Efficiency and quality of care in nursing homes: an Italian case study

Health Care Manag Sci. 2011 Mar;14(1):22-35. doi: 10.1007/s10729-010-9139-2. Epub 2010 Oct 5.

Abstract

This study investigates efficiency and quality of care in nursing homes. By means of Data Envelopment Analysis (DEA), the efficiency of 40 nursing homes that deliver their services in the north-western area of the Lombardy Region was assessed over a 3-year period (2005-2007). Lombardy is a very peculiar setting, since it is the only Region in Italy where the healthcare industry is organised as a quasi-market, in which the public authority buys health and nursing services from independent providers-establishing a reimbursement system for this purpose. The analysis is conducted by generating bootstrapped DEA efficiency scores for each nursing home (stage one), then regressing those scores on explanatory variables (stage two). Our DEA model employed two input (i.e. costs for health and nursing services and costs for residential services) and three output variables (case mix, extra nursing hours and residential charges). In the second-stage analysis, Tobit regressions and the Kruskall-Wallis tests of hypothesis to the efficiency scores were applied to define what are the factors that affect efficiency: (a) the ownership (private nursing houses outperform their public counterparts); and (b) the capability to implement strategies for labour cost and nursing costs containment, since the efficiency heavily depends upon the alignment of the costs to the public reimbursement system. Lastly, even though the public institutions are less efficient than the private ones, the results suggest that public nursing homes are moving towards their private counterparts, and thus competition is benefiting efficiency.

MeSH terms

  • Aged
  • Costs and Cost Analysis
  • Efficiency, Organizational*
  • Homes for the Aged / organization & administration*
  • Humans
  • Italy
  • Nursing Homes / organization & administration*
  • Organizational Case Studies
  • Private Sector / statistics & numerical data
  • Public Sector / statistics & numerical data
  • Quality of Health Care / organization & administration*