Inefficiencies in a healthcare system with a regulatory split of power: a spatial panel data analysis of avoidable hospitalisations in Austria.

The European Journal of Health Economics Pub Date : 2020-02-01 Epub Date: 2019-09-09 DOI:10.1007/s10198-019-01113-7
Anna-Theresa Renner
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Abstract

Despite generous universal social health insurance with little formal restrictions of outpatient utilisation, Austria exhibits high rates of avoidable hospitalisations, which indicate the inefficient provision of primary healthcare and might be a consequence of the strict regulatory split between the Austrian inpatient and outpatient sector. This paper exploits the considerable regional variations in acute and chronic avoidable hospitalisations in Austria to investigate whether those inefficiencies in primary care are rather related to regional healthcare supply or to population characteristics. To explicitly account for inter-regional dependencies, spatial panel data methods are applied to a comprehensive administrative dataset of all hospitalisations from 2008 to 2013 in the 117 Austrian districts. The initial selection of relevant covariates is based on Bayesian model averaging. The results of the analysis show that supply-side variables, such as the number of general practitioners, are significantly associated with decreased chronic and acute avoidable hospitalisations, whereas characteristics of the regional population, such as the share of population with university education or long-term unemployed, are less relevant. Furthermore, the spatial error term indicates that there are significant spatial dependencies between unobserved characteristics, such as practice style or patients' utilization behaviour. Not accounting for those would result in omitted variable bias.

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效率低下的医疗保健系统与监管权力分裂:空间面板数据分析可避免住院在奥地利。
尽管有慷慨的全民社会健康保险,对门诊病人的使用几乎没有正式限制,但奥地利可避免的住院率很高,这表明初级保健的提供效率低下,可能是奥地利住院和门诊部门之间严格的监管分歧的结果。本文利用奥地利急性和慢性可避免住院的相当大的区域差异来调查初级保健的效率低下是否与区域医疗保健供应或人口特征有关。为了明确考虑区域间的依赖关系,空间面板数据方法应用于奥地利117个地区2008年至2013年所有住院的综合行政数据集。相关协变量的初始选择基于贝叶斯模型平均。分析结果表明,供应方面的变量,如全科医生的数量,与减少慢性和急性可避免的住院治疗显著相关,而区域人口的特征,如受过大学教育或长期失业的人口比例,相关性较低。此外,空间误差项表明,在未观察到的特征(如执业风格或患者的利用行为)之间存在显著的空间依赖性。不考虑这些因素会导致忽略变量偏差。
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