Table 1 (Abstract P5) Theme summary of study results

1] The alignment of rapid-learning methodologies with the reality of practice

A rapid-learning approach using RWD can provide timely evidence and help to formalise changes (through an iterative learning process) that are routinely introduced but with little evaluation. The use of RWD further complements the vision to ‘learn from every patient’ offering greater potential for treatment personalisation.

2] Variability of clinical and RWD

Concerns around the quality of clinical and RWD extend to data collection (e.g. poor follow-up data), issues over data recording and sharing formats, incompleteness of data reporting (e.g. toxicity and PROM data), and data analysis (time, resource, skill).

3]The maturity of data and digital infrastructures for rapid-learning

The need to develop integrative data and digital infrastructures to enable timely access to data and data standardisation.

4] Support and evidence needed to convince adoption of rapid-learning approaches.

Support for implementation of rapid-learning includes time and resources for data collection, access to analytical support, and clear surveillance strategy (to increase confidence in the reliability of data). Further method clarification to better understand additional practice demands and provide guidance over critical data points (to minimise risk) when introducing treatment changes.