Drug reimbursement decisions are reliant on clinical trial data, which is often limited by the length of the trial, the number of participants and their demographics. If clinical trial data isn’t wholly representative of a drug’s treatment value, it introduces uncertainty for payers.

Digital health technologies (DHTs) have the potential to provide longer-term continuous outcome data, so that reimbursement can be informed by the outcomes of real-world patients. DHTs, also known as wearables, have great potential in the assessment of drugs for rare diseases and especially expensive therapies, where clinical trial data is often most limited, and the stakes of drug reimbursement are especially high.

COVID-19 has accelerated the adoption of virtual assessments, including the use of DHTs for clinical endpoints. We now have the opportunity to capture patient-generated health data that is acceptable to regulators and payers alike.

This whitepaper details:

• Common data limitations that make drug reimbursement decisions riskier for payers
• Advantages of data collected from wearables and suitable therapeutic areas for their use
• Selection criteria indicating a device is fit for purpose and will produce meaningful endpoints
• Factors to ensure device generated data will be acceptable to payers
• A case study illustrating how children with Duchenne Muscular Dystrophy have used an ankle-worn accelerometer to overcome limitations of the standard ambulatory assessment