Recent experiences in the use of diabetes registers show their ability to improve population health in a region. In the framework of the Umbria registry, we have defined general criteria for the development of a comprehensive model including new directions for active use of health information. General functions of the diabetes register have been designed for a range of stakeholders. Large scale data linkage is used to extract study cohorts and add information content to the register. Multidimensional/multilevel analysis is directly applied to define high risk strata on the basis of multiple individual, structural, contextual (ecological) and service-related components. Target subjects can be used to design specific interventions for the prevention of diabetic complications. The enhanced version of the Umbria Register involves a large group of institutional partners in a new program for clinical governance. Agreed routine health system evaluation now regards diabetes indicators as a high priority area. The data model supports information exchange across a network of national and international partners, contributing to the definition of a common benchmarking system. The present work shows that principles of evidence-based medicine can be used to underpin new ways of active use of health information. Involving policy makers and health professionals in the research and development of diabetes registers will be increasingly crucial to capture all opportunities arising from a wide application.
Diabetes registers and prevention strategies: towards an active use of health information
Carinci FMethodology
;
2006-01-01
Abstract
Recent experiences in the use of diabetes registers show their ability to improve population health in a region. In the framework of the Umbria registry, we have defined general criteria for the development of a comprehensive model including new directions for active use of health information. General functions of the diabetes register have been designed for a range of stakeholders. Large scale data linkage is used to extract study cohorts and add information content to the register. Multidimensional/multilevel analysis is directly applied to define high risk strata on the basis of multiple individual, structural, contextual (ecological) and service-related components. Target subjects can be used to design specific interventions for the prevention of diabetic complications. The enhanced version of the Umbria Register involves a large group of institutional partners in a new program for clinical governance. Agreed routine health system evaluation now regards diabetes indicators as a high priority area. The data model supports information exchange across a network of national and international partners, contributing to the definition of a common benchmarking system. The present work shows that principles of evidence-based medicine can be used to underpin new ways of active use of health information. Involving policy makers and health professionals in the research and development of diabetes registers will be increasingly crucial to capture all opportunities arising from a wide application.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.