Patient Recruitment and Engagement: How is Technology Lending a Hand?

Natural language processing can be used to construct algorithms that can analyze doctor's notes and pathology reports of patients when employed in clinical trials. This will speed up the patient recruitment process and boost the efficiency of clinical trials by ensuring the recruitment of the best individuals.

FREMONT, CA: Clinical trials have traditionally depended mainly on paperwork, with patient engagement receiving less attention. Changing clinical trial requirements, the clinical trial landscape, competition, and technological developments, on the other hand, allowed for the introduction of a personalized and digitalized patient-centric approach to clinical trials. Take a closer look at it.

How Can Artificial Intelligence Be Used for Patient Recruitment for A Clinical Trial?

Recruitment is the most time-consuming and the most expensive step in clinical research, as we all know. The procedure is lengthy and complicated, with a significant risk of patient abandonment. However, Artificial Intelligence (AI) and Natural Language Processing (NLP) can tackle these problems. NLP is a technique that allows a computer to evaluate written or spoken words. NLP can be used to construct algorithms that can analyze doctor's notes and pathology reports of patients when employed in clinical trials. This will speed up the patient recruitment process and boost the efficiency of clinical trials by ensuring the recruitment of the best individuals.

In Clinical Studies, How Can Mobile Technology Promote Patient Recruitment and Reduce Drop-Out Rates?

The availability of new technology such as patient portals, sensors, and other apps makes it easier to engage patients. They can now register their health information using their clinical trial/wearable medical devices instead of going to hospitals, making appointments, or asking for prescription refills. Chatbots, for example, have been facilitated by this technology, which has opened up new channels of contact between patients and researchers involved in the clinical trial study. For example, forgetting appointments is a common reason for patient drop-out. Clinical trial individuals can receive reminders for attending meetings or taking medication on time via their wearable medical devices. They can also ask inquiries or access clinical trial study information or instructional information about the treatment plan.

Remote patient monitoring applications are another incredible technological innovation in clinical trial patient recruiting. They allow for remote monitoring of patients (those who live far away from the trial locations) and the storage of all data linked to them, as well as ongoing interactions and communications. Virtual trials that are so accessible and unobtrusive can help minimize drop-out rates and increase enrollment.

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