A new integrated tool for complex decision making: Application to the UK energy sector

One means of anticipating and, thus, preventing natural resource problems, such as those that may arise from plant introductions, is to use effective decision frameworks. This paper argues that such frameworks are typified by 4 elements. These are clear goals explicitly linked to cultural values, key questions that scope problems and management options, application of appropriate analytical tools, and the connection of authority for decisions with responsibility for outcomes. These elements are explored here. Trade offs are an inevitable part of decisions concerning natural resource management, including those relating to plant introductions. Benefit-cost and multi-criteria decision analyses are useful in this regard, but must be applied using methods that ensure all the relevant cultural values and management options are explored. Some recent proposals concerning the assessment of plant introductions do not always adequately frame decision issues. Ecological risk assessments can be used to define an acceptable level of risk concerning the negative impacts of introducing new biota, and, combined with an appropriate benefit-cost or multi-criteria analysis, provide the suite of analytical tools to make effective decisions concerning plant introductions. Effective decisions are more likely when the authority to make decisions and the responsibility for unforeseen outcomes are closely linked.

Who gets to fish for sea bass? Using social, economic, and environmental criteria to determine access to the English sea bass fishery

Governance of responsible research and innovation: A social welfare, psychologically grounded multicriteria decision analysis approach

Background: Multi-criteria decision analysis (MCDA) is a decision-making tool that can take into account multidimensional factors and enables comparison of (medical) technologies by combining individual criteria into one overall appraisal. The MCDA approach has slowly gained traction within Health Technology Assessment (HTA) and its elements are gradually being incorporated into HTA across Europe. Several groups of scientists have proposed MCDA approaches targeted toward orphan drugs and rare diseases by including criteria specific to rare diseases. The goal of this article is to provide an overview of the current state of knowledge and latest developments in the field of MCDA in HTA for orphan drugs, to review existing models, their design characteristics, as well as to identify opportunities for further model improvement.Methods: A systematic literature search was conducted in January 2018 using four databases: MEDLINE (Pubmed), EBSCO HOST, EMBASE, and Web of science to find publications related to use of MCDA in the rare disease field (keywords: MCDA/orphan drug/rare disease and synonyms). Identified MCDA models were analyzed, e.g., structure, criteria, scoring, and weighting methodology.Results: Two hundred and eleven publications were identified, of which 29 were included after removal of duplicates. 9 authors developed own MCDA models, 7 of which based on literature reviews intended to identify the most important and relevant decision criteria in the model. In 13 publications (8 models) weights were assigned to criteria based on stakeholder input. The most commonly chosen criteria for creation of the MCDA models were: comparative effectiveness/efficacy, the need for intervention, and disease severity. Some models have overlapping criteria, especially in the treatment cost and effectiveness areas.Conclusions: A range of MCDA models for HTA have been developed, each with a slightly different approach, focus, and complexity, including several that specifically target rare diseases and orphan drug appraisal. Models have slowly progressed over the years based on pilots, stakeholder input, sharing experiences and scientific publications. However, full consensus on model structure, criteria selection and weighting is still lacking. A simplification of the MCDA model approach may increase its acceptance. A multi-stakeholder discussion on fundamental design and implementation strategies for MCDA models would be beneficial to this end.

Decision-making tools have become a prominent methodology in watershed management for many years due to the complexity of environmental systems and requirement for multi-disciplinary expertise. Multi-Criteria Decision Analysis (MCDA) is a systematic methodology, which combines hierarchical structures of a problem and priorities for the alternatives in many fields. This study reviews MCDA applications in pollution risk assessment in the abiotic environments of watersheds for multi-pollutants. Over 80 papers published between 2000 and 2021 are identified in three categories of the Web of Science Core Collection database: “Environmental Sciences”, “Environmental Studies”, and “Water Resources”. The publications are further classified according to different environmental compartments: surface water, groundwater, and soil to investigate MCDA applications in these matrices. Finally, the distribution of the publications according to contaminants and MCDA methods used are also examined. The results reveal that the number of the studies focusing on pollution risk assessment within watersheds has been significantly increasing, especially over the last decade. However, there are still limited MCDA applications linking environmental compartments. Despite several MCDA studies focusing on the vulnerability of watersheds to multiple pollutants, studies related with emerging pollutants are scarce. Moreover, compared to non-point source pollution, studies adopting MCDA to investigate pollutant concentrations coming from point sources are relatively few. According to the overall distributions of MCDA methods, Analytic Hierarchy Process, a commonly found method in the literature that adopts a technique of pairwise comparison to prioritize criteria of prominence, dominates 34% of the publications.

