Multi-criteria Decision Analysis Framework Research Articles

The application of multi-criteria decision analysis in evaluating the value of drug-oriented intervention: a literature review.

Objectives: Multi-Criteria Decision Analysis (MCDA) has gained increasing attention in supporting drug risk-benefit assessment, pricing and reimbursement, as well as optimization of clinical interventions. The objective of this study was to systematically collect and categorize evaluation criteria and techniques of weighting and scoring of MCDA for drug value assessment. Methods: A systematic review of the literature was conducted across seven databases to identify articles utilizing the MCDA frameworks for the evaluation of drug value. Evaluation criteria mentioned in the included studies were extracted and assigned to 5 dimensions including clinical, economic, innovative, societal and humanistic value. A descriptive statistical analysis was performed on the identified drug value evaluation criteria, as well as the weighting and scoring techniques employed. The more a criterion or technique were mentioned in articles, the more important we consider it. Results: Out of the 82 articles included, 111 unique criteria were identified to evaluate the value of drug. Among the 56 unique criteria (448 times) used to measure clinical value, the most frequently mentioned were "comparative safety/tolerability" (58 times), "comparative effectiveness/efficacy" (56 times), "comparative patient-perceived health/patient reported outcomes" (37 times), "disease severity" (34 times), and "unmet needs" (25 times). Regarding economic value measurement, out of the 20 unique criteria (124 times), the most frequently utilized criteria were "cost of intervention" (17 times), "comparative other medical costs" (16 times), and "comparative non-medical costs" (18 times). Out of the 10 criteria (18 times) for assessing innovative value, "a novel pharmacological mechanism" was the most frequently mentioned criterion (5 times). Among the 22 criteria (73 times) used to measure societal value, "system capacity and appropriate use of intervention" was the most frequently cited criterion (14 times). Out of the 3 criteria (15 times) utilized to measure humanistic value, "political/historical/cultural context" was the most frequently mentioned criterion (9 times). Furthermore, 11 scoring and 11 weighting techniques were found from various MCDA frameworks. "Swing weighting" and "a direct rating scale" were the most frequently used techniques in included articles. Conclusion: This study comprehensively presented the current evaluation dimensions, criteria, and techniques for scoring and weighting in drug-oriented MCDA articles. By highlighting the frequently cited evaluation criteria and techniques for scoring and weighting, this analysis will provide a foundation to reasonably select appropriate evaluation criteria and technique in constructing the MCDA framework that aligns with research objectives.

Value contribution of blood-based neurofilament light chain as a biomarker in multiple sclerosis using multi-criteria decision analysis.

Multiple sclerosis (MS) is a chronic autoimmune demyelinating disease that represents a leading cause of non-traumatic disability among young and middle-aged adults. MS is characterized by neurodegeneration caused by axonal injury. Current clinical and radiological markers often lack the sensitivity and specificity required to detect inflammatory activity and neurodegeneration, highlighting the need for better approaches. After neuronal injury, neurofilament light chains (NfL) are released into the cerebrospinal fluid, and eventually into blood. Thus, blood-based NfL could be used as a potential biomarker for inflammatory activity, neurodegeneration, and treatment response in MS. The objective of this study was to determine the value contribution of blood-based NfL as a biomarker in MS in Spain using the Multi-Criteria Decision Analysis (MCDA) methodology. A literature review was performed, and the results were synthesized in the evidence matrix following the criteria included in the MCDA framework. The study was conducted by a multidisciplinary group of six experts. Participants were trained in MCDA and scored the evidence matrix. Results were analyzed and discussed in a group meeting through reflective MCDA discussion methodology. MS was considered a severe condition as it is associated with significant disability. There are unmet needs in MS as a disease, but also in terms of biomarkers since no blood biomarker is available in clinical practice to determine disease activity, prognostic assessment, and response to treatment. The results of the present study suggest that quantification of blood-based NfL may represent a safe option to determine inflammation, neurodegeneration, and response to treatments in clinical practice, as well as to complement data to improve the sensitivity of the diagnosis. Participants considered that blood-based NfL could result in a lower use of expensive tests such as magnetic resonance imaging scans and could provide cost-savings by avoiding ineffective treatments. Lower indirect costs could also be expected due to a lower impact of disability consequences. Overall, blood-based NfL measurement is supported by high-quality evidence. Based on MCDA methodology and the experience of a multidisciplinary group of six stakeholders, blood-based NfL measurement might represent a high-value-option for the management of MS in Spain.

