Abstract

Background: Hospitalization may often be prevented by timely and effective outpatient care either bypreventing the onset of an illness, controlling an acute illness or managing a chronic disease with an appropriatefollow-up. The objective of the study is to examine the variability of hospital admissions within Italian regionsfor Ambulatory Care Sensitive Conditions (ACSCs), and their relationship with primary care supply.Methods: Hospital discharge data aggregated at a regional level collected in 2005 were analysed by typeof ACS conditions. Main outcome measures were regional hospital admission rates for ACSCs. Negativebinomial models were used to analyse the association with individual risk factors (age and gender) andregional risk factors (propensity to hospitalisation and prevalence of specific conditions).Non-parametric correlation indexes between standardised hospital admission rates and quantitativemeasures of primary care services were calculated.Results: ACSC admissions accounted for 6.6% of total admissions, 35.7% were classified as acuteconditions and 64.3% as chronic conditions. Admission rates for ACSCs varied widely across Italian regionswith different patterns for chronic and acute conditions. Southern regions showed significantly higher ratesfor chronic conditions and North-eastern regions for acute conditions. We found a significant negativeassociation between the provision of ambulatory specialist services and standardised hospitalization rates(SHR) for ACS chronic conditions (r=-0.50; p=0.02) and an inverse correlation among SHR for ACS acuteconditions and the rate of GPs per 1,000 residents, although the latter was not statistically significant.Conclusions: In Italy, about 480,000 inpatient hospital admissions in 2005 were attributable to ACSCs. Evenadjusting for potential confounders, differences in hospital admissions for ACSCs among Italian regionswere found. Such differences can be appropriately used to assess the effectiveness and/or appropriatenessof the primary care provided within different regions.

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