Multiple Criteria Decision Analysis Framework Research Articles

Design of a multiple criteria decision analysis framework for prioritizing high-impact health technologies in a regional health service.

This study aims to develop a framework for establishing priorities in the regional health service of Murcia, Spain, to facilitate the creation of a comprehensive multiple criteria decision analysis (MCDA) framework. This framework will aid in decision-making processes related to the assessment, reimbursement, and utilization of high-impact health technologies. Based on the results of a review of existing frameworks for MCDA of health technologies, a set of criteria was proposed to be used in the context of evaluating high-impact health technologies. Key stakeholders within regional healthcare services, including clinical leaders and management personnel, participated in a focus group (n=11) to discuss the proposed criteria and select the final fifteen. To elicit the weights of the criteria, two surveys were administered, one to a small sample of healthcare professionals (n=35) and another to a larger representative sample of the general population (n=494). The responses obtained from health professionals in the weighting procedure exhibited greater consistency compared to those provided by the general public. The criteria more highly weighted were "Need for intervention" and "Intervention outcomes." The weights finally assigned to each item in the multicriteria framework were derived as the equal-weighted sum of the mean weights from the two samples. A multi-attribute function capable of generating a composite measure (multicriteria) to assess the value of high-impact health interventions has been developed. Furthermore, it is recommended to pilot this procedure in a specific decision context to evaluate the efficacy, feasibility, usefulness, and reliability of the proposed tool.

Comparing Patient and Provider Priorities Around Amputation Level Outcomes Using Multiple Criteria Decision Analysis

Patients with chronic limb threatening ischemia may require a transmetatarsal amputation (TMA) or a transtibial amputation. When making an amputation-level decision, these patients face a tradeoff-a TMA preserves more limb and may provide better mobility but has a lower probability of primary wound healing and may therefore result in additional same or higher level amputation surgeries with an associated negative impact on function. Understanding differences in how patients and providers prioritize these tradeoffs and other outcomes may enhance shared decision-making. Compare patient priorities with provider perceptions of patient priorities using Multiple Criteria Decision Analysis (MCDA). The MCDA Analytic Hierarchy Process was chosen due to its low cognitive burden and ease of implementation. We included 5 criteria (outcomes): ability to walk, healing after amputation surgery, rehabilitation program intensity, limb length, and ease of use of prosthetic/orthotic device. A national sample of dysvascular lower-limb amputees and providers were recruited from the Veterans Health Administration with the MCDA administered online to providers and telephonically to patients. Twenty-six dysvascular amputees and 38 providers participated. Fifty percent of patients had undergone a TMA; 50%, a transtibial amputation. When compared to providers, patients placed higher value on TMA (72% vs. 63%). Patient versus provider priorities were ability to walk (47% vs. 42%), healing (18% vs. 28%), ease of prosthesis use (17% vs. 13%), limb length (11% vs. 13%), and then rehabilitation intensity (7% vs. 6%). Our sample may not generalize to other populations. Provider perceptions aligned with patient values on amputation level but varied around the importance of each outcome. These findings illuminate some differences between patients' values and provider perceptions of patient values, suggesting a role for shared decision-making. Embedding this MCDA framework into a future decision aid may facilitate these discussions.

Selection of appropriate on-site household sanitation options for rural communities of Zimbabwe – case of Mbire district, Zimbabwe

ABSTRACT Selecting an appropriate sanitation option involves multiple stakeholders with often conflicting objectives. A multiple criteria decision analysis (MCDA) framework was developed to inform decision makers on selecting appropriate sanitation options for rural communities. Criteria established from literature were evaluated and weighted on-line by stakeholders. A performance matrix was developed by assigning weights to criteria and scoring alternatives. Selection of alternatives was based on a composite appropriateness index from a rank using the simple multi-attribute ranking technique. The framework was evaluated by verification, validation and sensitivity analysis. Five alternatives were evaluated on 14 decision criteria. The first preferred alternative was the urine diverting dry toilet (72.54) then the Blair ventilated improved pit latrine (67.10). The framework was commented as reasonable and robust. A simple and transparent MCDA framework was developed considering local conditions in a participatory manner to select appropriate alternatives for rural sanitation where a single option is encouraged.

