Abstract 4439
Background
Proprietary advanced analytics were applied within US RWD, e.g. medical/prescription claims and physician reference data, to identify high potential sites and physicians treating eligible mCRPC patients, with the aim of accelerating recruitment into an ongoing mCRPC clinical trial. Furthermore, a bespoke methodology to identify physician-to-investigator relationships was used to implement an advanced data driven patient referral network.
Methods
Relevant standard diagnosis, drug, and procedure codes were applied to medical and prescription claims datasets and cross-linked with physician reference data, to identify medical oncologists treating the target patient population. Physicians were also referenced to their affiliated sites. Shared patient counts between investigators and local physicians were also quantified, providing valuable insights into physician-to-investigator relationships to prioritise and leverage into a patient referral network.
Results
Selected results summarised below: ∼20k eligible patients were identified - 270 sites each with ≥20 eligible patients were identified ∼2k oncologists treating eligible patients and with trial experience in the past year were identified ∼4k shared patients between targeted physicians and trial investigators were identified.
Conclusions
To facilitate faster patient access to effective medicines, novel methods such as those outlined above are required to optimise clinical trial operations and increase efficiency. Together with the innovative use of RWD to find eligible mCRPC patients and the physicians and sites treating these, we implemented sophisticated techniques to quantify shared patient counts between identified physicians and investigators. This created a foundation for a referral network that has been successfully implemented, as an alternative to the lengthy and costly initiation of a new site(s). This approach would be invaluable in future trials with ever smaller patient populations, for example within rare diseases and precision medicine.
Clinical trial identification
Legal entity responsible for the study
IQVIA.
Funding
IQVIA.
Editorial Acknowledgement
Disclosure
The author has declared no conflicts of interest.
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