A prospective ecological risk assessment method based on exposure and ecological scenarios (ERA-EES) to determine soil ecological risks around metal mining areas

Soil heavy metal (HM) contamination around metal mining areas (MMAs) is a global concern that requires a cost-effective ecological risk assessment (ERA) method for preventive management. Traditional ERAs, comparing environmental HM concentrations with benchmarks, are labor- and cost-intensive in field investigations and chemical analyses, which challenge the management demands of numerous MMAs. In this study, a prospective ecological risk assessment method based on exposure and ecological scenario (ERA-EES) was developed to predict the eco-risk levels (low/medium/high) around MMAs prior to field sampling. Five exposure scenario indicators related to soil HM exposure and three ecological scenario indicators reflecting the soil bioreceptor response were selected and combined with the analytic hierarchy process and fuzzy comprehensive evaluation methods for ERA-EES development. Case application and performance evaluation with 67 MMAs in China demonstrated that the ERA-EES method had an overall effective and conservative performance when referring to potential ecological risk index (PERI) levels, with an accuracy of 0.87, kappa coefficient of 0.7, and low or medium eco-risk levels in PERI classified to high levels in ERA-EES. Overall, the selected scenario indicators could efficiently reflect the risk levels of soil HM pollution from mining activities. Besides, more regulatory efforts should be paid to the MMAs of nonferrous metals, underground and long-term mining and those located in southern China. This work provided a convenient and cost-effective prospective ERA method under the trend of ERA being tiered and refined, facilitating the risk management of various MMAs.

A comparative evaluation of child health care in China using multicriteria decision analysis methods

Child health is an important public health issue in China and the Chinese government always attached great importance to child health care. With the implementation of a series of medical and health reforms in China in recent decades, the status of child health improved year by year. Objectives This study aims to comprehensively evaluate if the measures implemented in the medical and health reforms effectively promoted the development of Chinese child health care in recent years and provide theoretical support for future decision-making on the policies of child health care in China. Methods A total of six indicators were selected from the China Health Statistics Yearbook. Based on the multi-criteria decision analysis (MCDA) algorithm, three different evaluation methods were applied in the study, which are the weighted technique for order preference by similarity to an ideal solution (TOPSIS) method, the weighted rank-sum ratio (RSR) method, and the fuzzy comprehensive evaluation (FCE). Each indicator's weight was calculated by the entropy weight methods objectively. The sensitivity analysis was conducted to validate the stability and accuracy of the rank results. Results The results indicated that the rank values of each year's child health care calculated by the different evaluation methods were not exactly the same, but the overall trend is consistent which is that child health care in China improved year by year from 2000 to 2020. The top 5 were ranked from 2016-2020 and the bottom 5 were ranked from 2000-2004. Conclusions The results indicated that the policies and measures implemented in the medical and health reforms, as well as improved sanitation conditions, availability of healthy food and water, etc., have jointly promoted the development of child health care in China in the past 20 years, providing a scientific theoretical basis for future policy-making to promote child health care.

Multi-hazard susceptibility model based on high spatial resolution data-a case study of Sali settlement (Dugi otok, Croatia)

The world has been facing an increase in various natural hazards. The coastal regions are recognized as one of the most vulnerable due to high population pressure and climate change intensity. Mediterranean countries have one of the most burnable ecosystems in the world, one of the most exposed to pluvial floods, and have the highest erosion rates within the EU. Therefore, the aim of this study was to develop the first multihazard susceptibility model in Croatia for the Sali settlement (island of Dugi otok). The creation of a multi-hazard susceptibility model (MHSM) combined the application of geospatial technology (GST) with a local perception survey. The methodology consisted of two main steps: (1) creating individual hazard susceptibility models (soil erosion, wildfires, pluvial floods), and (2) overall hazard susceptibility modeling. Multicriterial GIS analyses and the Analytical Hierarchy Process were used to create individual hazard models. Criteria used (32) to create models are derived from very-high-resolution (VHR) models. Two versions of MHSM are created: 1) all criteria with equal weighting coefficients and 2) weight coefficients determined based on public perception. According to MHSM 1, most of the research (58%) area is moderately susceptible to multiple hazards. Highly and very highly susceptible areas are 27% of the drainage basin and are mostly located near roads and houses. MHSM 2 reveals similar results to MHSM 1. The public perceives that the research area is the most susceptible to wildfires. The wildfire ignition risk is ranked as moderate (3.00) with a standard deviation of 1.16. Pluvial flood risk is ranked low (2.78), with a standard deviation of 1.15. The risk of soil is most inferior (2.24) with a standard deviation of 0.91. The the most significant difference between public perception and the GIS-MCDA model of hazard susceptibility is related to soil erosion. However, the accuracy of the soil erosion model was confirmed by ROC curves based on recent traces of soil erosion in the research area. The proposed methodological framework of multi-hazard susceptibility modeling can be applied, with minor modifications, to other Mediterranean countries.