Optimal Design of District Metered Areas in a Water Distribution Network Using Coupled Self-Organizing Map and Community Structure Algorithm

Operation and management of a water distribution network (WDN) by district metered areas (DMAs) bring many benefits for water utilities, particularly regarding water loss control and pressure management. However, the optimal design of DMAs in a WDN is a challenging task. This paper proposes an approach for the optimal design of DMAs in the multiple-criteria decision analysis (MCDA) framework based on the outcome of a coupled model comprising a self-organizing map (SOM) and a community structure algorithm (CSA). First, the clustering principle of the SOM algorithm is applied to construct initial homologous clusters in terms of pressure and elevation. CSA is then coupled to refine the SOM-based initial clusters for the automated creation of multiscale and dynamic DMA layouts. Finally, the criteria for quantifying the performance of each DMA layout solution are assessed in the MCDA framework. Verifying the model on a hypothetical network and an actual WDN proved that it could efficiently create homologous and dynamic DMA layouts capable of adapting to water demand variability.

Development and Practical Application of a Multiple-Criteria Decision Analysis Framework on Respiratory Inhalers: Is It Always Useful in the MOH Malaysia Medicines Formulary Listing Context?

Objectives. The current health technology assessment used to evaluate respiratory inhalers is associated with limitations that have necessitated the development of an explicit formulary decision-making framework to ensure balance between the accessibility, value, and affordability of medicines. This study aimed to develop a multiple-criteria decision analysis (MCDA) framework, apply the framework to potential and currently listed respiratory inhalers in the Ministry of Health Medicines Formulary (MOHMF), and analyze the impacts of applying the outputs, from the perspective of listing and delisting medicines in the formulary. Methods. The overall methodology of the framework development adhered to the recommendations of the ISPOR MCDA Emerging Good Practices Task Force. The MCDA framework was developed using Microsoft Excel 2010 and involved all relevant stakeholders. The framework was then applied to 27 medicines, based on data gathered from the highest levels of available published evidence, pharmaceutical companies, and professional opinions. The performance scores were analyzed using the additive model. The end values were then deliberated by an expert committee. Results. A total of eight main criteria and seven subcriteria were determined by the stakeholders. The economic criterion was weighted at 30%. Among the noneconomic criteria, “patient suitability” was weighted the highest. Based on the MCDA outputs, the expert committee recommended one potential medicine (out of three; 33%) be added to the MOHMF and one existing medicine (out of 24; 4%) be removed/delisted from the MOHMF. The other existing medicines remained unchanged. Conclusions. Although this framework was useful for deciding to add new medicines to the formulary, it appears to be less functional and impactful for the removal/delisting existing medicines from the MOHMF. The generalizability of this conclusion to other formulations remains to be confirmed.

A Multiple Criteria Decision Analysis Framework for Dispersed Group Decision-Making Contexts

To support Group Decision-Making processes when participants are dispersed is a complex task. The biggest challenges are related to communication limitations that impede decision-makers to take advantage of the benefits associated with face-to-face Group Decision-Making processes. Several approaches that intend to aid dispersed groups attaining decisions have been applied to Group Decision Support Systems. However, strategies to support decision-makers in reasoning, understanding the reasons behind the different recommendations, and promoting the decision quality are very limited. In this work, we propose a Multiple Criteria Decision Analysis Framework that intends to overcome those limitations through a set of functionalities that can be used to support decision-makers attaining more informed, consistent, and satisfactory decisions. These functionalities are exposed through a microservice, which is part of a Consensus-Based Group Decision Support System and is used by autonomous software agents to support decision-makers according to their specific needs/interests. We concluded that the proposed framework greatly facilitates the definition of important procedures, allowing decision-makers to take advantage of deciding as a group and to understand the reasons behind the different recommendations and proposals.

PCN277 CATCH THE WIND EARLY: PRICE FORECASTING OF EARLY STAGE ONCOLOGY ASSETS IN US

Price and value forecasting is challenging for developmental products where only early efficacy data is available, with products often reaching pivotal clinical development stages without an estimate of likely price potential and, effectively, returns. This may result in missing the opportunity to optimise the asset’s evidence generation plan, price and launch sequence. To define the value and forecast the price potential of assets in development, we have selected a variety of different value attributes that drive decision-making within oncology to arrive at a value framework. A Multiple Criteria Decision Analysis (MCDA) framework was developed using 21 weighted criteria validated by previously published research on MCDA and value framework methodologies from ICER (Institute for Clinical and Economic Review) and ASCO for the evaluation of medicines. The MCDA was based on a scoring system on a scale of 0 to 5 depending on each criterion. The MCDA framework included two groups: the first (core) group includes attributes that measure clinical benefit, economic value and disease characteristics; the second (extended) group covers additional broader considerations such as public health interests and non-health benefits. A linear regression analysis was performed using monthly cost of treatment as the dependent variable and aggregate MCDA score as the independent variable for immune-oncology products launched in US. For 6 immuno-oncology products, a strong correlation between the MCDA scores and the average monthly cost of treatment was observed [R of 0.89 for core group and 0.93 for the extended group]. The correlation that statistically measures how close the data are to the fitted regression line (R2) was over 0.8 for both groups suggesting a high explanatory power of the developed value framework. The study provides a robust framework for estimating the value and price of assets within immuno-oncology indications to inform Pricing and Market Access strategy.