Multi-criteria decision analysis framework for engaging stakeholders in river pollution risk management

Water pollution presents a substantial environmental challenge with extensive implications for water resources, ecosystem sustainability, and human health. Using a South African catchment, this study aimed to provide watershed managers with a framework for selecting best management practices (BMPs) to reduce pollution and the related risk to river users, while also including the perspectives of key catchment stakeholders. The framework encompassed the identification of and consultation with key stakeholders within the catchment. A Multi-Criteria Decision Analysis (MCDA) methodology using the Simple Multi-Attribute Rating Technique for Enhanced Stakeholder Take-up (SMARTEST) was used to identify and prioritise suitable BMPs in a case study. Decision alternatives and assessment criteria as well as their weights were derived based on stakeholder responses to a two-stage survey. Stakeholders included those utilising the river for domestic and recreational purposes, municipal representatives, scientists, NGOs, and engineers. The assessment of decision alternatives considered environmental, economic, and social criteria. The aggregated scores for decision alternatives highlighted the significance of involving stakeholders throughout the decision process. This study recommends the pairing of structural and non-structural BMPs. The findings provide valuable insights for catchment managers, policymakers, and environmental stakeholders seeking inclusive and effective pollution mitigation strategies in a catchment.

A multi-criteria decision analysis framework that prioritizes economic policy to enhance value based health care during the COVID-19 pandemic

ObjectiveTo investigate pandemic impacts on Value-Based Health Care (VBHC) globally, using multi-criteria decision analysis (MCDA) to address challenges through prioritizing economic policies.MethodsPreferred Reporting Items for Systematic reviews and Meta Analyses extension for Scoping-Reviews (PRISMA-ScR), PUBMED, Medline, and google-scholar were used to analyze pandemic impacts on VBHC domains. MCDA prioritized economic policies, utilizing the value-measurement model with additive-weighted scores. The criteria weighting-method used direct-rating, ranking and robust deliberation by four experts to priority rank economic policies for each VBHC domain.ResultsCOVID-19 impacted on all VBHC domains: Integrated Practice Units, outcome and cost measurement, Value-Based Reimbursement, Information Technology (IT), regional systems integration, geography of care and VBHC policy and institutions. There were changes in patient complexity, service delivery, activity, models of care, pricing, costs, IT, quality, and health status. COVID-19 pricing impacts included increased capacity costs, Personal Protective Equipment costs, cost per patient, service delivery changes, and telehealth costs. A median of 37% of patients globally avoided care, negatively impacting on diabetes, venous thromboembolism, Parkinson’s disease, kidney disease, myocardial infarction, stroke, and cancer patients. A consequence is inaccurate assessments of health status, underestimated projected health needs, and costs for risk-adjustment, impacting health services. Innovations include telehealth and changing service redesign. New care models include state-wide ICU-COVID Models of Care, Telehealth-Inpatient Physician Services, COVID-linked pathology testing, and increased Hospital in the Home. Artificial Intelligence innovations involved patient-screening, triage, risk-evaluation, care assessment, pathways, and laboratories. Risk-adjustment challenges impacted on Value-Based Reimbursement and patient risk-stratification. MCDA prioritized economic policies, including healthcare system performance, healthcare demand and supply, risk-adjustment, planning and market mechanisms, economic evaluation of healthcare, economic sustainability initiatives, and health determinants.ConclusionCOVID-19 demonstrated the limits of health systems globally, with increasing costs and limited budgets. The economic strategies identified can enhance VBHC globally.

