TY - GEN
T1 - Efficiency of environmental measures in Portuguese healthcare institutions using stochastic frontier analysis
AU - Chen-Xu, José
AU - Moutinho, Victor
N1 - Funding Information:
Acknowledgements This research was supported by Professor Cristina Chaves from the Faculty of Economics, University of Porto, who contributed by connecting the authors and with the brainstorming phase of this study.
Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.
PY - 2023
Y1 - 2023
N2 - Attention has in recent years shifted towards the environmental impact of human activities and the need to reach zero net carbon impact, including in the healthcare sector, being essential to review management processes to ensure their environmental sustainability. This study aims to evaluate the efficiency of environmental sustainability measures of institutions providing healthcare in Portugal’s National Health Service associated with water, energy, and waste management. A cross-sectional study was implemented in 24 institutions, with application of a Stochastic Frontier Analysis. The significant model for electricity showed photovoltaic panels to be an efficient measure, whereas LED lamps, solar panels and CO2 emissions quantification showed an association with inefficiency, with potential for investment. While the model for water consumption was not significant, water reuse and pre-treatment showed to be adequate. For total waste production, the model highlighted the relevance of green purchase and adequate waste management. When disaggregating for group IV waste, the model showed technical inefficiency of measures despite not being significant. While there are differences between primary and secondary care, there is margin for efficiency improvement, especially regarding energy and waste management, working with health managers and partners. Further research is needed to strengthen environmental policy changes.
AB - Attention has in recent years shifted towards the environmental impact of human activities and the need to reach zero net carbon impact, including in the healthcare sector, being essential to review management processes to ensure their environmental sustainability. This study aims to evaluate the efficiency of environmental sustainability measures of institutions providing healthcare in Portugal’s National Health Service associated with water, energy, and waste management. A cross-sectional study was implemented in 24 institutions, with application of a Stochastic Frontier Analysis. The significant model for electricity showed photovoltaic panels to be an efficient measure, whereas LED lamps, solar panels and CO2 emissions quantification showed an association with inefficiency, with potential for investment. While the model for water consumption was not significant, water reuse and pre-treatment showed to be adequate. For total waste production, the model highlighted the relevance of green purchase and adequate waste management. When disaggregating for group IV waste, the model showed technical inefficiency of measures despite not being significant. While there are differences between primary and secondary care, there is margin for efficiency improvement, especially regarding energy and waste management, working with health managers and partners. Further research is needed to strengthen environmental policy changes.
KW - Energy
KW - Environment
KW - Healthcare
KW - Sustainability
KW - Waste management
KW - Water
UR - http://www.scopus.com/inward/record.url?scp=85185567322&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-43559-1_34
DO - 10.1007/978-3-031-43559-1_34
M3 - Conference contribution
AN - SCOPUS:85185567322
SN - 9783031435584
T3 - Environmental Science and Engineering
SP - 361
EP - 370
BT - 9th International Conference on Energy and Environment Research
A2 - Caetano, Nídia S.
A2 - Felgueiras, Manuel Carlos
PB - Springer Science and Business Media Deutschland GmbH
CY - Switzerland AG
T2 - 9th International Conference on Energy and Environment Research, ICEER 2022
Y2 - 12 September 2022 through 16 September 2022
ER -
