Incorporating preference information in network DEA models for measuring efficiency and productivity in healthcare

Funder

Organizational Unit

Publications

An Incentive-Based Framework for Analyzing the Alignment of Institutional Interventions in the Public Primary Healthcare Sector: The Portuguese Case

Publication . Pereira, Miguel Alves; Marques, Rui Cunha; Ferreira, Diogo Cunha; Ferreira, Diogo

Over the years, the Portuguese National Health Service has undergone several reforms to face the challenges posed by internal and external factors on the access to and quality of its health services. One of its most recent reforms addressed the primary healthcare sector, where understanding the incentives behind the actors of the inherent institutional interventions and how they are aligned with the governing health policies is paramount for reformative success. With the purpose of acknowledging the alignment of the primary healthcare sector’s institutional interventions from an incentive-based perspective, we propose a framework resting on a SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis, which was built in cooperation with a panel of decision-making actors from the Portuguese Ministry of Health. In the end, we derive possible policy implications and strategies. This holistic approach highlighted the positive impact of the primary healthcare reform in the upgrade of physical resources and human capital but stressed the geosocial asymmetries and the lack of intra- and inter-sectorial coordination. The proposed framework serves also as a guideline for future primary healthcare reforms, both national- and internationally.

2021-07-16Journal article

Open access

A network Data Envelopment Analysis to estimate nations’ efficiency in the fight against SARS-CoV-2

Publication . Pereira, Miguel Alves; Dinis, Duarte Caldeira; Ferreira, Diogo Cunha; Figueira, José Rui; Marques, Rui Cunha

The ongoing outbreak of SARS-CoV-2 has been deeply impacting health systems worldwide. In this context, it is pivotal to measure the efficiency of different nations’ response to the pandemic, whose insights can be used by governments and health authorities worldwide to improve their national COVID-19 strategies. Hence, we propose a network Data Envelopment Analysis (DEA) to estimate the efficiencies of fifty-five countries in the current crisis, including the thirty-seven Organisation for Economic Co-operation and Development (OECD) member countries, six OECD prospective members, four OECD key partners, and eight other countries. The network DEA model is designed as a general series structure with five single-division stages – population, contagion, triage, hospitalisation, and intensive care unit admission –, and considers an output maximisation orientation, denoting a social perspective, and an input minimisation orientation, denoting a financial perspective. It includes inputs related to health costs, desirable and undesirable intermediate products related to the use of personal protective equipment and infected population, respectively, and desirable and undesirable outputs regarding COVID-19 recoveries and deaths, respectively. To the best of the authors’ knowledge, this is the first study proposing a cross-country efficiency measurement using a network DEA within the context of the COVID-19 crisis. The study concludes that Estonia, Iceland, Latvia, Luxembourg, the Netherlands, and New Zealand are the countries exhibiting higher mean system efficiencies. Their national COVID-19 strategies should be studied, adapted, and used by countries exhibiting worse performances. In addition, the observation of countries with large populations presenting worse mean efficiency scores is statistically significant.

2022-12-30Journal article

Open access