Methods and perceptions of success for patient recruitment in decentralized clinical studies.

Patient recruitment, diversity, and retention continue to impede successful and representative clinical studies. This systematic review aims to assess the impact of decentralized methods on recruitment, retention, and diversity in recent clinical studies. A systematic search of literature reporting on recruitment in decentralized clinical studies was performed. Studies were reviewed for those reporting the primary outcome of recruitment in decentralized clinical trials, observational studies, or those covering the topic of clinical trials. Secondary outcomes included retention, participant diversity, and participant satisfaction. This systematic search returned 13 studies highlighting the role of decentralized methods impacting participant recruitment, retention, and diversity in clinical studies. Eleven reported improved recruitment using decentralized methods. Seven of these reported improvements directly compared to traditional methods. Seven studies reported positive retention outcomes, with four directly comparing decentralized methods with traditional methods. Six studies were reported to have trended toward increased diversity in the demographics of the sample population, including race or geographic location. Related reviews have stated a lack of published comparable data to determine if decentralized clinical methods improved recruitment and retention. Results suggest this review addresses such a gap, providing data on how decentralized methods such as virtual visits can positively impact recruitment and retention.

Real-world evidence and product development: Opportunities, challenges and risk mitigation.

Real-world evidence (RWE) is derived from real-world data (RWD) sources including electronic health records, claims data, registries (disease, product) and pragmatic clinical trials. The importance of RWE derived from RWD has been once again demonstrated during the coronavirus disease 2019 (COVID-19) pandemic, as it can improve patient care by complementing information obtained from traditional clinical trial programs. Additionally, RWE can generate insights into disease mechanisms, epidemiology, patient flows in and out of healthcare systems, and drivers and barriers to optimal clinical care in real-world settings. Identifying unmet medical needs is crucial as it often can inform which investigational new drugs enter clinical trial testing, and RWE studies from hospital settings have contributed substantial progress here. RWE can also optimize the design of clinical studies, inform benefit risk assessments and use networks of pragmatic studies to help with clinical trial feasibilities and eventual trial initiation. The challenges of RWD include data quality, reproducibility and accuracy which may affect validity. RWD and RWE must be fit for purpose and one must be cognizant of inherent biases.