Big data and little behaviours: audit and feedback with or without a quality improvement toolkit to help primary care facilitate COVID‑19 vaccine uptake
One of the most important ways to address vaccine hesitancy and build vaccine confidence is through conversations with a trusted health professional. People trust their primary care professionals to provide them with personalized recommendations based on an understanding of their whole lives. So, how can we best help primary care professionals to have effective conversations about the COVID vaccines with their patients who most need their help? This proposal is about implementing a province-wide strategy that uses « big data » to enable a sequence of little behaviours to bring us closer to herd immunity. The foundation for our approach is using registry data about vaccine uptake and linking it to datasets that identify the main family doctor for each person. The doctor will get a list of people in their practice who are ‘overdue’ for the vaccine (e.g., age over 80 and not yet vaccinated). As experts in behavioural science, we know there is more to solving this problem than simply providing a list. That’s why alongside this list we will be testing a set of tools to help the doctor to take the steps needed to effectively engage with each of their patients who need their support. We will carefully test whether the list, with or without the additional toolkit, increases vaccine uptake, in which types of primary care settings, and for which types of patients. We will specifically look at whether this strategy helped improve the fairness of vaccine uptake – that is, whether it helped get more people in hard-hit communities to get vaccinated.
