Tools4MCDA: An R-Package to estimate spatial fishing effort, weight and value of landings using multi-criteria decision analysis

Our article deals with the governance of responsible research and innovation (RRI) and aims to set out a first psychologically grounded decision-theoretic method for the governance of RRI. We approach the governance of RRI as a multicriteria group decision analysis problem of delivering social welfare in an innovation ecosystem. Following such a methodological approach, we develop a psychologically grounded multicriteria group decision analysis method that integrates in its value function the main psychological effects captured in the value function of prospect theory as the main theory of individual decision-making under risk. The method first applies a psychologically motivated multicriteria decision analysis function that measures the welfare delivered to all stakeholders involved in a research and innovation consortium. The method then applies a social welfare function on the welfare measurements of stakeholders to propose a social welfare solution that emerges as an RRI-compliant solution for the consortium. The results are a first psychologically grounded multicriteria group decision analysis method and its first application to the governance of RRI. The implications of our results are theoretical but also practical, as our method contributes not only to the established field of multicriteria decision analysis by setting out new method but also to the field of RRI by delivering a psychologically grounded decision-theoretic general method for the governance of RRI.

BACKGROUND: In the context of the progressive movement towards patientcentred care, patient-specific decision support is an important focus of interest. Many diagnostic and treatment patient decision aids (PDAs) are now available to help patients make informed choice decisions. An increasing number of these are software-based, with some available online. Multi-Criteria Decision Analysis (MCDA) is a potentially useful technique on which to base a software-assisted PDA, especially when the decision is complex - as is the case in choosing the best treatment for non-small cell lung cancer – but it has so far been relatively little exploited in this area. The use of any from a number of existing MCDA-based software applications in the development and delivery of a MCDA-based interactive PDA can be an effective way of achieving “best-practice” or normative standards of decision making, such as 1) a well-constructed set of decision criteria or 2) logically consistent patient preferences. However, it also involves the use of resources such as the time and cognitive effort involved in decision-making. The comparative evaluation of alternative MCDA-based software applications in developing and delivering a PDA therefore involves trade-offs between decision effectiveness and decision resource criteria moving from the normative to the prescriptive. MCDA is an ideal tool for this meta-evaluation task as well as for the adoption decision itself. AIM: To analyse, as proof of concept, the use of MCDA for the development, implementation and evaluation of interactive PDAs in routine clinical practice. OBJECTIVES: 1. To assess the use with clinicians in the Spanish NHS of two alternative MCDA software applications which implement dissimilar MCDA techniques in the development of a PDA in routine clinical practice; 2. To assess the use with clinicians in the Spanish NHS of the same two alternative MCDA software applications in the implementation of a PDA in an environment replicating actual clinical consultations; 3. To build a meta-multi-criteria decision model based on the Decision Resources Decision Effectiveness Analysis (DRDEA) framework and assess the use of this model by clinicians in the Spanish NHS to make the choice between the two MCDA applications as the basis for a PDA. METHODS: 1) Two dissimilar MCDA software applications served as a basis for the development of a lung cancer clinical management PDA in close collaboration with two different groups of three clinicians from two different Spanish NHS hospitals (H1 and H2): 1) Expert Choice, which implements the Analytic Hierarchy Process (AHP) MCDA approach; 2) Annalisa in Elicia (ALEL), which implements the Simple Attribute Weighting (SAW) MCDA approach. The process of codevelopment of the PDA in hospitals H1 and H2 was documented; 2) Expert Choice was used to implement (i.e. deliver) the lung cancer clinical management PDA in three hypothetical consultations in hospital H1. In each consultation, one of the three clinicians involved in the development of the tool, with support by this researcher, guided a proxy patient (a non-clinical member of hospital staff) through the PDA. The same process was repeated with the MCDA software ALEL in hospital H2. The process of delivery of the PDA in hospitals H1 and H2 was documented; 3) This researcher built a meta-multi-criteria decision model based on the DRDEA framework to help clinicians choose between different MCDA software applications as the basis of a PDA. The MCDA approach used for this meta-model was Multi- Attribute Value Theory (MAVT). The model was implemented, using the software HiView 3, with three clinicians from hospital H3 for the choice between Expert Choice and ALEL as the basis of a lung cancer clinical management PDA. RESULTS: The thesis makes a three-fold contribution to research in patient-centred decision support. First, it presents two new MCDA software-based approaches to clinical decision support, based on joint work with clinicians in the Spanish NHS, for developing an interactive PDA for the clinical management of non-small cell lung cancer. Second, it describes the use of these decision support tools in the delivery of 5 an interactive PDA for the clinical management of non-small cell lung cancer in a hospital environment via simulated consultations between actual clinicians, with support from this researcher, and proxy lung cancer patients. Third, it presents and applies a new MCDA-based methodology for evaluating the use of alternative MCDA software applications in the development and delivery of interactive PDAs.