PHP12 - Value-Based Decisions for Off-Patent Pharmaceuticals in Developing Countries – A Pilot Study Using Multi-Criteria Decision Analysis for Tenders in Indonesia

Off-patent pharmaceuticals (OPPs) play a vital role in meeting public health objectives, especially in developing countries with high budgetary constraints. Despite a high need for minimizing acquisition cost, additional criteria matter and therefore, Multiple Criteria Decision Analysis (MCDA) can support prioritization. The objective of our work was to develop an approach which can be easily adapted and implemented by decision makers in developing countries in order to improve the evidence base, robustness and transparency of policy decisions related to OPPs. A spreadsheet was developed based on previously suggested decision criteria for OPPs (Brixner et al, ViHRI 2018). This is complemented by a policy workshop with representatives of multiple stakeholder to set local priorities and define requirements to be met by manufacturers of OPPs. A pilot workshop was conducted in Indonesia in order to test and improve the spreadsheet and workshop format. The format was implemented successfully to adapt the MCDA framework to the specific local decision requirements for OPP tenders. The key success factors are: (1) all important stakeholder groups were represented in the 2-day workshop (2) a local health-policy leader was the owner of the process (3) the international academic moderators guided the participants through the process but did not influence the local priority setting (4) realistic case studies helped to test and fine-tune the initial MCDA tool. The criteria selected for OPP tenders in Indonesia were acquisition cost (40% weight), manufacturing quality (18.8%), equivalence with the reference product (12.2%), product formulation and stability (12.2%), supply reliability (8.4%), real-world outcomes (4.2%) and pharmacovigilance (3.6%). A standardized interactive format can be implemented in developing countries to support decision makers in establishing value-driven off-patent pharmaceutical policies.

Guidance toward the implementation of multicriteria decision analysis framework in developing countries

ABSTRACTIntroduction: Multiple Criteria Decision Analysis (MCDA) is increasingly used in health care mainly because it moves decision-making from ad hoc to an evidence-based and comprehensive process. Developing countries with more restricted financial and human research capacities, however, should consider their own methods of MCDA development and implementation.Areas covered: An MCDA framework to improve procurement decisions of off-patent pharmaceuticals was developed for developing countries and adapted to Indonesia, Kazakhstan and Vietnam during three policy workshops. Based on the experience of these workshops and one joint workshop with international experts and decision makers from multiple developing countries, general recommendations were formulated on how to implement MCDA specifically in developing countries. We provide 17 practical MCDA implementation recommendations in four major areas, including (1) MCDA objectives; (2) technical considerations of MCDA tool; (3) development and customization of MCDA tool and (4) policy implementation of MCDA in decision-making.Expert commentary: These practical MCDA recommendations for developing countries contribute to feasible, transparent, stepwise, iterative and standardized decision-making in health care.

Community-engaged development of a GIS-based healthfulness index to shape health equity solutions

Addressing health disparities requires both community engagement and an understanding of the social determinants of health. Although elements of the built environment can influence behavior change in public health interventions, such determinants have not been explicitly teased out via participatory mapping. An opportunity exists to integrate community voice in the development of such metrics. To fill this gap and inform the deployment of public health interventions in the Flint (USA) Center for Health Equity Solutions (FCHES), we created a means of assessing spatially-varying community needs and assets in a geographic information system (GIS), what we refer to as a healthfulness index.We engaged community and academic partners in their expert opinions on features of Flint's built environment that may promote or inhibit healthy behaviors via a multiple-criteria decision analysis framework. Experts selected from and ranked 29 variables in 6 categories (including amenities, environment, greenspace, housing, infrastructure, and social issues) using the analytic hierarchy process. The resulting matrices of expert opinions were aggregated and appended as weights for each variable's corresponding map layer. When combined through map algebra, composite scores yield spatially-varying healthfulness indices which signal any neighborhood's relative health promoting qualities (along a 0–100 scale).Results varied substantially across Flint, with the middle belt scoring highest and older neighborhoods in the northeast and north center of the city scoring lowest. Scores were aggregated to 38 Flint neighborhoods; for each of two project-specific indices, these ranged from lows of 38.7 (Hilborn Park) and 41.8 (Columbia Heights) to highs of 52.9 (College Cultural) and 58.0 (University Ave Corridor). We hypothesize that—even when controlling for individual-level factors—we will measure better and more sustained behavior change among participants living in neighborhoods with high healthfulness scores. Future work will examine this hypothesis and determine the importance of such indices in other similar communities.