Using MCDA to assist an Intermunicipal community develop a resilience strategy in face of the pandemic caused by the SARS-CoV-2

The topic of regional economic resilience has been the subject of intense debate in the academic and political fields over the past decade and gained a new sense of urgency because of the pandemic caused by the SARS-CoV-2 virus as territories faced relevant impacts on their economies and social structures. The economic downturn, the increase in unemployment, and the deterioration of social conditions lead policy makers to search for solutions to make their territories more resilient to this type of event. The current article discusses how multicriteria decision analysis (MCDA) was used to help a Portuguese Intermunicipal Community, formed by 16 councils, develop a strategy to make its territory more cohesive, competitive, sustainable, and resilient. In addition to discussing an innovative application of a MCDA technique, this article illustrates how, through a MCDA approach, it was possible to reach a consensus among several policymakers, despite each of them having their own political agendas.

Analysis of wastewater reuse options using a multicriteria decision tool for Phuket, Thailand

The act of balancing between water demand and water supply in Phuket Island is facing challenges, suggesting water reuse options in various activities on the island should be properly promoted considering the potential benefits in a variety of dimensions. This research presented options to reuse effluent water from wastewater treatment plants for Phuket Municipality in 3 main activity groups, namely, domestic reuse, agricultural reuse, and raw water for water treatment plants (WTP). Water demand, additional water treatment trains, and the length of the major water distribution pipeline for each water reuse option were designed, and its cost and expenses were calculated. Multi-criteria decision analysis (MCDA) was used by 1000Minds internet-based software to prioritize the suitability of each water reuse option based on a four-dimensional scorecard, including economic, social, health, and environmental aspects. The decision algorithm for the trade-off scenario based on the government's budget allocation was proposed to obtain weighing without subjective expert opinions. The results revealed that recycling effluent water as raw water for the existing WTP was the first priority, followed by agriculture reuse for planting coconut, Phuket's economic crops, and domestic reuse. There was a significant difference in the total scores of economic and health indicators between the first- and second-priority options because of the difference in the additional treatment system in which the first-priority option applied the microfiltration and reverse osmosis system, which could effectively eliminate viruses and chemical micropollutants. In addition, the first priority option required a much smaller piping system than other water reuse options because it relied on the existing plumbing system of WTP, lowering the investment cost, which was a very important indicator for decision-making.

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

BACKGROUND

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Uncovering COVID-19 infection determinants in Portugal: towards an evidence-based spatial susceptibility index to support epidemiological containment policies

BACKGROUND

COVID-19 caused the largest pandemic of the twenty-first century forcing the adoption of containment policies all over the world. Many studies on COVID-19 health determinants have been conducted, mainly using multivariate methods and geographic information systems (GIS), but few attempted to demonstrate how knowing social, economic, mobility, behavioural, and other spatial determinants and their effects can help to contain the disease. For example, in mainland Portugal, non-pharmacological interventions (NPI) were primarily dependent on epidemiological indicators and ignored the spatial variation of susceptibility to infection.

METHODS

We present a data-driven GIS-multicriteria analysis to derive a spatial-based susceptibility index to COVID-19 infection in Portugal. The cumulative incidence over 14 days was used in a stepwise multiple linear regression as the target variable along potential determinants at the municipal scale. To infer the existence of thresholds in the relationships between determinants and incidence the most relevant factors were examined using a bivariate Bayesian change point analysis. The susceptibility index was mapped based on these thresholds using a weighted linear combination.

RESULTS

Regression results support that COVID-19 spread in mainland Portugal had strong associations with factors related to socio-territorial specificities, namely sociodemographic, economic and mobility. Change point analysis revealed evidence of nonlinearity, and the susceptibility classes reflect spatial dependency. The spatial index of susceptibility to infection explains with accuracy previous and posterior infections. Assessing the NPI levels in relation to the susceptibility map points towards a disagreement between the severity of restrictions and the actual propensity for transmission, highlighting the need for more tailored interventions.

CONCLUSIONS

This article argues that NPI to contain COVID-19 spread should consider the spatial variation of the susceptibility to infection. The findings highlight the importance of customising interventions to specific geographical contexts due to the uneven distribution of COVID-19 infection determinants. The methodology has the potential for replication at other geographical scales and regions to better understand the role of health determinants in explaining spatiotemporal patterns of diseases and promoting evidence-based public health policies.

Using surface markers to describe the kinematics of the medial longitudinal arch

BACKGROUND

Static and dynamic assessment of the medial longitudinal arch (MLA) is an essential aspect for measuring foot function in both clinical and research fields. Despite this, most multi-segment foot models lack the ability to directly track the MLA. This study aimed to assess various methods of MLA assessment, through motion capture of surface markers on the foot during various activities.

