Burden of Diabetes Mellitus Estimated with a Longitudinal Population-Based Study Using Administrative Databases

Objective: To assess the epidemiologic and economic burden of diabetes mellitus (DM) from a longitudinal population-based study. Research Design and Methods: Lombardy Region includes 9.9 million individuals. Its DM population was identified through a data warehouse (DENALI), which matches with a probabilistic linkage demographic, clinical and economic data of different Healthcare Administrative databases. All individuals, who, during the year 2000 had an hospital discharge with a IDC-9 CM code 250. XX, and/or two consecutive prescriptions of drugs for diabetes (ATC code A10XXXX) within one year, and/or an exemption from co-payment healthcare costs specific for DM, were selected and followed up to 9 years. We calculated prevalence, mortality and healthcare costs (hospitalizations, drugs and outpatient examinations/visits) from the National Health Service's perspective. Results: We identified 312,223 eligible subjects. The study population (51% male) had a mean age of 66 (from 0.03 to 105.12) years at the index date. Prevalence ranged from 0.4% among subjects aged <= 45 years to 10.1% among those >85 years old. Overall 43.4 deaths per 1,000 patients per year were estimated, significantly (p<0.001) higher in men than women. Overall, 3,315(sic)/patient-year were spent on average: hospitalizations were the cost driver (54.2% of total cost). Drugs contributed to 31.5%, outpatient claims represented 14.3% of total costs. Thirty-five percent of hospital costs were attributable to cerebro-/cardiovascular reasons, 6% to other complications of DM, and 4% to DM as a main diagnosis. Cardiovascular drugs contributed to 33.5% of total drug costs, 21.8% was attributable to class A (16.7% to class A10) and 4.3% to class B (2.4% to class B01) drugs. Conclusions: Merging different administrative databases can provide with many data from large populations observed for long time periods. DENALI shows to be an efficient instrument to obtain accurate estimates of burden of diseases such as diabetes mellitus.