Land valuation with Best Worst Method in land consolidation projects

<p>THEORETICAL FOUNDATIONS AND USE OF MULTI-CRITERIA DECISION ANALYSIS IN THE PHARMACEUTICAL SECTOR OF UKRAINE ACCORDING TO THE EUROPEAN REFORMING VECTOR</p><p>O.B. Piniazhko, O.M. Zaliska</p><p>Danylo Halytsky Lviv National Medical University</p><p> </p><p>The reforming of health care system has been started to carry out in Ukraine. Assessing the value of medical technologies may require new approaches that take into account a more comprehensive set of parameters than the incremental cost-effectiveness ratio, ICER/ quality adjusted life years, QALY.</p><p>Technological advancements in combination with higher life expectancy, higher patient expectations, and increased prevalence of chronic diseases, have led to significant increases in public spending on pharmaceuticals, which, on average account for 9,3% of total health expenditure or about 1,4% of GDP across OECD countries (OECD, 2012). Given the resources governments and health systems can spend on healthcare, the pathway to optimal resource allocation passes through cost containment and efficiency improvement policies. </p><p>In the context of multi-criteria decision analysis (MCDA), elements of value can be measured and scored in their natural units or through constructed scales, quantitatively or qualitatively, and weights are assigned to reflect criteria’s importance when combining them. This approach may provide a more comprehensive account of value parameters, greater transparency in how multiple criteria are explicitly valued, weighted, and aggregated, and a more inclusive approach to stakeholder views on value.</p><p>Our aim was to perform a comparative analysis of the main approaches, methods and stages of MCDA, to determine the urgent and relevant use of MCDA in health care system of Ukraine based on the experience of developed countries.</p><p>We have analyzed the ukrainian and foreign publications, articles, systematic reviews, practical guidelines on MCDA in health care using PubMed, EMBASE, Internet resources as search tools.</p><p>Decision analysis can provide an alternative way of measuring and eliciting value. In particular, MCDA is both an approach and a set of techniques, with the goal of providing an overall ordering of options by looking at the extent to which a set of objectives are achieved. MCDA methodologies have been suggested for use in public services since 1960. MCDA has been used, on an experimental basis, in order to assess the benefit-risk (clinical) profile of new medicines for the purpose of regulatory approval during marketing authorisation stage by the European Medicines Agency and others. Its use has also been suggested in health care and value assessment in HTA also offering a conceptual framework.</p><p>Although a variety of MCDA methodologies exist, the process of MCDA includes a number of common stages as follows: 1) establishing the decision context by defining the aims of the MDCA, and who the decision makers and other key stakeholders are; 2) identifying the objectives and criteria that reflect the value associated with the consequences of each option; 3) «scoring» the value associated with the performance of each option against the criteria; 4) «weighting» each of the criteria to reflect their relative importance to the decision; 5) examine the results; 6) conducting a sensitivity analysis of the results to test the influence of changes in scores or weights.</p><p>As the results of our review we suggested the urgent and relevant use of MCDA in health care system of Ukraine based on the experience of developed countries. The comparative analysis of the main approaches, methods and stages of MCDA was performed and trends of it’s implementation in the pharmaceutical industry of our country were suggested.</p><p>Due to the performed analysis, in our opinion in order to optimize and improve the decision-making process in health care the implementation of MCDA approach will provide transparent and consistent management decisions in Ukraine.</p>

