be able to see terms they understand when using search engines to look for trial-relevant information, increasing their likelihood to get involved and stay engaged in a clinical trial.
Neucruit aims to introduce this tool to CRNs to improve recruitment and patient outcomes, and to allow CRNs to focus on other aspects of clinical trials too.
Kelly Imperial College London and Cancer Research UK.
A Clinical Research Nurses’ Perspective on Recruitment Issues. 2021.
ALS Patient Advocate interview. In: Neucruit, editor. 2021.
A female-led team transforming clinical trial efficiency, transparency and diversity by improving accessibility to all patient communities. Neucruit is an intelligent software for clinical trial recruitment that redefines patient recruitment. Our technology aggregates real-time data from the over 25 million health-related conversations initiated online everyday to facilitate planning and recruitment in clinical trials. We support biopharmaceutical companies, site teams and investigators enhance site selection, optimise recruitment materials and reach groups that cannot be easily accessed through traditional methods.