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Background  Patient care teams have an important role in providing medical care to patients with chronic disease, but insight into how to improve their performance is limited. Two potentially relevant determinants are the presence of a central care provider with a coordinating role and an active role of the patient in the network of care providers. In this study, we aimed to develop and test measures of these factors related to the network of care providers of an individual patient.    Methods  We performed an observational study in patients with type 2 diabetes or chronic heart failure, who were recruited from three primary care practices in The Netherlands. The study focused on medical treatment, advice on physical activity, and disease monitoring. We used patient questionnaires and chart review to measure connections between the patient and care providers, and a written survey among care providers to measure their connections. Data on clinical performance were extracted from the medical records. We used network analysis to compute degree centrality coefficients for the patient and to identify the most central health professional in each network. A range of other network characteristics were computed including network centralization, density, size, diversity of disciplines, and overlap among activity-specific networks. Differences across the two chronic conditions and associations with disease monitoring were explored.    Results  Approximately 50% of the invited patients participated. Participation rates of health professionals were close to 100%. We identified 63 networks of 25 patients: 22 for medical treatment, 16 for physical exercise advice, and 25 for disease monitoring. General practitioners (GPs) were the most central care providers for the three clinical activities in both chronic conditions. The GP's degree centrality coefficient varied substantially, and higher scores seemed to be associated with receiving more comprehensive disease monitoring. The degree centrality coefficient of patients also varied substantially but did not seem to be associated with disease monitoring.    Conclusions  Our method can be used to measure connections between care providers of an individual patient, and to examine the association between specific network parameters and healthcare received. Further research is needed to refine the measurement method and to test the association of specific network parameters with quality and outcomes of healthcare.

Patient Care Teams in treatment of diabetes and chronic heart failure in primary care: an observational networks study