A Multi-Criteria Decision Analysis Framework for Evaluating Strategic Alternatives in Complex Business Markets

Considering all of the criteria involved in vendor evaluation makes it a difficult Multi-Criteria Decision-Making (MCDM) problem. In this case, they factor in DMs that are knowledgeable about the suppliers and their needs. Rating, a multi-criteria assessment method based on optimum scoring is proposed in this work. To meet the requirements of the decision-making process, this method employs rating-Based Optimal-Point Sorting (RBOP). A tried-and-true MCDM method can consistently find the option that will make the DM happy by first modeling the decision-making process after how humans really behave. Additionally, they create a new subjective scoring mechanism for the MCDM that is based on human behavior; they call it the win-loss-draw (WLD) method. They apply their methods to a case study that is based on actual Iranian cheese company operations in order to find the best possible cheese supplier for a hypermarket in Iran. The WLD approach had an effect on the RBOP strategy’s findings, which differ somewhat from the other MCDM methods. The WLD method increased spread and optimum regions throughout the choosing process.

Evaluation of antibody-based preventive alternatives for respiratory syncytial virus: a novel multi-criteria decision analysis framework and assessment of nirsevimab in Spain

BackgroundRespiratory syncytial virus (RSV) is a highly infectious disease that poses a significant clinical and medical burden, as well as social disruption and economic costs, recognized by the World Health Organization as a public health issue. After several failed attempts to find preventive candidates (compounds, products, including vaccines), new alternatives might be available, one being nirsevimab, the first and only option approved for RSV prevention in neonates and infants during their first RSV season. The objective of this study was to develop a novel multi-criteria decision analysis (MCDA) framework for RSV antibody-based preventive alternatives and to use it to assess the value of nirsevimab vs. placebo as a systematic immunization approach to prevent RSV in neonates and infants during their first RSV season in Spain.MethodsBased on a pre-established model called Vaccinex, an ad-hoc MCDA framework was created to reflect relevant attributes for the assessment of current and future antibody-based preventive measures for RSV. The estimated value of nirsevimab was obtained by means of an additive linear model combining weights and scores assigned by a multidisciplinary committee of 9 experts. A retest and three sensitivity analyses were conducted.ResultsNirsevimab was evaluated through a novel framework with 26 criteria by the committee as a measure that adds value (positive final estimated value: 0.56 ± 0.11) to the current RSV scenario in Spain, by providing a high efficacy for prevention of neonates and infants. In addition, its implementation might generate cost savings in hospitalizations and to the healthcare system and increase the level of public health awareness among the general population, while reducing health inequities.ConclusionsUnder a methodology with increasing use in the health field, nirsevimab has been evaluated as a measure which adds value for RSV prevention in neonates and infants during their first RSV season in Spain.

An integration of hybrid MCDA framework to the statistical analysis of computer-based health monitoring applications.

The surge in computer-based health surveillance applications, leveraging technologies like big data analytics, artificial intelligence, and the Internet of Things, aims to provide personalized and streamlined medical services. These applications encompass diverse functionalities, from portable health trackers to remote patient monitoring systems, covering aspects such as heart rate tracking, task monitoring, glucose level checking, medication reminders, and sleep pattern assessment. Despite the anticipated benefits, concerns about performance, security, and alignment with healthcare professionals' needs arise with their widespread deployment. This study introduces a Hybrid Multi-Criteria Decision Analysis (MCDA) paradigm, combining the strengths of Additive Ratio Assessment (ARAS) and Analytic Hierarchy Process (AHP), to address the intricate nature of decision-making processes. The method involves selecting and structuring criteria hierarchically, providing a detailed evaluation of application efficacy. Professional stakeholders quantify the relative importance of each criterion through pairwise comparisons, generating criteria weights using AHP. The ARAS methodology then ranks applications based on their performance concerning the weighted criteria. This approach delivers a comprehensive assessment, considering factors like real-time capabilities, surgical services, and other crucial aspects. The research results provide valuable insights for healthcare practitioners, legislators, and technologists, aiding in deciding the adoption and integration of computer-based health monitoring applications, ultimately enhancing medical services and healthcare outcomes.

