This paper provides a roadmap for the implementation of collaborative QI programmes in a range of settings across three countries. It summarises the barriers we have experienced in the QI cycle and solutions we have identified in our history of working with healthcare providers to deliver QI programmes in primary and secondary care. Key lessons include the strategic involvement of partners in the fields of medicine, health IT, data science and epidemiology, to harness, understand and act on the insights gained from patient and practice electronic health data (EHR) alongside crucial input from patients and practicing clinicians themselves.
QI aims resource-poor healthcare providers to increase the precision of identifying key patient groups requiring further follow-up – such as those at risk of worsening health outcomes using risk prediction tools. Parallel goals are to increase the proportion of patients receiving prompt and appropriate treatment and to increase patient engagement. We achieve this by providing customised software tools and disease management algorithms to our healthcare partners to allow for automation of aspects of QI that have traditionally involved a manual process. Sharing our experience of these methods helps to embed a sustainable programme of QI in many systems in varied settings.
|Journal||Quality in Primary Care|
|Publication status||Published - 28 Nov 2020|