METHODS

Thirty general population participants (mean age 20 years) without morphological alterations to their feet underwent gait analysis. Eight measures, each representing a unique definition of the MLA angle using either real only, or both real and floor-projected markers, were created. Participants performed tasks including standing, sitting, heel lift, Jack's test and walking, and had their Arch Height Index (AHI) measured using callipers. Multiple-criteria decision analysis (MCDA) with 10 criteria was utilised for selecting the optimal measure for dynamic and static MLA assessment.

RESULTS

In static tasks, the standing MLA angle was significantly greater in all measures but one when compared to sitting, Jack's test and heel lift. The MLA angle in Jack's test was significantly greater than in heel lift in all measures. Across the compared dynamic tasks, significant differences were noted in all measures except one for foot strike in comparison to 50% gait cycle. All MLA measures held significant inverse correlations with MLA measured from static and dynamic tasks. Based on MCDA criteria, a measure comprising the first metatarsal head, fifth metatarsal base, navicular and heel markers was deemed the best for MLA assessment.

SIGNIFICANCE

This study aligns with the current literature recommendations for the use of a navicular marker for characterising the MLA. It contrasts with previous recommendations and advocates against the use of projected markers in most situations.

Benefit-risk assessment of traditional Chinese medicine preparations of sinomenine using multicriteria decision analysis (MCDA) for patients with rheumatoid arthritis

OBJECTIVE

A multicriteria decision analysis (MCDA) model was used to evaluate the benefits and risks of traditional Chinese medicine preparations of sinomenine alone or in combination with conventional drugs in the treatment of rheumatoid arthritis (RA) and to provide a basis for the rational clinical application of sinomenine.

METHODS

A study search was performed using six major databases, and Review Manager 5.3 was used for data analysis. Then, an MCDA model evaluation system was established for the treatment of RA with sinomenine preparations, and the benefit values, risk values, and total benefit-risk values of sinomenine preparations alone or in combination with conventional drugs were calculated using Hiview 3.2 software. Finally, Monte Carlo simulations were performed using Crystal Ball embedded in Excel software to calculate the 95% confidence intervals (95% CI), and the probability of the differences between the 2 drug regimens was determined to optimize the evaluation results.

RESULTS

Forty-four randomized controlled trials (RCTs) were included. Quantitative assessment of the MCDA model showed that the sinomenine preparation alone offered less benefits than when combined with conventional drugs with a benefit difference of 20 (95% CI 3.06, 35.71). However, the risk of the combination was significantly lower with a risk difference of 13(95% CI -10.26, 27.52). The total value of the benefit-risk of sinomenine alone and in combination with conventional drugs was 46 and 53 at 60% and 40% of the benefit-risk ratio of the two dosing regimens, respectively, with a difference of 7 (95% CI -4.26, 22.12). The probability that the comprehensive score of the combined regimen is greater than that of sinomenine alone is 90.1%, and the evaluation was steady.

CONCLUSION

The benefit-risk of the combined application regimen of sinomenine is greater than that of sinomenine alone.

Assessing the impact of COVID-19 on the efficiency of Portuguese state-owned enterprise hospitals

This paper uses Value-Based Data Envelopment Analysis (VBDEA), to assess the impact of the COVID-19 pandemic on the efficiency of 37 state-owned enterprises (SOE) hospitals by employing data publicly available from the Portuguese Health Service database between January and November 2019 and 2020, respectively. Furthermore, a productivity index (specifically adjusted to the VBDEA approach) is also used that allows identifying which factors are behind the relative efficiency changes of these hospitals. The factors considered to perform the efficiency assessment of the Portuguese SOE hospitals include labour, capacity, and activity-related indicators. Out of the 37 SOE hospitals, 21 and 17 were efficient in 2019 and 2020, respectively. Irrespective of the value functions considered, the hospitals more often viewed as a reference for best practices were Santa Maria Maior, Tâmega e Sousa and Entre Douro e Vouga. Santa Maria Maior and Algarve were the only hospitals found to be robustly efficient for both years. Overall, the majority of SOE hospitals showed negative productivity (except for Évora and Santa Maria Maior) and all of them presented negative technological change, thus highlighting the massive impact that the COVID-19 outbreak has had on the performance of these hospitals. An additional conclusion is that inefficient hospitals substantially increased all their resources in 2020 as compared to inefficient hospitals in 2019, suggesting that the inefficiency of these hospitals was not due to the lack of resources. Finally, irrespective of the model employed, the hospitals located in the Portuguese northern region were more resilient to the COVID-19 crisis. All in all, to become more resilient (even for future COVID-19 outbreaks), hospitals should undertake changes that are advantageous irrespective of the obstacles they face and that are even beneficial during normal times. A culture of cooperation within and across hospitals should also be cultivated, which allows exchanging resources where they can be used more efficiently.