Analyzing MAUT, ELECTRE, and SMART Methods in Determining the Best Physics Learning Media Aid

This study, titled " Analyzing MAUT, ELECTRE, and SMART Methods in Determining the Best Physics Learning Media Aid", evaluates three decision analysis methods—Multi-Attribute Utility Theory (MAUT), Elimination Et Choix Traduisant la Realité (ELECTRE), and Simple Multi-Attribute Rating Technique (SMART). Focused on factors like usability, effectiveness, cost, and adaptability, it guides educators in choosing the best learning tools. Using a multi-criteria decision analysis framework, the research systematically assesses MAUT, ELECTRE, and SMART, emphasizing their strengths and limitations in physics education. Beyond immediate decision-making, it prompts discussions on technology integration, encouraging innovative approaches. Findings offer insights for future research at the intersections of technology, pedagogy, and decision science. In conclusion, the study illuminates decision analysis methods for optimal physics learning media tools. PhyWiz's consistent top-ranking performance highlights its potential for enhancing physics education. The research recommends PhyWiz integration, emphasizing regular evaluation and adoption of innovative tools to improve physics education quality. It provides a practical guide for educators, contributing to continuous enhancements in teaching and learning experiences

GIS-driven Hydro Energy Potential Estimation for Technoeconomic Assessment of Hydro Power Plant in Bawean, Gresik

This study aims to assess the spatial distribution of hydropower capacity on Bawean Island using a Geographic Information System (GIS). The objective of this study is to provide a valuable contribution to the progress of sustainable energy transition initiatives in Indonesia. The primary objective of the hydropower map is to enhance the process of strategic planning and implementation of hydropower infrastructure, with a particular emphasis on supplying electricity to rural regions. The essential components required for the successful implementation of hydropower are the head, which represents the vertical distance between the water source and the water outflow, which refers to the rate at which water is discharged from the system. Bawean Island, located in the eastern region of Java, possesses a unique topographical structure distinguished by an abundance of rivers, making it a promising site for the establishment of hydropower infrastructure. The utilization of ArcGIS was applied for the aim of hydropower mapping. The estimation of water discharge was conducted using the Soil Conservation Service-Curve Number (SCS-CN) approach. The current investigation utilized the Multi-Criteria Decision Analysis (MCDA) framework, which incorporated the Analytical Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) to ascertain the most advantageous choice of hydropower plant types for deployment in the Bawean region. The classifications comprise pico-hydro, micro-hydro, mini-hydro, and large-scale hydropower installations.The Multi-Criteria Decision Analysis (MCDA) framework incorporates various criteria, including cost, policy, social concerns, technology assistance, integration, and natural catastrophe considerations. The results indicate that the hydropower potential on Bawean Island peaks in January, coinciding with the rainy season, while it is at its lowest in August, corresponding to the dry season. Moreover, the spectrum of hydropower installations suitable for Bawean Island includes pico-hydro systems, which have a power generation capacity of up to 5 kW. Additionally, mini-hydro plants are categorized into two classes: class A, with a power generation capacity ranging from 5 to 100 kW, and class B, with a power generation capacity ranging from 100 to 200 kW. The utilization of Multi-criterion Decision Analysis (MCDA) reveals the results of the techno-economic assessment, emphasizing the importance of cost, social factors, and policy as the key criterion for decision-making. The factors mentioned above are allocated weights of 0.44, 0.17, and 0.17, correspondingly. Pico-hydro is a suggested category of hydropower plants that are being considered for the development of hydropower infrastructure in the Bawean region.

Improving hospital formulary drug decision making with multi-criteria decision analysis (MCDA): case study from a national government hospital in Indonesia

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.

