Doctoral thesis

Essays on the cost structure of nonprofit nursing homes


98 p

Thèse de doctorat: Università della Svizzera italiana, 2013 (jury note: magna cum laude)

English Public provision of institutionalized long term care will pose an increasing challenge to the sustainability of public finances. Population ageing has been recognized as one of the main factors driving health care costs increase in Europe and is expected to further raise the demand of nursing home care. To ensure a sustainable system in the next decades, policymakers need evidence on the determinants of nursing care costs and how to best organize the sector to ensure efficient provision of care. This thesis aims at investigating issues regarding the cost structure of not-for profit nursing homes by using sound economic theory and rigorous empirical methodologies. The analysis is performed using a panel dataset of nursing homes located in a Swiss region. The first chapter investigates the impact of different forms of organizations on the cost efficiency of non-profit nursing homes. In particular, it uses an improved specification of the cost frontier as compared to previous studies based on Swiss data and sheds light on the issue of measuring constant inefficiency in the presence of unobserved heterogeneity. The second chapter analyses the impact of prospective payments on costs of nursing home care services. To evaluate the impact of the recent policy change - from retrospective to prospective payment - on nursing home costs, we adopt two empirical approaches: i) we estimate a model using a fixed-effects estimator (FE) with a time trend that is allowed to change after the policy reform; ii) we use a counterfactual approach (CF) where a fixed-effects model is used to predict costs for the years after the reform, and calculate the impact of the reform as the difference between observed- and predicted costs in each year. Finally, the third chapter focuses on the relationship between costs and quality in non- profit nursing homes. We use data on the clinical indicators derived from the Minimum Data Set. These quality indicators meet the taxonomy of the Structure-Process-Outcome (SPO) framework to measure quality in health care suggested by Donabedian (1988). As with respect to previous studies, we control for unobserved characteristics that may bias the relationship between costs and quality and address the issue of potential endogeneity of the quality indicators.
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