The alarming rates surrounding the recruitment, retention, and engagement of qualified patients for clinical trials presents a clear and present danger to the drug development pipeline. Many innovative minds are trying different platforms, outreaches, and technologies to mitigate the problem. If clinical trials are to be patient centric, then the approach to patient retention needs to be more personalized.
There are many different reasons why patients do not engage or choose to follow through in a clinical trial. Even in developed countries there is a lack of awareness and knowledge as to why participate in a clinical trial and what it can offer. In a survey assessing the challenges in participant retention, it was found that 44% of the participants feared side effects. Fear of study procedures and change of residence were reported by 47% as the reasons for dropping. Lack of support from the family physician and family members was reported by 27%, while 55% of the participants stated that the lack of dedicated approach by an investigator’s team and 9% each reported negative media publicity and perceived lack of efficacy of the treatment as reasons for dropping out1.
Of the many factors mentioned for dropping out there are some that can be mitigated with the rapid growth of digital technologies that are enabling the generational shift towards bringing hospital care to the patient’s home. The “hospital-at-home market” is projected to grow 50% from $200 billion to nearly $300 billion by 2028.2 More than a financial blockbuster for the hospital system, clinical home providers, and digital health technology companies; it is very much welcomed by patients. Digital technology companies can support the convenience, personalized outreach approach, and comfort of the patient at home (where possible).
The various digital technologies enabling this generational shift of care from a health facility to the home may offer solutions to challenges in trials associated with patient adherence, inconvenient site location, and on-demand access to clinical support staff.
- Digital Health Technologies such as clinical-grade wearables and biomedical sensors can provide continuous on-demand monitoring of patient’s vitals, activities and/or response to therapies.
- Digital Therapeutics an app on a smart device providing autonomous reminders for patients to take their medication, appointments, or complete an assessment, etc.
- Electronic Clinical Outcome Assessments (eCOAs ) in the form of ePROs, ClinROs, ObsROs, PerfOs, deployed digitally and remotely to assess how trial participants are functioning, feeling and surviving a medical intervention.
- Virtual AI-driven Assistants for on-demand response to patient’s queries or need for more information delivering that on-demand “accessibility” to clinical support staff that cannot be easily supplied with human resources.
Although many are skeptical of the accuracy and acceptance of virtual AI assistants in healthcare, recently there was a case-study published about the feasibility of using a virtual augmented chatbot named, “Penny” at Penn Medicine to support oncology patients. The study showed increased engagement and patient adherence from patients. A medication adherence rate of approximately 70% was measured in participants who responded ‘TAKEN;’ through an iterative process, patient engagement in symptom assessment increased from 25% to approximately 70%.3
The use of these technologies offers many benefits and level of convenience to patients. Patients will no longer be subject to long wait times for clinical team response or delays in waiting-room facilities. For the clinical research team, they will have more tools available to keep patients engaged, adherent and overall satisfied with the experience by personalizing the approach through more convenience for the patient.
The benefits in the use of digital technologies does not come without a price bundle of challenges yet to be resolved. Many of the digital technologies permeating the remote care market have not addressed fundamental issues that impact both patients and clinical researchers. The lack of data and device interoperability presents a barrier to clinical research staff and to patients as more data continues to sit in silos making clinical decision support and actions more difficult. The continued concern of data security and privacy from the point of data generation to distribution to cloud storage continue to fuel that lack of trust and safety in the process. The concerns of bias and lack of explainability in the algorithms create a sense of uncertainty on the accuracy of the data and suggested outcomes of the devices. All of these issues make the process of wide-spread adoption very difficult. If only regulatory bodies and standards development organizations can bring forward industry accepted solutions make these technologies more convenient to use for a very personalized need.