The Tri-State Mining District was formed to encompass areas of Oklahoma, Kansas, and Missouri where lead, zinc, and other metals were mined from the 1900s until the 1960s. Tar Creek in Ottowa County, Oklahoma was the recipient of much of the mining waste generated during this period. The Tar Creek watershed is an approximately 53.3-square-mile area, where 19,566 people reside. It is characterized by high heavy metal soil concentrations, contaminated surface and ground waters, air transport of contaminants, and exposed mining wastes. There are human health and ecological exposure hazards from these media. A need for evaluations of long-term solutions that could be constructed or implemented to improve the ecosystems is apparent. There has been a movement toward a more ‘holistic’ response to human health and wildlife risks at and adjacent to Tar Creek, including determining problems affecting residents and identifying appropriate remedial actions. In 1983, the area along Tar Creek was listed on the National Priority List (NPL) as a Superfund Site. The Environmental Protection Agency signed a Memorandum of Understanding with United States Army Corps of Engineers and the Department of Interior in 2003 to collaborate on assessment and remediation efforts with multiple stakeholders, which include tribal authorities, local interest parties, and other entities. Multi-Criteria Decision Analysis (MCDA) is a systematic and structured process beneficial to users during the pre- and postphase of decision making. MCDA could prove an asset to the Tar Creek project, particularly when dealing with multiple stakeholders coupled with numerous remediation objectives and risk remedies, by applying decision processes such as Analytical Hierarchy Process (AHP) and Multi-Attribute Utility Theory (MAUT). Commercial software packages use decision processes as engines; for example, Expert Choice® utilizes AHP while Criterium DecisionPlus® exercises MAUT. MCDA, paired with decision-making tools, provides the results of modeling/-monitoring studies, risk analysis, cost, and stakeholder preferences so that risk managers are able to systematically evaluate and compare alternatives and actions supporting risk management and thus credibly prioritize resources. The following sections will discuss the background and history of the Tar Creek Superfund Site, the MCDA framework/structure, commonly used MCDA tools in conjunction with theories, and a methodology for how MCDA can be effectively used at the site.

This chapter addresses three policy issues related to the application of multi-criteria decision analysis (MCDA) for priority setting of health interventions in low- and middle-income countries (LMICs), namely, stakeholder involvement, institutionalization, and the impact of MCDA on policy decisions. Based on a literature review, we evaluate 11 case studies in the light of these issues. We found that there is no systematic approach for the involvement of stakeholders. Only four case studies implemented MCDA in an institutional context, and three studies evaluated the impact of MCDA on policy decisions. A detailed case study that explicitly integrated MCDA in the policy-making process for HIV/AIDS control in Indonesia is presented, and enablers and barriers of such an approach with regard to the three policy issues are outlined. The final part of the chapter provides recommendations of the future application of MCDA in policy processes. It provides methodological guidance on which stakeholders to involved and why. Recommendations are given on the institutionalization of MCDA and to improve the evaluation of the impact of MCDA on policy decisions.

Semantic interoperability of GIS and MCDA tools for environmental assessment and decision making

In this study, we develop a web-based Decision-Making Tool (DMT) based on a four-year research project in building the proper multiple criteria Decision-Making Framework (DMF) for infrastructure project selection automation. Several challenges in selecting and prioritizing infrastructure projects include poor front-end planning, lack of project funding, improper investment, unsustainable development, regulatory barriers, and poor coordination among stakeholders. The Non-Structural Fuzzy Decision Support System II (NSFDSS-II) is chosen as the main method applied in the proposed DMF since it could resolve complex multi-criteria problems, even without sufficient information provided. When developing the DMT, Agile software development method is used since the development cycle can be run in a light and fast manner with iterative and incremental processes. The DMT is successfully developed by using PHP, HTML, and JavaScript which implement the proposed NSFDSS-II method. We further tested the decision results from the DMT by using eight real past infrastructure projects from relevant infrastructure agencies in Indonesia, such as the Ministry of Public Works and Housing (MPWH), the Ministry of Transportation, and the Local Government. The DMT outcomes were compared with the actual implementation status and evaluated by an independent expert. It was found that the decision results from the developed DMT are in accordance with the real implementation status of evaluated projects. The DMT is recommended to be used for infrastructure project selection automation. However, despite of its fast and accurate result, the DMT should be tested on larger number of infrastructure projects in the future

