Spatial disparities in hospital performance (original) (raw)
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Spatial effects in hospital expenditures: A district level analysis
Health Economics, 2017
Geographical clusters in health expenditures are well documented and accounting for spatial interactions may contribute to properly identify the factors affecting the use of health services the most. As for hospital care, spillovers may derive from strategic behaviour of hospitals and from patients' preferences that may induce mobility across jurisdictions, as well as from geographically-concentrated risk factors, knowledge transfer and interactions between different layers of care. Our paper focuses on a largely overlooked potential source of spillovers in hospital expenditure: the heterogeneity of primary care providers' behaviour. To do so, we analyse expenditures associated to avoidable hospitalisations separately from expenditures for highly complex treatments, as the former are most likely affected by General Practitioners, while the latter are not. We use administrative data for Italy's Region Emilia Romagna between 2007 and 2010. Since neighbouring districts may belong to different Local Health Authorities (LHAs), we employ a spatial contiguity matrix that allows to investigate the effects of geographical and institutional proximity and use it to estimate Spatial Autoregressive and Spatial Durbin Models.
Exploring the spatial pattern in hospital admissions
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The determinants for the number of inpatient hospital admissions across Danish municipalities are analysed using balanced panel data from the period 1998-2004. The determinants include socio-demographic variables, home help service, residential homes capacity, proxy variables for morbidity, utilisation of primary care services, accessibility of hospitals and a number of other factors. Panel effects in the form of intra-municipal correlation and heterogeneity across years are controlled for. Spatial spillover effects across municipalities will be investigated in order to disclose the spatial dynamics of hospital admissions. Reverse causalities among the number of hospital admissions and certain health systems characteristics are further controlled for. The results are shown to be highly sensitive to such adjustments, as the effects of determinants -including those over which the municipalities exert some control -are seriously overestimated if such features are ignored.
Exploring the small area variation and spatial patterns in outpatient treatments
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The determinants for the number of outpatient hospital treatments across Danish municipalities are analysed using balanced panel data from the period 1998-2004. The determinants include socio-demographic variables, home help service, residential homes capacity, proxy variables for morbidity, utilisation of primary care services, accessibility of hospitals and a number of other factors. Panel effects in the form of intramunicipal correlation and heterogeneity across years are controlled for. Spatial spillover effects across municipalities will be investigated in order to disclose the spatial dynamics of outpatient treatments. The results reveal substantial heterogeneity and dependency across time, as well as presence of a significant spatial spillover effect. Reverse causalities among the number of hospital outpatient treatments and certain health systems characteristics are further controlled for. The results are shown to be highly sensitive to such adjustments, as the effects of determinants-including those over which the municipalities exert some control-are seriously overestimated if such features are ignored.
PloS one, 2017
To illustrate the ability of hierarchical Bayesian spatio-temporal models in capturing different geo-temporal structures in order to explain hospital risk variations using three different conditions: Percutaneous Coronary Intervention (PCI), Colectomy in Colorectal Cancer (CCC) and Chronic Obstructive Pulmonary Disease (COPD). This is an observational population-based spatio-temporal study, from 2002 to 2013, with a two-level geographical structure, Autonomous Communities (AC) and Health Care Areas (HA). The Spanish National Health System, a quasi-federal structure with 17 regional governments (AC) with full responsibility in planning and financing, and 203 HA providing hospital and primary care to a defined population. A poisson-log normal mixed model in the Bayesian framework was fitted using the INLA efficient estimation procedure. The spatio-temporal hospitalization relative risks, the evolution of their variation, and the relative contribution (fraction of variation) of each of...
A Window on Geographic Variation in Health Care: Insights from EuroHOPE
Health economics, 2015
The aim of EuroHOPE was to provide new evidence on the performance of healthcare systems, using a disease-based approach, linkable patient-level data and internationally standardized methods. This paper summarizes its main results. In the seven EuroHOPE countries, the Acute Myocardial Infarction (AMI), stroke and hip fracture patient populations were similar with regard to age, sex and comorbidity. However, non-negligible geographic variation in mortality and resource use was found to exist. Survival rates varied to similar extents between countries and regions for AMI, stroke, hip fracture and very low birth weight. Geographic variation in length of stay differed according to type of disease. Regression analyses showed that only a small part of geographic variation could be explained by demand and supply side factors. Furthermore, the impact of these factors varied between countries. The findings show that there is room for improvement in performance at all levels of analysis and c...