A multi-criteria decision model to support sustainable building energy management system with intelligent automation

With rising energy consumption in buildings, optimizing energy management is crucial for sustainability. This research pioneers the application of multi-criteria decision making (MCDM) techniques for real-time operational optimization of energy systems in buildings. A multicriteria decision analysis framework is used in this study to provide a model for decision making of generation and load balance. To assess the selection criteria, a thorough investigation is undertaken. The decision-based sustainable framework across conflicting criteria (encapsulating equal and objective weights) and aims towards the suitable trade-off solution. The framework is applied on workshop building across load-generation balance and is benchmarked with hardware. The research endeavor relies heavily on the deployment of sensor systems to prevent power wastage. By incorporating sensor systems, solar power usage control becomes smarter and more adaptable, enabling real-time modifications according to environmental conditions and energy requirements. This maximizes the overall efficiency and effectiveness of solar energy systems. Furthermore, the integration of sensor systems in solar power usage control improves reliability and maintenance through the identification and alerting of potential problems. TOPSIS and MCE are two methodologies that can be used in the field of multi-criteria decision model (MCDM). The originality of this study lies in the development of a MCDM framework to assist consumers in identifying resilient and optimal combinations of energy efficiency, cost-saving, and Indoor Environmental Quality (IEQ) improvement strategies for buildings in Pakistan.

Norwegian offshore wind power—Spatial planning using multi‐criteria decision analysis

AbstractThe Norwegian government recently agreed on the goal 30by40, which involves opening Norwegian offshore areas to host 30 GW of installed wind power by 2040. We address this goal by presenting a first mapping of wind power suitability scores (WPSS) for the entire Norwegian economic zone (NEZ) using a multi‐criteria decision analysis framework (MCDA), namely, the analytical hierarchical process (AHP) approach. We obtain WPSS considering relevant criteria like wind resources, techno‐economic aspects, social acceptance, environmental considerations, and met‐ocean constraints such as wind and wave conditions. The results starts with a baseline scenario, where the criterion importance is pairwise compared in the context of balancing economic incentives and conflicting interests. Additionally, to reveal regions that are robust to changes in criterion importance, we carry out a sensitivity analysis by introducing three additional scenarios. These scenarios represent stereotypical actors with distinct preferences for siting of wind farms: the investor, the environmentalist, and the fisherman. The results show that the southern part of the NEZ is the most suitable and robust region for offshore wind power deployment. This region receives the highest suitability category (“very high” suitability for wind power application) throughout all the scenarios. Areas in the Norwegian part of the Barents Sea and the near‐coastal areas outside mid‐Norway are also well suited regions, but these are more sensitive to the choice of criterion importance. The use of AHP within the framework of MCDA is shown to be a promising tool for pinpointing the best Norwegian offshore areas for wind power application.

Exploring the Affordable Housing Solutions for the Resettlement Projects of Padma Bridge

The construction of Padma Bridge in Bangladesh has necessitated the resettlement of displaced residents, highlighting the need for affordable and sustainable housing solutions aligned with Sustainable Development Goals 9 (Industry, Innovation, and Infrastructure), 10 (Reduce inequality), and 11 (Sustainable Cities and Communities). This study aims to engage undergraduate architecture students in a design studio exercise to develop innovative housing models for resettlement projects, addressing displaced communities' social, economic, and environmental challenges. A multi-criteria decision analysis (MCDA) framework is introduced, integrating stakeholder data. In the design studio, students explore housing alternatives and concentrate on community-driven cooperative housing, assessing their effectiveness, feasibility, and sustainability using the MCDA framework. The exercise produces a range of housing solutions that balance affordability, sustainability, and community-centric design. Students demonstrate the potential of novel approaches to address the complex challenges displaced communities face and contribute to equitable development in Bangladesh. Engaging architecture students in developing affordable housing solutions provides valuable insights for policymakers and stakeholders in resettlement. The study emphasizes the need for holistic, participatory approaches and highlights the role of innovative, sustainable housing models in enhancing the quality of life for those affected by the Padma Bridge project, aligning with the SDGs.

