Fiche du document
- doi: 10.1002/mpr.1937
- issn: 1049-8931
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/doi/10.1002/mpr.1937
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/pmid/35976617
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/eissn/1557-0657
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/urn/urn:nbn:ch:serval-BIB_6C2EC410DCBB9
info:eu-repo/semantics/openAccess , Copying allowed only for non-profit organizations , https://serval.unil.ch/disclaimer
Sujets proches
Use ofCiter ce document
N. Stulz et al., « Mental health service areas in Switzerland. », Serveur académique Lausannois, ID : 10.1002/mpr.1937
Métriques
Partage / Export
Résumé
Small area analysis is a health services research technique that facilitates geographical comparison of services supply and utilization rates between health service areas (HSAs). HSAs are functionally relevant regions around medical facilities within which most residents undergo treatment. We aimed to identify HSAs for psychiatric outpatient care (HSA-PSY) in Switzerland. We used HSAr, a new and automated methodological approach, and comprehensive psychiatric service use data from insurances to identify HSA-PSY based on travel patterns between patients' residences and service sites. Resulting HSA-PSY were compared geographically, demographically and regarding the use of inpatient and outpatient psychiatric services. We identified 68 HSA-PSY, which were reviewed and validated by local mental health services experts. The population-based rate of inpatient and outpatient service utilization varied considerably between HSA-PSY. Utilization of inpatient and outpatient services tended to be positively associated across HSA-PSY. Wide variation of service use between HSA-PSY can hardly be fully explained by underlying differences in the prevalence or incidence of disorders. Whether other factors such as the amount of services supply did add to the high variation should be addressed in further studies, for which our functional mapping on a small-scale regional level provides a good analytical framework.