DCT Benefits to Patients and Impacts on Clinical Data Management | The Future of Clinical Data Management Series

This blog was authored by Teresa Fishburne, Vice President, Strategic Consulting, Medidata.

This post explores the benefits of decentralized clinical trials for patients and the impacts of decentralization on data management.

Benefits of Decentralized Clinical Trials to Patients

By nature, decentralized clinical trials are patient-focused since they provide patients with options for flexibility when it comes to logistics and travel to the investigative site (if required at all). Flexibility and increasing the number of options to patients is occurring through technology enablers that allow for decentralization support from the beginning to the end of the clinical trial. 

Relative to traditional trials, decentralized trials offer several well-characterized benefits to patients, including the following:

• Higher Convenience: Patients have more flexibility with site visits; travel is eliminated or greatly reduced.
• Increased Trial Access: Patients may be more willing to enroll in trials that they might not have previously qualified for due to geographic location or if the patient is highly incapacitated. 
• Increased Access to Data: Patients often want access to the data collected about them to share with their HCPs or for their own interest. Digital technologies can enable easier data access for them. 
• Higher Satisfaction: Patients are more empowered and engaged, and they are more highly satisfied with participation.

Given that the patient experience is paramount to the overall success of any clinical trial—if planned correctly, decentralized trials are well-positioned for success given their patient-centric nature.

Direct Impacts of Decentralized Clinical Trials on Data Management

With more data being collected directly from patients, including wearable devices, electronic clinical outcome assessments (eCOA), and telehealth platforms, there is an urgent need to shift our thinking from reactive strategies to proactive planning and technology-based solutions to replace query and listing-based reviews of trial data. In traditional clinical trials, clinical data managers are tasked with manually identifying trends and data anomalies via data listings, dashboards, and home-grown tools that often lack interoperability.

The future of clinical data management is here, and modernized processes and technologies will increasingly become available to support clinical data managers in their roles and responsibilities as they adapt to the new realm of data management in clinical trials, including benefits associated with risk-based quality management methodologies guided by RBQM/ICH E6 recommendations. 

The challenge for those in data management leadership and those working directly on trials is how to best incorporate an ever-increasing list of data sources, novel data types, analytic tools, and existing personnel in a risk-based environment to execute the core function of data management, which is ensuring that clinical data is collected “fit for purpose.” As mentioned above, modern clinical data managers will have to be increasingly proactive when planning and deploying interoperable technology-based solutions to replace the manual query and listing-based reviews. In short, clinical data managers are increasingly becoming the nucleus for bringing together all of the disparate data to harmoniously communicate a complete patient’s journey.

What is clear is that the old ways will not work in the new, modernized world of clinical data management. Clinical data management organizations will need to prioritize upskilling clinical data managers and dedicate time and resources to expand their analytical mindsets, clinical skills, and risk and mitigation processes, as well as their understanding and use of real-world evidence, data trends, and new clinical endpoints based on alternative EDC designs from decentralized trials.

If clinical data management commits to this cultural shift and we augment our daily activities with a new data governance toolkit that includes specialized tools for real-time analytics, data managers will be better equipped to provide engagement from protocol design to data visualization development, as well as with patient-centric technology solutions in any phase of a decentralized trial.

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