A Multi-Criteria decision analysis framework to determine the optimal combination of energy efficiency and indoor air quality schemes for English school classrooms

A Multi-Criteria decision analysis framework to determine the optimal combination of energy efficiency and indoor air quality schemes for English school classrooms

Value contribution of cenobamate for the treatment of Focal-Onset Seizures (FOS) in patients with drug-resistant epilepsy (DRE) in Spain through reflective Multi-Criteria Decision Analysis (MCDA)

IntroductionEpilepsy is one of the most common neurological conditions worldwide. The main goal of its treatment is to achieve seizure freedom without intolerable adverse effects. However, despite the availability of many anti-seizure medications, including the latest options, called third-generation anti-seizure medications (ASMs), approximately 40% of people with epilepsy present drug-resistant epilepsy (DRE). Cenobamate is the first ASM approved in Spain for the adjunctive treatment of Focal-Onset Seizures (FOS) in adult patients with DRE. In a chronic disease with a portfolio of available ASMs, the decision to introduce a new therapeutic alternative must follow a holistic evaluation of value provided. Reflective Multi-Criteria Decision Analysis (MCDA) methodology allows to determine the value contribution of a treatment in a given indication considering all relevant criteria for healthcare decision-making in a transparent and systematic manner from the perspective of relevant stakeholders. PurposeThe aim of this study was to determine the relative value contribution of cenobamate in the treatment of FOS in patients with DRE compared with third-generation ASMs using reflective MCDA-based methodology. MethodsA systematic literature review (combining biomedical databases and grey literature sources) was performed to populate the Evidence and Value: Impact on DEcisionMaking (EVIDEM) MCDA framework adapted to determine what represents value in the management of FOS in patients with DRE in Spain. The study was conducted in two phases. The first took place in 2021 with a multi-stakeholder group of eight participants. The second phase was conducted in 2022 with a multi-stakeholder group of 32 participants. Participants were trained in MCDA methodology and scored four evidence matrices (cenobamate vs. brivaracetam, vs. perampanel, vs. lacosamide and vs. eslicarbazepine acetate). Results were analyzed and discussed in a group meeting through reflective MCDA discussion methodology. ResultsDRE is considered a very severe condition associated with many important unmet needs, mainly with regard to the lack of more effective treatments to achieve the ultimate goal of treatment. Compared to third-generation ASMs, cenobamate is perceived to have a better efficacy profile based on improvements in responder rate and seizure freedom. Regarding safety, it is considered to have a similar profile to alternatives and a positive quality-of-life profile. Cenobamate results in lower direct medical costs (excluding pharmacological) and indirect costs. Overall, cenobamate is regarded as providing a high therapeutic impact and supported by high-quality evidence. ConclusionsBased on reflective MCDA methodology and stakeholders’ experience in clinical management of epilepsy in Spain, cenobamate is perceived as a value-added option for the treatment of patients with DRE when compared with third-generation ASMs.

Integrating heat pumps into district heating systems: A multi-criteria decision analysis framework incorporating heat density and renewable energy mapping

The implementation of district heating (DH) projects necessitates a thorough and accurate evaluation and planning process. The availability of energy resources is often the key determinant in identifying the suitability of a specific location for district heating applications. Also, it is crucial to consider the other factors during the planning stage: the environment, economics, and technical parameters. This research aims to plan and implement a DH site selection model based on a geographic information system (GIS). This model employs Boolean and fuzzy toolboxes to analyze various layers, followed by the analytic hierarchy process (AHP) to identify the most appropriate locations for district heating in Gaziantep, Turkey. A mixed integer linear programming (MILP) approach is utilized to model proposed energy systems to achieve optimal operation and planning. The study's primary objective is to minimize the levelized cost of energy (LCOE), which encompasses initial costs, operations, maintenance, replacement expenses, and energy demand while also meeting the energy demand. A hybrid energy system that includes solar thermal/photovoltaic (ST, PV) energy, wind turbine (WT), and heat pump (HP) is considered, and its LCOE of optimal size is compared to other scenarios using HOMER simulation software. The results indicate that 270 km2 of the study area is suitable for DH implementation, with 83 km2 being highly suitable. Among the various scenarios, the hybrid energy system with a renewable energy penetration rate of approximately 78% achieves the best LCOE of 0.0442. The study concludes by providing a map of the potential for district heating and a discussion of the strengths and drawbacks of each scenario.