Introduction:The use of multi-criteria decision analysis (MCDA) in health technology assessment (HTA) studies has become more common due to the fact that MCDA offers a comprehensive technique for decisions that involve multiple criteria and stakeholders. How MCDA contributes to the HTA decision making process is an issue to be investigated. A systematic review was carried out in order to provide an overview of the benefits identified in MCDA applications for the strategic HTA decision making process.Methods:A systematic review developed by Philip Wahlster et al. (2014) was updated. The papers were analyzed in order to determine how MCDA is connected with traditional HTA, and to identify opportunities through the application of MCDA. In total 965 papers were found, and 43 articles were included in the review. The included articles detailed MCDA applications oriented to tactical and strategic decision making processes. The review was conducted by two researchers.Results:Of the available studies published on MCDA, 76 percent were published between 2014 and 2017, and 24 percent were published prior to 2014. Regarding the MCDA methodology defined in the included studies, 10 used the analytical hierarchy process, four used multi-attribute theory, and others refer the methodology only as “MCDA”. Seventeen studies also included health technology economic analysis, in special cost-effectiveness, safety and technological innovation. The studies suggest MCDA adds value since it allows different stakeholders to be engaged in the decision making process.Conclusions:The increase in studies on MCDA and healthcare point to the possibility to add different criteria, engage people with different knowledge levels, and make the decision-making process more transparent. In comparison with other technical areas, the use of MCDA in healthcare is more focused on achieving the decision about adding the new technology, and to show how to engage stakeholders than to explain how to develop the algorithms and methodologies.

Background: There is a perception held by payers that orphan products are expensive. As a result, the current health technology assessment systems might be too restrictive for orphan drugs, therefore potentially denying patients access to life-saving medicines. While price is important, it should be considered in relation to a broader range of disease-related product attributes that are not necessarily considered by many health technology assessment agencies. To overcome these challenges, multi-criteria decision analysis has been proposed as an alternative to evaluate technologies. Methods: A targeted literature review was conducted to identify the most frequently cited attributes in multi-criteria decision analysis (MCDA) in rare diseases. From the leading attributes identified, we developed a multi-criteria decision analysis framework with which to aggregate the orphan drug values. We subsequently reviewed and plotted the relationship between single attributes and the average annual treatment costs for 8 drugs used in the treatment of rare endocrine diseases. The annual treatment costs were based on UK list prices for the average daily dose per patient. Results: The five most frequently mentioned attributes in the literature were as follows: Disease severity, Unmet need (or availability of therapeutic alternatives), Comparative effectiveness or efficacy, Quality of evidence and Safety & tolerability. Results from the multi-criteria decision analysis framework indicate a wide range of average annual per-patients costs for drugs intended for the same diseases, and likewise for diseases with a similar level of Disease severity. Conclusions: Multi-criteria decision analysis may offer a viable alternative to support discussion in reimbursement decisions for orphan drugs. The analyses can be used to inform investigations on the application of MCDAs in rare diseases.

To determine the effect of multi-criteria decision analysis (MCDA) on the effect of bundle treatment for severe pneumonia. A prospective historical control observation was conducted. Seventy-five patients with severe pneumonia having received MCDA (from January 2013 to August 2014) were assigned as intervention group. MCDA group was set up by the medical staff. Bundled treatment plan was composed of the MCDA evaluation results, anti-infection, phlegm and other conventional treatment measures which was adjust on time until the patient was transferred out of the respiratory intensive care unit (RICU) or died. Seventy patients with severe pneumonia before receiving MCDA (from August 2010 to December 2012) were set as historical control group. Comparison of general condition before treatment and the incidence of hospital infection, average hospitalization cost, duration of RICU stay and mortality between these two groups were performed. There were no statistically significant differences in gender, age, past history, and acute physiology and chronic health evaluation II (APACHE II) score at admission between two groups. Compared with control group, the incidence of hospital infection [1.33% (1/75) vs. 11.43% (8/70), χ2 = 4.723, P = 0.030], mean hospitalization cost in RICU (10 thousand Yuan: 3.44 ± 0.79 vs. 3.76 ± 0.91, t = 2.265, P = 0.025), length of RICU stay (days: 15.01 ± 4.22 vs. 16.92 ± 4.79, t = 2.552, P = 0.012) and mortality in RICU [8.0% (6/75) vs. 21.4% (15/70 ), χ2 = 5.272, P = 0.032] in intervention group was significantly decreased. Application of MCDA in the bundle treatment of severe pneumonia could elevate the scientificalness of decision, and reduce the medical cost. Additionally, MCDA is worth to be generalized because the implementation of guidelines can improve the clinical outcome and prognosis of the patients.

