Aims/introduction: We aimed at estimating the prevalence and at identifying the frequent comorbidities of diabetes mellitus in a region of northeastern Italy from administrative health data.
Materials and methods: The prevalence was estimated according to two disease definitions, based on administrative health data. Association rule mining was used to detect comorbid diagnoses that coexisted with a diagnosis of diabetes among patients admitted to the regional hospitals.
Results: The prevalence of known diabetes in 2010 was 6.0-8.1%, with great variations by age class (from approximately 2% <60 years to more than 20% in some elderly age groups). Of 155,494 patients admitted to the hospital in 2011, 9,358 had a diagnosis of diabetes. A total of 12 rules satisfied our criteria for support (>0.5%) and confidence (>5%), and identified nine frequent isolated comorbidities and three pairs of comorbid diagnoses. The rule with the highest support (2.4%) and confidence (39.5%) identified the combination of diabetes and essential hypertension.
Conclusions: Association rule mining was useful, because it showed the complexity of diabetic patients. Clinical management of those patients cannot neglect comorbidities.
Keywords: Association rule mining; Diabetes mellitus; Hospital discharge data.