Correction: Hani et al. Sensitivity Analysis for Multi-Criteria Decision Analysis Framework for Site Selection of Aquifer Recharge with Reclaimed Water. Sustainability 2023, 15, 5399

Correction: Hani et al. Sensitivity Analysis for Multi-Criteria Decision Analysis Framework for Site Selection of Aquifer Recharge with Reclaimed Water. Sustainability 2023, 15, 5399

The New Zealand drug harms ranking study: A multi-criteria decision analysis.

The harms arising from psychoactive drug use are complex, and harm reduction strategies should be informed by a detailed understanding of the extent and nature of that harm. Drug harm is also context specific, and so any comprehensive assessment of drug harm should be relevant to the characteristics of the population in question. This study aimed to evaluate and rank drug harms within Aotearoa New Zealand using a multi-criteria decision analysis (MCDA) framework, and to separately consider harm within the total population, and among youth. Two facilitated workshops involved the separate ranking of harm for the total population, and then for youth aged 12-17, by two expert panels. In the total population workshop, 23 drugs were scored against 17 harm criteria, and those criteria were then evaluated using a swing weighting process. Scoring and weighting were subsequently updated during the youth-specific workshop. All results were recorded and analysed using specialised MCDA software. When considering overall harm, the MCDA modelling results indicated that alcohol, methamphetamine and synthetic cannabinoids were the most harmful to both the overall population and the youth, followed by tobacco in the total population. Alcohol remained the most harmful drug for the total population when separately considering harm to those who use it, and harm to others. The results provide detailed and context-specific insight into the harm associated with psychoactive drugs use within Aotearoa New Zealand. The findings also demonstrate the value of separately considering harm for different countries, and for different population subgroups.

HTA86 Establishing the Multi-Criteria Decision Analysis (MCDA) Framework to Assess the Value of Orphan Drugs in China: From the Perspective of Stakeholders and the Public

This study aims to establish the value evaluation framework based on multi-criteria decision analysis for orphan drugs in China from the perspectives of stakeholders and the public, so as to provide evidence for the decision-making of medical insurance access.

Development of a Choice-framework for Covid vaccines in India using a multi-criteria decision analysis approach.

Vaccines were crucial in controlling the Covid-19 pandemic. As more vaccines receive regulatory approval, stakeholders will be faced with several options and must make an appropriate choice for themselves. We proposed a multi-criteria decision analysis (MCDA) framework to guide decision-makers in comparing vaccines for the Indian context. We adhered to the ISPOR guidance for the MCDA process. Seven vaccine options were compared under ten criteria. Through three virtual workshops, we obtained opinions and weights from citizens, private-sector hospitals, and public health organisations. Available evidence was rescaled and incorporated into the performance matrix. The final score for each vaccine was calculated for the different groups. We performed different sensitivity analyses to assess the consistency of the rank list. The cost, efficacy and operational score of the vaccines had the highest weights among the stakeholders. From the six scenario groups, Janssen had the highest score in four. This was driven by the advantage of having a single dose of vaccination. In the probabilistic sensitivity analysis for the overall group, Covaxin, Janssen, and Sputnik were the first three options. The participants expressed that availability, WHO approvals and safety, among others, would be crucial when considering vaccines. The MCDA process has not been capitalised on in healthcare decision-making in India and LMICs. Considering the available data and stakeholder preference at the time of the study, Covaxin, Janssen, and Sputnik were preferred options. The choice framework with the dynamic performance matrix is a valuable tool that could be adapted to different population groups and extended based on increasing vaccine options and emerging evidence. *ISPOR - The Professional Society for Health Economics and Outcomes Research.