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Introduction: Current evaluation approaches for new medical technologies are problematic for a plethora of reasons relating to measuring their expected costs and consequences, but also due to hurdles in turning assessed information into coverage decisions. Most adopted methodologies focus on a limited number of value dimensions, despite the fact that the value of new medicines is multi-dimensional in nature. Explicit elicitation of social value tradeoffs is not possible and decision-makers may adopt intuitive or heuristic modes for simplification purposes, based on ad hoc procedures that might lead to arbitrary decisions. Objectives: The objective of the present thesis is to develop and empirically test a methodological framework that can be used to assess the overall value of new medical technologies by explicitly capturing multiple aspects of value while allowing for their tradeoffs, through the incorporation of decision-makers’ preferences in a structured and transparent way. The research hypothesis is that Multiple Criteria Decision Analysis (MCDA) can provide a methodological option for the evaluation of new medicines in the context of Health Technology Assessment (HTA), to support decision-making and contribute to more efficient resource allocation. Methods and Empirical Evidence: The first paper proposes a conceptual methodological process, based on multi-attribute value theory (MAVT) methods comprising five distinct phases, outlining the stages involved in each phase and discusses their relevance in the HTA context. The second paper conducts a systematic literature review and expert consultation in order to investigate the practices, processes and policies of value-assessment for new medicines across eight European countries and identifies the evaluation criteria employed and how these inform coverage recommendations as part of HTA. The third paper develops a MAVT value framework for HTA, incorporating a generic value tree for new medicines composed from different levels of criteria that fall under five value domains (i.e. therapeutic, safety, burden of disease, innovation and socio-economic), together with a selection of scoring, weighting and aggregating techniques. In the fourth and fifth papers, the value framework is tested empirically by conducting two real-world case studies: in the first, the value tree is adapted for the evaluation of second-line biological treatments for metastatic colorectal cancer (mCRC) patients having received prior oxaliplatin-based chemotherapy; in the second, the value tree is conditioned for the evaluation of third-line treatments for metastatic castrate resistant prostate cancer (mCRPC) patients having received prior docetaxel chemotherapy. Both case studies were informed by decision conferences with relevant expert panels. In the mCRC decision conference multiple stakeholders participated reflecting the composition of the English National Institute for Health and Care Excellence (NICE) technology appraisal committees, whereas in the mCRPC decision conference a group of evaluators participated from the Swedish Dental and Pharmaceutical Benefits Agency (TLV), thereby adopting the TLV decision-making perspective. Policy Implications: The value scores produced from the MCDA process reflect a more comprehensive benefit metric that embeds the preferences of stakeholders and decisionsmakers across a number of explicit evaluation criteria. The incorporation of alternative treatments’ purchasing costs can then be used to derive incremental cost value ratios based on which the treatments can be ranked on ‘value-for-money’ grounds, reflecting their incremental cost relative to incremental value. Conclusion: The MCDA value framework developed can aid HTA decision-makers by allowing them to explicitly consider multiple criteria and their relative importance, enabling them to understand and incorporate their own preferences and value trade-offs in a constructed and transparent way. It can be turned into a flexible decision tool for resource allocation purposes in the coverage of new medicines by payers but could also be adapted for other decision-making contexts along their development, regulation and use.

This study aimed to look at the applicability of the multi-criteria decision analysis (MCDA) framework to improve hospital formulary drug decision-making. The case study method was used to investigate MCDA implementation in the National Brain Center Hospital Jakarta, Indonesia. A two stage-workshop was held on October 29th, 2019 and 5 February 5th, 2020, where participants conducted a hands-on experience in applying MCDA for selecting off-patent pharmaceuticals (OPPs) for the hospital formulary. The results of the workshop created awareness of MCDA that can be beneficial in transparently selecting OPP, which is not based only on price while involving multiple stakeholders. As a follow-up, MCDA was used during the drug selection process for the National Brain Center Hospital formulary in 2021 with criteria in accordance with the workshops, namely: 1) equivalence with the reference (originator) product; 2) real-world clinical or economic outcomes; 3) quality assurance; 4) reliability of drug supply; 5) stability and drug formulation; 6) pharmacovigilance, and 7) price advantages. In conclusion, the MCDA method can be implemented with customized criteria and weighting based on hospital needs to help with drug selection for the hospital formularies.

Multi-criteria decision analysis (MCDA), a decision-making tool, has received increasing attention in recent years, notably in the healthcare field. For Canada, it is unclear whether and how MCDA should be incorporated into the existing health technology assessment (HTA) decision-making process. To facilitate debate on improving HTA decision-making in Canada, a workshop was held in conjunction with the 8th World Congress on Health Economics of the International Health Economics Association in Toronto, Canada in July 2011. The objective of the workshop was to discuss the potential benefits and challenges related to the use of MCDA for HTA decision-making in Canada. This paper summarizes and discusses the recommendations of an expert panel convened at the workshop to discuss opportunities and concerns with reference to the implementation of MCDA in Canada.

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.

Knowledge sharing in Web-based collaborative multicriteria spatial decision analysis: An ontology-based multi-agent approach