Paola Ballotari1, Sofia Chiatamone Ranieri2, Massimo Vicentini1, Stefania Caroli1, Andrea Gardini3, Rossella Rodolfi4, Roberto Crucco5, Marina Greci6, Valeria Manicardi7, Paolo Giorgi Rossi1. 1. Servizio Interaziendale di Epidemiologia, Local Health Authority of Reggio Emilia, Italy. 2. Clinical Chemistry, Laboratory and Endocrinology Unit, Department of Laboratory Medicine, Azienda Ospedaliera ASMN, Istituto di Ricovero e Cura a Carattere Scientifico, Italy. Electronic address: sofia.chiatamoneranieri@asmn.re.it. 3. Pharmaceutical Department, Local Health Authority of Reggio Emilia, Italy. 4. Planning and Control Staff, Local Health Authority of Reggio Emilia, Italy. 5. Information Technology Unit, Local Health Authority of Reggio Emilia, Italy. 6. Primary Care Department, Local Health Authority of Reggio Emilia, Italy. 7. Department of Internal Medicine, Hospital of Montecchio, Local Health Authority of Reggio Emilia, Italy.
Abstract
AIMS: To describe the methodology used to set up the Reggio Emilia (northern Italy) Diabetes Register. The prevalence estimates on December 31st, 2009 are also provided. METHODS: The Diabetes Register covers all residents in the Reggio Emilia province. The register was created by deterministic linkage of six routinely collected data sources through a definite algorithm able to ascertain cases and to distinguish type of diabetes and model of care: Hospital Discharge, Drug Dispensation, Biochemistry Laboratory, Disease-specific Exemption, Diabetes Outpatient Clinics, and Mortality databases. Using these data, we estimated crude prevalence on December 31st, 2009 by sex, age groups, and type of diabetes. RESULTS: There were 25,425 ascertained prevalent cases on December 31st, 2009. Drug Dispensation and Exemption databases made the greatest contribution to prevalence. Analyzing overlapping sources, more than 80% of cases were reported by at least two sources. Crude prevalence was 4.8% and 5.9% for the whole population and for people aged 18 years and over, respectively. Males accounted for 53.6%. Type 1 diabetes accounted for 3.8% of cases, while people with Type 2 diabetes were the overriding majority (91.2%), and Diabetes Outpatient Clinics treated 75.4% of people with Type 2 diabetes. CONCLUSION: The Register is able to quantify the burden of disease, the first step in planning, implementing, and monitoring appropriate interventions. All data sources contributed to completeness and/or accuracy of the Register. Although all cases are identified by deterministic record linkage, manual revision and General Practitioner involvement are still necessary when information is insufficient or conflicting.
AIMS: To describe the methodology used to set up the Reggio Emilia (northern Italy) Diabetes Register. The prevalence estimates on December 31st, 2009 are also provided. METHODS: The Diabetes Register covers all residents in the Reggio Emilia province. The register was created by deterministic linkage of six routinely collected data sources through a definite algorithm able to ascertain cases and to distinguish type of diabetes and model of care: Hospital Discharge, Drug Dispensation, Biochemistry Laboratory, Disease-specific Exemption, DiabetesOutpatient Clinics, and Mortality databases. Using these data, we estimated crude prevalence on December 31st, 2009 by sex, age groups, and type of diabetes. RESULTS: There were 25,425 ascertained prevalent cases on December 31st, 2009. Drug Dispensation and Exemption databases made the greatest contribution to prevalence. Analyzing overlapping sources, more than 80% of cases were reported by at least two sources. Crude prevalence was 4.8% and 5.9% for the whole population and for people aged 18 years and over, respectively. Males accounted for 53.6%. Type 1 diabetes accounted for 3.8% of cases, while people with Type 2 diabetes were the overriding majority (91.2%), and DiabetesOutpatient Clinics treated 75.4% of people with Type 2 diabetes. CONCLUSION: The Register is able to quantify the burden of disease, the first step in planning, implementing, and monitoring appropriate interventions. All data sources contributed to completeness and/or accuracy of the Register. Although all cases are identified by deterministic record linkage, manual revision and General Practitioner involvement are still necessary when information is insufficient or conflicting.
Authors: F Fortunato; M G Cappelli; M M Vece; G Caputi; M Delvecchio; R Prato; D Martinelli Journal: J Diabetes Res Date: 2016-03-22 Impact factor: 4.011