BMC Public Health (Jan 2013)

Chronic disease prevalence from Italian administrative databases in the VALORE project: a validation through comparison of population estimates with general practice databases and national survey

  • Gini Rosa,
  • Francesconi Paolo,
  • Mazzaglia Giampiero,
  • Cricelli Iacopo,
  • Pasqua Alessandro,
  • Gallina Pietro,
  • Brugaletta Salvatore,
  • Donato Daniele,
  • Donatini Andrea,
  • Marini Alessandro,
  • Zocchetti Carlo,
  • Cricelli Claudio,
  • Damiani Gianfranco,
  • Bellentani Mariadonata,
  • Sturkenboom Miriam CJM,
  • Schuemie Martijn J

DOI
https://doi.org/10.1186/1471-2458-13-15
Journal volume & issue
Vol. 13, no. 1
p. 15

Abstract

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Abstract Background Administrative databases are widely available and have been extensively used to provide estimates of chronic disease prevalence for the purpose of surveillance of both geographical and temporal trends. There are, however, other sources of data available, such as medical records from primary care and national surveys. In this paper we compare disease prevalence estimates obtained from these three different data sources. Methods Data from general practitioners (GP) and administrative transactions for health services were collected from five Italian regions (Veneto, Emilia Romagna, Tuscany, Marche and Sicily) belonging to all the three macroareas of the country (North, Center, South). Crude prevalence estimates were calculated by data source and region for diabetes, ischaemic heart disease, heart failure and chronic obstructive pulmonary disease (COPD). For diabetes and COPD, prevalence estimates were also obtained from a national health survey. When necessary, estimates were adjusted for completeness of data ascertainment. Results Crude prevalence estimates of diabetes in administrative databases (range: from 4.8% to 7.1%) were lower than corresponding GP (6.2%-8.5%) and survey-based estimates (5.1%-7.5%). Geographical trends were similar in the three sources and estimates based on treatment were the same, while estimates adjusted for completeness of ascertainment (6.1%-8.8%) were slightly higher. For ischaemic heart disease administrative and GP data sources were fairly consistent, with prevalence ranging from 3.7% to 4.7% and from 3.3% to 4.9%, respectively. In the case of heart failure administrative estimates were consistently higher than GPs’ estimates in all five regions, the highest difference being 1.4% vs 1.1%. For COPD the estimates from administrative data, ranging from 3.1% to 5.2%, fell into the confidence interval of the Survey estimates in four regions, but failed to detect the higher prevalence in the most Southern region (4.0% in administrative data vs 6.8% in survey data). The prevalence estimates for COPD from GP data were consistently higher than the corresponding estimates from the other two sources. Conclusion This study supports the use of data from Italian administrative databases to estimate geographic differences in population prevalence of ischaemic heart disease, treated diabetes, diabetes mellitus and heart failure. The algorithm for COPD used in this study requires further refinement.

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