Risk matrices are adopted and recommended by many organizations, but the way they are usually constructed violates some basic theoretical principles, giving rise to inconsistent risk ratings. This paper studies ways in which multiple criteria and portfolio decision analyses can improve the design and deployment of risk matrices, using MACBETH (the \Measuring Attractiveness by a Categorical Based Evaluation TecHnique"). Firstly, it introduces`value risk-matrices', built with MACBETH in the following modeling steps: (1) building a value measurement scale on each impact dimension and constructing a subjective probability scale, (2) additive aggregation of the value scales into a cumulative value scale, and (3) design of the value risk-matrix. The value and probability scores of risks are plotted in the matrix and its analysis informs the identi¯cation of mitigation actions, which can then be prioritized making use of the recent portfolio module of the MACBETH decision support system. Taken all together, the paper sketches a new modeling approach for Improving Risk Matrices (IRIS).
Risk matrices (RMs) are extensively used for risk management, namely in occupational health and safety (OHS) settings, despite suffering from well-known methodological problems. The IRIS approach (improving RMs) proposes to overcome those problems throughout the construction of value RMs (VRMs) that shift the basis of risk analysis from probability versus impact to probability versus "impact value." This article describes the real-world participatory process of building a VRM for an OHS unit. The complexity of the case required the enhancement of IRIS with soft mapping tools to structure the risk impact dimensions, the MACBETH-Choquet (where MACBETH is measuring attractiveness by a categorical based evaluation technique) procedure to model interdependent impacts, and a system of rules to risk probability assessment. A discussion on the model-building process is presented, namely addressing the cognitive burden imposed on the participants by different value elicitation procedures, which informed the design of a decision support system to assist the managers of the OHS unit in using the VRM.
Understanding imbalances between the supply and demand of the human resour- ces for health (HRH) is essential for enhancing health outcomes. Addressing the HRH demand is particularly challenging, especially given the deficit of accurate data and surplus of unresolved methodological flaws. This study presents a systematic review of the literature surrounding HRH demand and answers the following key questions: How has HRH demand been addressed? What are the harms and barriers that accompany HRH demand modeling? This systematic review was performed following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) statement. Relevant keywords were used in a thorough search of the PubMed/MEDLINE, SCOPUS, and Web of Science databases. A total of 2,599 papers were retrieved and evaluated according to their title and abstract. Of these, the full-text of 400 papers was analyzed, 53 of which successfully met the inclusion criteria in our study. While the topic’s relevance is widespread, it still lacks a validated approach to model HRH demand adequately. The main characteristics of the applied methods are presented, such as their application complexity by health policymakers. Opportunities and orientations for further research are also highlighted.
Access to health care services is a key concept in the formulation of health policies to improve the population’s health status and to mitigate inequities in health. Previous studies have significantly enhanced our understanding and knowledge of the role played by spatial distribution of health facilities in sustaining population health, with extensive research being devoted to the place-based accessibility theory, with special focus on the gravity-based methods. Although they represent a good starting point to analyse disparities across different regions, the results are not intelligible for policy-making purposes. Given the weaknesses of these methods and the multidimensional nature of the topic, this study intends to: (i) highlight the main measurements of access and their major challenges; and (ii) propose a framework based on multiple criteria decision analysis methods and GIS to appraise the population’s accessibility to health facilities. In particular, this framework is based on a new variant of the UTASTAR method, which requires decision makers and/or experts preference information, in the form of an ordinal ranking, similarly to the UTASTAR method, but to which cardinal information is also added. A numerical example is presented to illustrate the application of the proposed methodology.
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