Socio-economic disparities in the appropriateness of diabetes care in an Italian region: findings of AEQUITAS study

Background: To evaluate socio-economic disparities in diabetes prevalence and care in Marches (a region of central Italy) in 2003-2010 through a cross-sectional study. Methods: The databases of 52 general practitioners were mined for people with diabetes (age ≥20 years). These data were linked with records from other regional administrative databases. Healthcare disparities, specifically potentially preventable hospitalizations (PPH) related to diabetes and its complications, were analysed using participants’ gender, age, and education data and the Italian Deprivation Index. Crude, age-specific and gender-specific diabetes prevalence was estimated for each year of observation. A time-trend analysis was performed. Admissions that might have been prevented according to Agency for Healthcare Research and Quality criteria were used to calculate the PPH rate for each level of social condition indicators. Rate ratios and 95% confidence intervals were estimated with a multiple Poisson regression model. Results: The search found 6,494 participants with diabetes mellitus aged ≥20 years. Disease prevalence ranged from 5.4% (2003) to 7.8% (2010), with a significant 0.31% positive trend. Those aged ≤44 years were at significantly higher risk of PPH than older people. A significant PPH excess was found among people living in socio-economically disadvantaged areas. Education and gender did not significantly affect PPH. Conclusion. People with diabetes seem to use primary care services appropriately irrespective of socio-economic status. Outpatient services are not equally distributed on the regional territory; this may increase disease severity and/or the risk of diabetes complications and affect appropriateness of diabetes care

Prevalence of the prescription of potentially interacting drugs

The use of multiple medications is becoming more common, with a correspondingly increased risk of untoward effects and drug-related morbidity and mortality. We aimed at estimating the prevalence of prescription of relevant potentially interacting drugs and at evaluating possible predictors of potentially interacting drug exposure. We retrospectively analyzed data on prescriptions dispensed from January 2004 to August 2005 to individuals of two Italian regions with a population of almost 2.1 million individuals. We identified 27 pairs of potentially interacting drugs by examining clinical relevance, documentation, and volume of use in Italy. Subjects who received at least one prescription of both drugs were selected. Co-prescribing denotes “two prescriptions in the same day”, and concomitant medication “the prescription of two drugs with overlapping coverage”. A logistic regression analysis was conducted to examine the predictors of potential Drug-Drug Interaction (pDDIs). 957,553 subjects (45.3% of study population) were exposed to at least one of the drugs/classes of the 27 pairs. Overall, pDDIs occurred 2,465,819 times. The highest rates of concomitant prescription and of co-prescription were for ACE inhibitors+NSAIDs (6,253 and 4,621/100,000 plan participants). Considering concomitance, the male/female ratio was <1 in 17/27 pairs (from 0.31 for NSAIDs-ASA+SSRI to 0.74 for omeprazole+clopidogrel). The mean age was lowest for methotrexate pairs (+omeprazole, 59.9 years; +NSAIDs-ASA, 59.1 years) and highest for digoxin+verapamil (75.4 years). In 13/27 pairs, the mean ages were ≥70 years. On average, subjects involved in pDDIs received ≥10 drugs. The odds of exposure were more frequently higher for age ≥65 years, males, and those taking a large number of drugs. A substantial number of clinically important pDDIs were observed, particularly among warfarin users. Awareness of the most prevalent pDDIs could help practitioners in preventing concomitant use, resulting in a better quality of drug prescription and potentially avoiding unwanted side effects

ASSET (Age/Sex Standardised Estimates of Treatment): a research model to improve the governance of prescribing funds in Italy

BACKGROUND: The primary objective of this study was to make the first step in the modelling of pharmaceutical demand in Italy, by deriving a weighted capitation model to account for demographic differences among general practices. The experimental model was called ASSET (Age/Sex Standardised Estimates of Treatment). METHODS AND MAJOR FINDINGS: Individual prescription costs and demographic data referred to 3,175,691 Italian subjects and were collected directly from three Regional Health Authorities over the 12-month period between October 2004 and September 2005. The mean annual prescription cost per individual was similar for males (196.13 euro) and females (195.12 euro). After 65 years of age, the mean prescribing costs for males were significantly higher than females. On average, costs for a 75-year-old subject would be 12 times the costs for a 25-34 year-old subject if male, 8 times if female. Subjects over 65 years of age (22% of total population) accounted for 56% of total prescribing costs. The weightings explained approximately 90% of the evolution of total prescribing costs, in spite of the pricing and reimbursement turbulences affecting Italy in the 2000-2005 period. The ASSET weightings were able to explain only about 25% of the variation in prescribing costs among individuals. CONCLUSIONS: If mainly idiosyncratic prescribing by general practitioners causes the unexplained variations, the introduction of capitation-based budgets would gradually move practices with high prescribing costs towards the national average. It is also possible, though, that the unexplained individual variation in prescribing costs is the result of differences in the clinical characteristics or socio-economic conditions of practice populations. If this is the case, capitation-based budgets may lead to unfair distribution of resources. The ASSET age/sex weightings should be used as a guide, not as the ultimate determinant, for an equitable allocation of prescribing resources to regional authorities and general practices

Number and proportion of patients involved in pDDIs.

<p>Number and proportion of patients involved in pDDIs.</p

Distribution of ASSET clusters compared to the distribution of Italian population (ISTAT, 2005)

<p>Distribution of ASSET clusters compared to the distribution of Italian population (ISTAT, 2005)</p

Comparison of 2005 population of two Italian regions (Liguria and Sardinia) weighted using the ASSET's weights.

<p>Comparison of 2005 population of two Italian regions (Liguria and Sardinia) weighted using the ASSET's weights.</p