Patient outcomes and regional planning of coronary care services: A location-allocation approach
Social Science & Medicine, 1990
We explore the use of patient outcome criteria in planning the locations of critical care health services. Two attributes of the regional distribution of health services which influence health outcomes are: (1) the geographical accessibility of services and (2) the number of patients served by each facility (the patient volume). A model incorporating both factors is developed to determine the number, sizes, and locations of coronary care services in a region in order lo maximize patient outcomes. We examine the implications and use of the model in an investigation of the location of coronary care units in rural upstate New York. The results indicate that a system consisting of fewer, well-located coronary care units would be superior for patient survival than the existing system of many dispersed units. Disparities in access to services between urban and rural areas are discussed.
BMC Public Health, 2017
Background: It is now widely accepted that social and physical environment participate in shaping health. While mortality is used to guide public health policies and is considered as a synthetic measure of population health, few studies deals with the contextual features potentially associated with mortality in a representative sample of an entire country. This paper investigates the possible role of area deprivation (FDep99) and travel time to health care on French cause-specific mortality in a proper multilevel setting. Methods: The study population was a 1% sample representative of the French population aged from 30 to 79 years in 1990 and followed up until 2007. A frailty Cox model was used to measure individual, contextual effects and spatial variances for several causes of death. The chosen contextual scale was the Zone d'Emploi of 1994 (348 units) which delimits the daily commute of people. The geographical accessibility to health care score was constructed with principal component analysis, using 40 variables of hospital specialties and health practitioners' travel time. Results: The outcomes highlight a positive and significant association between area deprivation and mortality for all causes (HR = 1.24), cancers, cerebrovascular diseases, ischemic heart diseases, and preventable and amenable diseases (HR from 1.14 to 1.29). These contextual associations exhibit no substantial differences by sex except for premature ischemic heart diseases mortality which was much greater in women. Unexpectedly, mortality decreased as the time to reach health care resources increased. Only geographical disparities in cerebrovascular and ischemic heart diseases mortality were explained by compositional and contextual effects. Discussion: The findings suggest the presence of confounding factors in the association between mortality and travel time to health care, possibly owing to population density and health-selected migration. Although the spatial scale considered to define the context of residence was relatively large, the associations with area deprivation were strong in comparison to the existing literature and significant for almost all the causes of deaths investigated. Conclusion: The broad spectrum of diseases associated with area deprivation and individual education support the idea of a need for a global health policy targeting both individual and territories to reduce social and socio-spatial inequalities.
Using Simulated Data to Examine the Determinants of Acute Hospital Demand at the Small Area Level
Geographical Analysis, 2013
The aim of this article is to establish whether spatial variation exists in acute hospital utilization in Ireland and, if it does, to identify the microlevel factors influencing this variation. First, an alignment process is used to calibrate the acute inpatient attendance and nights spent in hospital variables produced by a spatial microsimulation model at both the national and the subnational levels. Comparing the results of the national and subnational alignment allows us to examine whether spatial variation exists. Second, after establishing that hospital utilization displays a significant spatial pattern, we use a nationally representative survey to determine which individual-level factors significantly affect inpatient attendance and the number of nights spent in hospitals. Using the calibrated data from the aforementioned spatial microsimulation model, we examine whether the spatial patterns of those variables found to influence hospital utilization match the spatial pattern of actual hospital utilization rates at the small area, electoral division level. That is, are the individuals/areas with the highest demand for acute hospital services utilizing acute hospital services? Finally, the results of this research are discussed in relation to both the national and international literature.
Geographic Knowledge Spillovers: Evidence from the Treatment of Heart Attacks
Knowledge spillovers are often cited as a reason for geographic specialization in production. We test the empirical implications of knowledge spillovers for specialization in the treatment of heart attacks. A large literature in economics and medicine documents persistent variation across areas in the use of surgical treatments for clinically identical patients, which is unrelated to average patient outcomes. We show that a very simple equilibrium Roy model of patient treatment choice with geographic knowledge spillovers can generate these facts. In addition, the model predicts that high-use areas will have higher returns to surgical management, better outcomes among patients most appropriate for surgery, and worse outcomes among patients least appropriate for surgery. We find strong empirical support for these and other predictions of the model, and decisively reject alternative explanations for the geographic variation in medical care.