Cardiology patients' medicines management networks after hospital discharge: A mixed methods analysis of a complex...

The complex healthcare system that provides patients with medicines places them at risk when care is transferred between healthcare organisations, for example discharge from hospital. Consequently, understanding and improving medicines management, particularly at care transfers, is a priority.

This study aimed to explore the medicines management system as patients experience it and determine differences in the patient-perceived importance of people in the system.

We used a Social Network Analysis framework, collecting ego-net data about the importance of people patients had contact with concerning their medicines after hospital discharge. Single- and multi-level logistic regression models of patients' networks were constructed, and model residuals were explored at the patient level. This enabled us to identify patients' networks with support tie patterns different from the general patterns suggested by the model results. Qualitative data for those patients were then analysed to understand their differing experiences.

Networks comprised clinical and administrative healthcare staff and friends and family members. Networks were highly individual and the perceived importance of alters varied both within and between patients. Ties to spouses were significantly more likely to be rated as highly important and ties to community pharmacy staff (other than pharmacists) and to GP receptionists were less likely to be highly rated. Patients with low-value medicines management networks described having limited information about their medicines and a lack of understanding or help. Patients with high-value networks described appreciating support and having confidence in staff.

Patients experienced medicines management as individual systems within which they interacted with healthcare staff and informal support to manage their treatment. Multilevel models indicated that there are unexplained variables impacting on patients' assessments of their medicines management networks. Qualitative exploration of the model residuals can offer an understanding of networks that do not have the typical range of support ties.