BackgroundIn recent years, the potential of multi-criteria decision analysis (MCDA) in the health field has been discussed widely. However, most MCDA methodologies have given little attention to the aggregation of different stakeholder individual perspectives.ObjectiveTo illustrate how a paraconsistent theory-based MCDA reusable framework, designed to aid hospital-based Health Technology Assessment (HTA), could be used to aggregate individual expert perspectives when valuing cancer treatments.MethodsAn MCDA methodological process was adopted based on paraconsistent theory and following ISPOR recommended steps in conducting an MCDA study. A proof-of-concept exercise focusing on identifying and assessing the global value of first-line treatments for metastatic colorectal cancer (mCRC) was conducted to foster the development of the MCDA framework.ResultsOn consultation with hospital-based HTA committee members, 11 perspectives were considered in an expert panel: medical oncology, oncologic surgery, radiotherapy, palliative care, pharmacist, health economist, epidemiologist, public health expert, health media expert, pharmaceutical industry, and patient advocate. The highest weights were assigned to the criteria “overall survival” (mean 0.22), “burden of disease” (mean 0.21) and “adverse events” (mean 0.20), and the lowest weights were given to “progression-free survival” and “cost of treatment” (mean 0.18 for both). FOLFIRI and mFlox scored the highest global value score of 0.75, followed by mFOLFOX6 with a global value score of 0.71. mIFL was ranked last with a global value score of 0.62. The paraconsistent analysis (para-analysis) of 6 first-line treatments for mCRC indicated that FOLFIRI and mFlox were the appropriate options for reimbursement in the context of this study.ConclusionThe Paraconsistent Value Framework is proposed as a step beyond the current MCDA practices, in order to improve means of dealing with individual expert perspectives in hospital-based HTA of cancer treatments.

Qualitative methods tend to be used to incorporate patient preferences into healthcare decision making. However, for patient preferences to be given adequate consideration by decision makers they need to be quantified. Multi-criteria decision analysis (MCDA) is one way to quantify and capture the patient voice. The objective of this review was to report on existing MCDAs involving patients to support the future use of MCDA to capture the patient voice. MEDLINE and EMBASE were searched in June 2014 for English-language papers with no date restriction. The following search terms were used: 'multi-criteria decision*', 'multiple criteria decision*', 'MCDA', 'benefit risk assessment*', 'risk benefit assessment*', 'multicriteri* decision*', 'MCDM', 'multi-criteri* decision*'. Abstracts were included if they reported the application of MCDA to assess healthcare interventions where patients were the source of weights. Abstracts were excluded if they did not apply MCDA, such as discussions of how MCDA could be used; or did not evaluate healthcare interventions, such as MCDAs to assess the level of health need in a locality. Data were extracted on weighting method, variation in patient and expert preferences, and discussion on different weighting techniques. The review identified ten English-language studies that reported an MCDA to assess healthcare interventions and involved patients as a source of weights. These studies reported 12 applications of MCDA. Different methods of preference elicitation were employed: direct weighting in workshops; discrete choice experiment surveys; and the analytical hierarchy process using both workshops and surveys. There was significant heterogeneity in patient responses and differences between patients, who put greater weight on disease characteristics and treatment convenience, and experts, who put more weight on efficacy. The studies highlighted cognitive challenges associated with some weighting methods, though patients' views on their ability to undertake weighting tasks was positive. This review identified several recent examples of MCDA used to elicit patient preferences, which support the feasibility of using MCDA to capture the patient voice. Challenges identified included, how best to reflect the heterogeneity of patient preferences in decision making and how to manage the cognitive burden associated with some MCDA tasks.

