Factors associated with hospitalisations in chronic conditions deemed avoidable: ecological study in the Spanish healthcare system

Abstract

ObjectivesPotentially avoidable hospitalisations have been used as a proxy for primary care quality. We aimed to analyse the ecological association between contextual and systemic factors featured in the Spanish healthcare system and the variation in potentially avoidable hospitalisations for a number of chronic conditions.MethodsA cross-section ecological study based on the linkage of administrative data sources from virtually all healthcare areas (n=202) and autonomous communities (n=16) composing the Spanish National Health System was performed. Potentially avoidable hospitalisations in chronic conditions were defined using the Spanish validation of the Agency for Health Research and Quality (AHRQ) preventable quality indicators. Using 2012 data, the ecological association between potentially avoidable hospitalisations and factors featuring healthcare areas and autonomous communities was tested using multilevel negative binomial regression.ResultsIn 2012, 151 468 admissions were flagged as potentially avoidable in Spain. After adjusting for differences in age, sex and burden of disease, the only variable associated with the outcome was hospitalisation intensity for any cause in previous years (incidence risk ratio 1.19 (95% CI 1.13 to 1.26)). The autonomous community of residence explained a negligible part of the residual unexplained variation (variance 0.01 (SE 0.008)). Primary care supply and activity did not show any association.ConclusionsThe findings suggest that the variation in potentially avoidable hospitalisations in chronic conditions at the healthcare area level is a reflection of how intensively hospitals are used in a healthcare area for any cause, rather than of primary care characteristics. Whether other non-studied features at the healthcare area level or primary care level could explain the observed variation remains uncertain.

Evolution of public hospitals expenditure by healthcare area in the Spanish National Health System: the determinants to pay attention to

“…Indeed, socioeconomic factors have not been included as these factors are not annually available in Spain at HCA level for the whole period of analysis. Previous research in our context found a very small effect of socioeconomic differences on hospital utilization [ 9 , 25 ]. All in all, as geographic analyses act as a natural experiment built upon big areas (75% of the HCA in our study have more than 94,000 inhabitants), the distribution of latent or unobserved need factors not included in the regression models will reflect a reasonably homogeneous distribution across HCA.…”

“…Need was defined using four different ecological variables: a) human sex ratio as the ratio of males to females residing in a HCA; b) ageing index as the ratio of people aged 65 and older to individuals aged 15 and younger; c) over-ageing index as the proportion of people aged 75 and older to those aged 64 and older; and d) burden of disease (i.e., population morbidity) as the cumulative number of hospitalisations for hip fracture, acute myocardial infarction, ischaemic stroke and cancer of the colon, lung or breast treated surgically aged 40 and older. These hospitalisations very likely reflect differences in health populations across HCAs and not differences in supply-side factors [ 8 , 9 ].…”

Unwarranted Variations in Healthcare: The Role of Business Intelligence

“…Rizza et al, 2007;Griffiths et al, 2010;Rosano et al, 2013), confirming the influencing role that primary care plays on preventable admissions. Our findings, however, are in contrast with the work by Angulo-Pueyo et al (2017), who found no association between primary care supply and ACSCs in Spain. As their dependent variable, the authors considered a mixed factor obtained from several ACSCs (including COPD and CHF) and a variable factor to measure primary care supply composed of the number of primary care centres plus the number of GP and nurse consultations.…”

“…Moreover, the significant variables are not exactly the same for all three conditions. Thus, using a single factor instead of individual variables may contribute towards generating the insignificant association between primary care resources and ACSC admissions found in (Angulo-Pueyo et al, 2017).…”

Data Envelopment Analysis Applications on Primary Health Care Using Exogenous Variables and Health Outcomes

“…• Number of avoidable hospitalisations. This refers to the number of hospital admissions of the population over 40 years old caused by pathologies that should be controlled from the primary health centres [48] and as such should not result in an admission.…”