Analyzing determinants for promoting emerging technology through intermediaries by using a DANP-based MCDA framework

Multiple Criteria Decision Analysis (MCDA) has been widely considered a useful tool for evaluating decision making. Several derivatives of MCDA, including AHP, ANP, DANP, have been implemented in previous studies to construct real-world applications. However, literature combining a systematic introduction on methodological developments of MCDA with an empirical implementation in promoting technology through intermediaries is still rare. To fill in this gap, this paper begins with introducing the methodological development of MCDA to set out an analytical framework, namely DANP for the empirical analysis. Consequently, this paper applied DANP to analyze multiple determinants and five dimensions that we summarized from existing literature to find out the key determinants and the interdependent relationship for promoting the emerging sector through institutional intermediaries. While conducting empirical implementation, 33 experts from major intermediaries involved in promoting the biotechnology sector were visited. 7 out of 33 of these experts were further visited for interview to verify our analysis. Based on our MCDA analysis, we found that government policies and regulations are the most influential determinates while promoting emerging sectors through intermediaries. This paper contributes to the literature in several ways including highlighting methodological improvements of DANP, improving approaches on empirical data collection, and implementing an empirical MCDA analysis by applying an influential network relation map (INRM) to construct useful policy suggestions for real-world applications.

OP58 Testing Of A Multiple Criteria Decision Analysis Value Framework With Decision Makers Across Europe

INTRODUCTION:We test in practice a Multiple Criteria Decision Analysis (MCDA) framework for the value assessment of a set of therapeutic options for the indication of hormone relapsed metastatic prostate cancer (mPC) through a series of simulation exercises with the participation of decision makers from different Health Technology Assessment (HTA)/insurance agencies across Europe, including TLV (Sweden), AETSA (Andalusia-Spain), INAMI-RIZIV (Belgium) and AOTMiT (Poland). The drugs evaluated were abiraterone, cabazitaxel and enzalutamide.METHODS:Using a multi-attribute value theory framework, past research outcomes and literature findings, an mPC-specific value tree was constructed incorporating relevant concerns as criteria. By adopting the MACBETH approach the different drugs were scored against the criteria through the development of value functions, relative weights were assigned to the criteria using a swing weighting technique, scores and weights were combined using an additive aggregation technique, and sensitivity analysis of results was conducted. All stages were informed through the participation of a small group of experts from each HTA/insurance agency at a series of decision conferences taking place in each country.RESULTS:Value parameters considered spanned the dimensions of therapeutic impact, safety profile, innovation level and socioeconomic impact. Overall weighted preference value scores were produced reflecting the performance of the treatments against the criteria while considering their relative importance. Order of treatments’ rankings was identical across all agencies, with enzalutamide scoring highest and cabazitaxel lowest. Therapeutic impact criteria always produced the greatest relative weight. Hypothetical priority setting decisions were made based on “value-for-money” grounds through the use of “cost per unit of value” metrics by incorporating purchasing costs.CONCLUSIONS:The MCDA framework tested possesses a number of characteristics that could facilitate decision making, including the systematic and explicit incorporation of value trade-offs as part of model assessment and the transparency throughout all its stages. Therefore, it has the prospects to act as a practical evaluation tool for value assessment and communication during the HTA process.

Potential impact of the implementation of multiple-criteria decision analysis (MCDA) on the Polish pricing and reimbursement process of orphan drugs.

BackgroundThe objective of this study was to assess the potential impact of the implementation of multiple-criteria decision analysis (MCDA) on the Polish pricing and reimbursement (P&R) process with regard to orphan drugs.MethodsA four step approach was designed. Firstly, a systematic literature review was conducted to select the MCDA criteria. Secondly, a database of orphan drugs was established. Thirdly, health technology appraisals (HTA recommendations) were categorized and an MCDA appraisal was conducted. Finally, a comparison of HTA and MCDA outcomes was carried out. An MCDA outcome was considered positive if more than 50 % of the maximum number of points was reached (base case). In the sensitivity analysis, 25 % and 75 % thresholds were tested as well.ResultsOut of 2242 publications, 23 full-text articles were included. The final MCDA tool consisted of ten criteria. In total, 27 distinctive drug-indication pairs regarding 21 drugs were used for the study. Six negative and 21 positive HTA recommendations were issued. In the base case, there were 19 positive MCDA outcomes. Of the 27 cases, there were 12 disagreements between the HTA and MCDA outcomes, the majority of which related to positive HTA guidance for negative MCDA outcomes. All drug-indication pairs with negative HTA recommendations were appraised positively in the MCDA framework. Economic details were available for 12 cases, of which there were 9 positive MCDA outcomes. Amongst the 12 drug-indication pairs, two were negatively appraised in the HTA process, with positive MCDA guidance, and two were appraised in the opposite direction.ConclusionsAn MCDA approach may lead to different P&R outcomes compared to a standard HTA process. On the one hand, enrichment of the list of decision making criteria means further scrutiny of a given health technology and as such increases the odds of a negative P&R outcome. On the other hand, it may uncover additional values and as such increase the odds of positive P&R outcomes.Electronic supplementary materialThe online version of this article (doi:10.1186/s13023-016-0388-0) contains supplementary material, which is available to authorized users.