Context. The process of multi-criteria decision analysis for territorial planning and rational placement of spatial objects, based on modeling the properties of the territory, is considered. Objective. Development of technology for multi-criteria decision analysis for territorial planning based on the apparatus of the theory of fuzzy sets and functions of geoinformation analysis. Method. An object-spatial approach to the formation of a set of alternatives and criteria is proposed, according to which the process of multicriteria decision analysis is divided into two stages: macro- and microanalysis.The macroanalysis stage involves the assessment of the ecological and socio-economic properties of the territory using geomodeling functions. The paper provides a formalized description of the macroanalysis stage, including methods for assessing the qualitative and quantitative impact of spatial objects on the properties of the territory and decomposing objects into thematic layers of criteria. At the stage of microanalysis, the ranking of alternatives is performed taking into account the chosen decision-making strategy. The method of standardization of criteria attributes using fuzzy set membership functions and the modification of the method for calculating the coefficients of relative importance (weights) of criteria, taking into account the spatial heterogeneity of the preferences of the decision maker, are considered. A comparative analysis of the methods for aggregating the estimates of alternatives according to different criteria has been carried out. A feature of the presented technology of geospatial multi-criteria decision analysis of decisions for territorial planning is the possibility of its integration into modern geographic information systems. Results. The procedure of geospatial multi-criteria decision analysis was implemented in the environment of the geographic information system ESRI ArcGIS 10.5 and was studied in solving the spatial problem of rational location of an enterprise. Conclusions. The proposed object-spatial approach to multi-criteria decision analysis makes it possible to explicitly take into account the spatial heterogeneity of geographic data, which is the result of the influence of geographic objects on the properties of the territory. The developed technology can be used to solve a wide range of problems related to determining the most rational placement of various capital construction and infrastructure facilities.

BackgroundZoonoses are a growing international threat interacting at the human-animal-environment interface and call for transdisciplinary and multi-sectoral approaches in order to achieve effective disease management. The recent emergence of Lyme disease in Quebec, Canada is a good example of a complex health issue for which the public health sector must find protective interventions. Traditional preventive and control interventions can have important environmental, social and economic impacts and as a result, decision-making requires a systems approach capable of integrating these multiple aspects of interventions. This paper presents the results from a study of a multi-criteria decision analysis (MCDA) approach for the management of Lyme disease in Quebec, Canada. MCDA methods allow a comparison of interventions or alternatives based on multiple criteria.MethodsMCDA models were developed to assess various prevention and control decision criteria pertinent to a comprehensive management of Lyme disease: a first model was developed for surveillance interventions and a second was developed for control interventions. Multi-criteria analyses were conducted under two epidemiological scenarios: a disease emergence scenario and an epidemic scenario.ResultsIn general, we observed a good level of agreement between stakeholders. For the surveillance model, the three preferred interventions were: active surveillance of vectors by flagging or dragging, active surveillance of vectors by trapping of small rodents and passive surveillance of vectors of human origin. For the control interventions model, basic preventive communications, human vaccination and small scale landscaping were the three preferred interventions. Scenarios were found to only have a small effect on the group ranking of interventions in the control model.ConclusionsMCDA was used to structure key decision criteria and capture the complexity of Lyme disease management. This facilitated the identification of gaps in the scientific literature and enabled a clear identification of complementary interventions that could be used to improve the relevance and acceptability of proposed prevention and control strategy. Overall, MCDA presents itself as an interesting systematic approach for public health planning and zoonoses management with a “One Health” perspective.

