Participatory codesign of patient involvement in a Learning Health System: How can data-driven care be patient-driven care?

Background: A Learning Health System (LHS) is a model of how routinely collected health data can be used to improve care, creating 'virtuous cycles' between data and improvement. This requires the active involvement of health service stakeholders, including patients themselves. However, to date, research has explored the acceptability of being 'data donors' rather than considering patients as active contributors. The study aimed to understand how patients should be actively involved in an LHS.

Design: Ten participatory codesign workshops were conducted with eight experienced public contributors using visual, collective and iterative methods. This led contributors to challenge and revise not only the idea of an LHS but also revise the study aims and outputs.

Results: The contributors proposed three exemplar roles for patients in patient-driven LHS, which aligned with the idea of three forms of transparency: informational, participatory and accountability. 'Epistemic injustice' was considered a useful concept to express the risks of an LHS that did not provide active roles to patients (testimonial injustice) and that neglected their experience through collecting data that did not reflect the complexity of their lives (hermeneutic injustice).

Discussion: Patient involvement in an LHS should be 'with and by' patients, not 'about or for'. This requires systems to actively work with and respond to patient feedback, as demonstrated within the study itself by the adaptive approach to responding to contributor questions, to work in partnership with patients to create a 'virtuous alliance' to achieve change.

Patient or public contribution: Public contributors were active partners throughout, and co-authored the paper.