Applying Multiple Criteria Decision Analysis (MCDA) in the context of HTA: an experimental case study on metastatic colorectal cancer

Objectives Past research has indicated that Multiple Criteria Decision Analysis (MCDA) could be used as an alternative methodology for assessing the value of new medical technologies in the context of Health Technology Assessment (HTA). The objective of this study is to apply in practice an MCDA framework for the value assessment of a set of therapeutic options in metastatic colorectal cancer through a simulation exercise based on MCDA principles.

Multi-criteria logistics modeling for military humanitarian assistance and disaster relief aerial delivery operations

Given that it is not always feasible to reach an affected area via land or sea within the first week following a natural disaster, aerial delivery provides the primary means to rapidly supply the affected population. Further, it is often the case that high density delivery of humanitarian aid supplies are taken over by non-friendly groups within the affected population. By using direct airdrop systems to deliver large quantities of individually wrapped food and water items, dispersion among the affected disaster relief population will occur more quickly. In this paper, we proffer a multiple criteria decision analysis (MCDA) framework to optimize the military humanitarian assistance/disaster relief (HA/DR) aerial delivery supply chain network. The model uses stochastic, mixed-integer, weighted goal programming to optimize network design, logistics costs, staging locations, procurement amounts, and inventory levels. The MCDA framework enables decision-makers to explore the trade-offs between military HA/DR aerial delivery supply chain efficiency and responsiveness, while optimizing across a wide range of real-world, probabilistic scenarios to account for the inherent uncertainty in the location of global humanitarian disasters as well as the amount of demand to be met.

MCDA Framework for Fishing Rights Allocation in South Africa

The work discussed in this paper relates to the allocation of fishing rights within the Western Cape province of South Africa. Many of these fisheries are under threat through over-exploitation, and yet are a traditional source of livelihood in many communities. We describe a sequence of interventions during which principles and processes of multiple criteria decision analysis (MCDA) formed the framework for structuring the problems, for facilitating group consensus on the decision making process, and for designing a decision support template for use in future allocations. Interactions with community representatives and with the the national Department of Environmental Affairs and Tourism revealed a high degree of consistency in perceptions of the management goals that need to be taken into consideration. These goals could be structured and summarized in the form of an integrated value tree, which in turn formed the basis for a formalized decision support structure that could provide a transparent, coherent and auditable basis for the allocation of fishing rights in a fully goal-directed manner.

Nonlinear information aggregation via evidential reasoning in multiattribute decision analysis under uncertainty

In many decision situations, it is inevitable to deal with both quantitative and qualitative information under uncertainty. Evidence-based reasoning within a multiple criteria decision analysis framework provides an alternative way of handling such information systematically and consistently. In this paper, the evidential reasoning (ER) approach is introduced, which is based on a recursive ER algorithm that, in essence, constitutes a nonlinear information aggregation process. To facilitate the application of the ER approach and as an indispensable part of its development, the nonlinear features of the ER information aggregation process need to be thoroughly investigated and properly understood. This forms the theme of this paper where the nonlinear features are explored by examining typical reasoning patterns in aggregating harmonic, quasi-harmonic, and contradictory decision information. This analytical investigation provides insights into the recursive nature of the ER approach as well as valuable experience that could be useful to other researchers and practitioners interested in developing and applying operation research/artificial intelligence (OR/AI)-based approaches for decision analysis under uncertainty. The analytical study is complemented by the numerical studies of two application examples. The analysis of a quality assessment problem for motor engines is aimed to show the step-by-step process of implementing the ER approach and to illustrate its nonlinear features in a real-life decision situation. The study of a more complex assessment problem in ship design is intended to demonstrate the potential of the ER approach and its supporting software for dealing with general decision problems.