PurposeThe purpose of this paper is to present a framework for evaluation and ranking of potential surrogates to select the optimum surrogates and test it for five selected social resilience indicators in a disaster context. Innovative resilience assessment approaches are required to capture key facets of resilience indicators to deepen the understanding of social resilience. Surrogates can adequately represent the target indicator that is difficult to measure, as surrogates are defined as key facets of a target indicator.Design/methodology/approachTo optimize the selection of surrogates, five key evaluation criteria were used. Disaster management experts completed an online survey questionnaire and evaluated three potential surrogate options. Surrogates were then ranked using PROMETHEE, a multi-experts multi-criteria group decision analysis technique.FindingsA framework was devised to evaluate and rank potential surrogates to assess social resilience in a disaster context. The findings revealed that the first ranked surrogate can be the most critical facet of a resilience indicator of measure. In most instances, highly experienced cohort of practitioners and policy makers have aligned their preferences of surrogates with the overall ranking of surrogates obtained in this study.Research limitations/implicationsThe surrogate approach can also be tested in different disaster and geographic contexts. The resilience indicators used in this study to explore surrogates are largely applicable in all contexts. However, the preference of surrogates may also vary in different contexts.Practical implicationsOnce the surrogate is selected through an evaluation process proposed in this paper, the resilience status can be updated regularly with the help of the selected surrogate. The first ranked surrogate for each of the social resilience indicator can be applied, since the findings revealed that the first ranked surrogate can be the most critical facet in the context of the social resilience indicator being measured.Social implicationsThe framework and the selection of optimal surrogates will assist to overcome the conceptual and methodical challenges of social resilience assessment. The applicability of selected surrogates by practitioners and policymakers in disaster management will play a vital role in resilience investment decision-making at the community level.Originality/valueThe surrogate approach has been used in the fields of ecology and clinical medicine to overcome the challenges in measuring difficult to measure indicators. The use of surrogates in this study to measure social resilience indicators in a disaster context is innovative, which was not yet explored in resilience measurement in disaster management.Graphical abstract

Abstract. Climate change is projected to increase flood risks in western Africa. In the FANFAR project, a pre-operational flood early warning system (FEWS) for western Africa was co-designed in workshops with 50–60 stakeholders from 17 countries, adopting multi-criteria decision analysis (MCDA). We aimed at (i) designing a FEWS with western African stakeholders using MCDA and (ii) evaluating participatory MCDA as a transdisciplinary process. To achieve the first aim (i), we used MCDA methods for problem structuring and preference elicitation in workshops. Problem structuring included stakeholder analysis, creating 10 objectives to be achieved by the FANFAR FEWS and designing 11 possible FEWS configurations. Experts predicted FEWS configuration performance, which we integrated with stakeholder preferences. We tested MCDA results in sensitivity analyses. Three FEWSs showed good performance, despite uncertainty, and were robust across different preferences. For stakeholders it was most important that the FEWS produces accurate, clear, timely, and accessible flood risk information. To achieve the second aim (ii), we clustered common characteristics of collaborative governance frameworks from the sustainability science and transdisciplinary literature. Our framework emphasizes issues crucial to the earth systems sciences, such as uncertainty and integrating interdisciplinary knowledge. MCDA can address both well. Other strengths of MCDA are co-producing knowledge with stakeholders and providing a consistent methodology with unambiguous, shared results. Participatory MCDA including problem structuring can contribute to co-designing a project but does not achieve later phases of transdisciplinary processes well, such as co-disseminating and evaluating results. We encourage colleagues to use MCDA and the proposed framework for evaluating transdisciplinary hydrology research that engages with stakeholders and society.

Participative multi-criteria decision analysis in marine management and conservation: Research progress and the challenge of integrating value judgments and uncertainty

Design thinking (DT) has attracted much attention in management practice as a novel problem-solving methodology. It supports and encourages collaborative creativity to solve problems in a holistically and user-centred way. Although there are similarities between DT and multi-criteria decision analysis (MCDA), such as the process orientation and stakeholder participation, there are also differences. Whereas DT mainly focuses on the innovative creation of a prototype, MCDA concentrates instead on the ranking of alternatives. In this paper, we analyse the similarities and differences of DT and MCDA. Based on this analysis, we then develop an approach to integrate elements from DT into MCDA. The stepwise procedure of the adjusted decision process from MCDA is presented in detail. Here, the approach of rapid prototyping from DT is of particular interest. Finally, we discuss the opportunities and challenges of combining multi-criteria decision analysis and design thinking. [Received 8 July 2017; Revised 23 January 2018; Revised 18 April 2018; Accepted 6 May 2018]