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Review
. 2019 Feb;62(2):140-149.
doi: 10.1007/s00103-018-2862-4.

[A social network analysis regarding geographic variation for patients with depression in Germany]

[Article in German]
Affiliations
Review

[A social network analysis regarding geographic variation for patients with depression in Germany]

[Article in German]
Clarissa Gerber et al. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2019 Feb.

Abstract

Background: Worldwide there is an acute requirement for an early and needs-based treatment for patients with depression. The successful treatment of depression requires the collaborative care of all healthcare providers.

Aim: The aim of this work was to identify virtual networks of physicians treating patients with depression in Germany. We identified specialists who are involved in the care of patients with depression, including geographic variations.

Methods: The analyses were based on claims data of physician practices and psychotherapists in Germany. The data of 18- to 79-year-old patients with depression during 2016 were analysed. Methods and algorithms related to the network analysis were taken from mathematical graph theory. In addition, analyses were stratified by geographical areas (17 associations of statutory health insurance physicians).

Results: The analyses presented an opportunity to generate maps illustrating patient sharing networks within the 17 associations. The analyses demonstrated that general practitioners, psychiatrists and neurologists play a major role in the treatment of patients with depression. It was also shown that different cooperation and cost structures varied by geographical area. Complete-coverage networking of all physicians was shown in Schleswig-Holstein. By contrast Rhineland-Palatinate had four distinct areas.

Conclusion: In the future, differences in healthcare processes and cooperation between physicians might become more visible through network analyses. This would create opportunities for cooperation and coordination between different practitioners of higher quality.

Keywords: Analysis of claims data; Collaborative care; Graph theory; Network analysis; Patient sharing networks.

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