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http://hdl.handle.net/10071/22059
acessibilidade
Title: From problem structuring to optimization: a multi-methodological framework to assist the planning of medical training
Authors: Cardoso-Grilo, T.
Monteiro, M.
Oliveira, M. D.
Amorim-Lopes, M.
Barbosa-Póvoa, A.
Keywords: CATWOE
Medical training
MILP
Multi-methodology
OR in Health Services
Issue Date: 2019
Publisher: Elsevier
Abstract: Medical training is an intricate and long process, which is compulsory to medical practice and often lasts up to twelve years for some specialties. Health stakeholders recognise that an adequate planning is crucial for health systems to deliver necessary care services. However, proper planning needs to account for complexity related with the setting of medical school vacancies and of residency programs, which are highly influenced by multiple stakeholders with diverse perspectives and views, as well as by the specificities of medical training. Aiming at building comprehensive models with a potential to assist health decision-makers, this article develops a multi-methodological framework to assist the planning of medical training under such a complex environment. It combines the structuring of the objectives and specificities of the medical training problem with a Soft Systems Methodology through the CATWOE (Customer, Actor, Transformation, Weltanschauung, Owner, Environment) approach, and the formulation of a Mixed Integer Linear Programming model that considers all relevant aspects. Considering the specificities of countries based on a National Health Service structure, a multi-objective planning model emerges, informing on how many vacancies should be opened/closed per year in medical schools and in each specialty. This model aims at (i) minimizing imbalances between medical demand and supply; (ii) minimizing costs; and (iii) maximizing equity across medical specialties. A case study in Portugal is explored so as to illustrate the applicability of the proposed multi-methodology, showing the relevance of proper structuring for planning models having the potential to inform health decision-makers and planners in practice.
Peer reviewed: yes
URI: http://hdl.handle.net/10071/22059
DOI: 10.1016/j.ejor.2018.08.003
ISSN: 0377-2217
Ciência-IUL: https://ciencia.iscte-iul.pt/id/ci-pub-50065
Accession number: WOS:000452345600021
Appears in Collections:BRU-RI - Artigos em revistas científicas internacionais com arbitragem científica

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