What Counts in Nursing Homes’ Quality and Efficiency? Results From Data Envelopment Analysis in Italy

Author:

Barsanti Sara1ORCID,Bunea Anita Mariana1,Colombini Giulia1

Affiliation:

1. Management and Health Laboratory, Institute of Management - Department EMbeDS, Sant’Anna School of Advanced Studies, Pisa, Italy

Abstract

Purpose: Economic resource constrains in public spending budget in a country, such as Italy, with an ageing population with high incidence of chronic diseases calls for better strategies to improve measuring quality and efficiency in nursing homes (NHs). This paper analyses the efficiency of 40 NHs based in Tuscany considering not only structural characteristics but also quality of care, including residents, relatives and staff satisfaction. Methodology: We run a classic data envelopment analysis (DEA) on data gathered by the NHs’ regional performance evaluation system. We include as inputs the number of total work hours as labour and the daily cost for services as economic resources. As outputs we include measures for quality of care (number of falls, urinary infections and antidepressants), satisfaction (residents, relatives and professionals) and quality of life (days of recreational activities). We run a multivariate regression to analyse the determinants of previously obtained efficiency scores considering factors such as: institutional (ownership), managerial (training) and clinical (patient’s severity). Findings: Results find 35% efficient NHs. Moreover, management and the managerial factor (staff trained in end-of-life support) are predictors of the efficiency score. Originality: Our study uses satisfaction (residents, relatives and professionals) measures as proxy for quality output in the DEA model and measures related to staff management (eg training) as predictors of the efficiency scores.

Publisher

SAGE Publications

Subject

Health Policy

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3