The introduction of a data-driven population health management approach in the Netherlands since 2019: The Extramural LUMC Academic Network data infrastructure.

Improving population health and reducing inequalities through better integrated health and social care services is high up on the agenda of policymakers internationally. In recent years, regional cross-domain partnerships have emerged in several countries, which aim to achieve better population health, quality of care and a reduction in the per capita costs. These cross-domain partnerships aim to have a strong data foundation and are committed to continuous learning in which data plays an essential role. This paper describes our approach towards the development of the regional integrative population-based data infrastructure Extramural LUMC (Leiden University Medical Center) Academic Network (ELAN), in which we linked routinely collected medical, social and public health data at the patient level from the greater The Hague and Leiden area. Furthermore, we discuss the methodological issues of routine care data and the lessons learned about privacy, legislation and reciprocities. The initiative presented in this paper is relevant for international researchers and policy-makers because a unique data infrastructure has been set up that contains data across different domains, providing insights into societal issues and scientific questions that are important for data driven population health management approaches.

Implementation fidelity of a clinical medication review intervention: process evaluation.

Background Implementation of clinical medication reviews in daily practice is scarcely evaluated. The Opti-Med intervention applied a structured approach with external expert teams (pharmacist and physician) to conduct medication reviews. The intervention was effective with respect to resolving drug related problems, but did not improve quality of life. Objective The objective of this process evaluation was to gain more insight into the implementation fidelity of the intervention. Setting Process evaluation alongside a cluster randomized trial in 22 general practices and 518 patients of 65 years and over. Method A mixed methods design using quantitative and qualitative data and the conceptual framework for implementation fidelity was used. Implementation fidelity is defined as the degree to which the various components of an intervention are delivered as intended. Main outcome measure Implementation fidelity for key components of the Opti-Med intervention. Results Patient selection and preparation of the medication analyses were carried out as planned, although mostly by the Opti-Med researchers instead of practice nurses. Medication analyses by expert teams were performed as planned, as well as patient consultations and patient involvement. 48% of the proposed changes in the medication regime were implemented. Cooperation between expert teams members and the use of an online decision-support medication evaluation facilitated implementation. Barriers for implementation were time constraints in daily practice, software difficulties with patient selection and incompleteness of medical files. The degree of embedding of the intervention was found to influence implementation fidelity. The total time investment for healthcare professionals was 94 min per patient. Conclusion Overall, the implementation fidelity was moderate to high for all key components of the Opti-Med intervention. The absence of its effectiveness with respect to quality of life could not be explained by insufficient implementation fidelity.