hSNS publication in International Transactions in Operational Research

Optimizing payments based on efficiency, quality, complexity,and heterogeneity: the case of hospital funding

Authors: Diogo C. Ferreira; Alexandre M. Nunes; Rui C. Marques.

Abstract: In several countries around the world, public hospitals are paid for by the health care services they provide tothe population. Different funding systems are available, such as the Beveridge Model. Furthermore, paymentscan be either prospective, retrospective, or even a merging of both. Payments are usually nonoptimal in thePareto sense and disregard the quality of delivered services as well as the environment (either internal orexternal) in which hospitals operate. This gap may introduce inefficiencies and inequities in the health caresystem, which currently faces scenarios of reduction/scarcity of resources. Furthermore, there are problemsrelated to overpaying and misallocation of resources. Hence, payments should be optimized to guarantee anefficient allocation of resources to the health care systems. This study proposes a new best practice based tool,applying it to the Portuguese National Health Service. Considerable cost savings may emerge for inefficienthospitals if the model is successfully employed.

Keywords: hospital funding; best practices; efficiency; quality; heterogeneity.

[Bibliographic reference] Ferreira, DC; Marques, RC; Nunes, AM (2019). Optimising payments based on efficiency, quality, and heterogeneity: The case of hospitals funding. International Transactions in Operational Research. URL: https://doi.org/10.1111/itor.12713

About the journal: International Transactions in Operational Research (ITOR) aims to advance and promote the methodology, understanding, education and practice of Operational Research (OR) by creating bridges between theory and application and academics and practitioners. The journal also has the goal of fostering the interface of Operational Research with related disciplines, such as management science, data science and analytics, computer science, artificial intelligence and machine learning, economics and game theory, simulation and statistics, applied mathematics, mathematical programming and optimization, large scale networks, computer and social networks, among others.