Treatment Preference for Alzheimer's Disease: A Multicriteria Decision Analysis with Caregivers, Neurologists, and Payors

INTRODUCTION

Alzheimer's disease (AD) is a chronic neurodegenerative disorder associated with a high burden of illness. New therapies under development include agents that target amyloid-beta (Aβ), a key component in AD pathogenesis. Understanding the decision-making process for new AD drugs would help determine if such therapies should be adopted by society. Multicriteria decision analysis (MCDA) was applied to three key stakeholder groups to assess treatment alternatives for AD based on a multitude of decision trade-offs covering main components of care.

METHODS

AD caregivers (n = 117), neurologists (n = 90), and payors (n = 90) from the USA received an online survey. The decision problem was broken down into four decision criterion and 12 subcriteria for two treatment scenarios: an Aβ-targeted therapy vs. the standard of care (SOC). Respondents were asked to indicate how much they preferred one option over another on a scale from 1 (equal preference) to 9 (high preference) based on each criterion and subcriterion. The decision criteria and subcriteria were weighted and presented as partial utility scores (pUS), with higher scores suggesting an increased preference for that decision-making component.

RESULTS

Caregivers and payors applied the highest value to need for intervention (mean pUS = 0.303 and 0.259) and clinical outcomes (mean pUS = 0.286 and 0.377). In contrast, neurologists placed the highest value on clinical outcomes and types of benefits (mean pUS = 0.436 and 0.248). When decision subcriteria were examined, efficacy (mean pUS = 0.115, 0.219, and 0.166) and the type of patient benefits (mean pUS = 0.135, 0.178, and 0.126) were among the most valued by caregivers, neurologists, and payors.

CONCLUSION

All groups placed the highest value on drug efficacy and types of benefit derived by patients. In contrast, cost implications were among the least important aspects in their decision-making.

Estimating solid waste generation and suitability analysis of landfill sites using regression, geospatial, and remote sensing techniques in Rangpur, Bangladesh

Municipal solid waste (MSW) management has been a growing problem in fast-developing cities. A considerable amount of solid waste is generated daily and disposed anywhere, which creates an unhealthy environment. This study aims to develop a model to determine household solid waste (HSW) generation using multiple linear regression and identify suitable landfill sites to ensure proper MSW disposal in Rangpur City, Bangladesh. Socioeconomic variables data like average monthly income, educational level, family size, age of family head, and average HSW generation per day were collected from 381 respondents through stratified random sampling with a 95% confidence level. Multi-criteria decision analysis (MCDA) was performed using variables like surface water, slope, road network, and land use through GIS and remote sensing to find suitable landfill sites. Results of the model show no multicollinearity as the variance inflation factor was estimated to be less than 2 for each independent variable. Furthermore, the model provides a moderate overall fit because of the coefficient of determination (R² = 0.661), which denotes the independent variables' predictive capability. The results also demonstrate that family size and education are the most critical variables in predicting waste generation because of the values of coefficients 122.39 and - 184.72, respectively. This study also illustrated suitable landfill sites through MCDA, which can be a useful resource for the city authority to ensure environmental sustainability by implementing effective strategies for proper MSW management.

Model to support intervention prioritization for the control of Aedes aegypti in Brazil: a multi-criteria approach

Background

Despite continuous strategic investments to mitigate the complexity involving arboviruses control, it is still necessary to further research methods and techniques to achieve in depth knowledge and shorter response times in the application of intervention activities. Consequently, the current work focused its efforts on the development of a multicriteria decision support model for the prioritization of prompt response activities for Aedes aegypti control, based on a case study in the city of Natal/RN.

Method

The research was carried out in three stages: a) preliminary; b) modelling and choice; and c) finalization; the second stage was made possible by the Flexible and Interactive Tradeoff (FITradeoff) method for ranking problematic. Furthermore, the research encompassed ten actors who were involved in the model construction, eight internal and two external to the Natal Zoonoses Control Center (ZCC-Natal) as well as the observation of four operating scenarios for arboviruses control, based on transmission levels; and, evaluation of eleven alternatives from six different criteria perspectives.

Results

Rankings of the interventions evaluated in each of the four control operation scenarios present in the city of Natal/RN were obtained, considering technical criteria guided by the Pan American Health Organization (PAHO).

Conclusions

As a result, it was developed a structured decision-making model that could help decision makers to minimize the effects and risks associated with the proliferation of the vector.

Proposal for a Tool for Assessing Access to Water in Rural Communities: a Case Study in the Brazilian Semi-arid

This paper proposes a Water Access Index (WAI). Using this tool, decision-makers can identify and prioritize areas that need state intervention to develop actions to guarantee rural population access to water. Thus, was carried out is a case study, rural communities in the semi-arid region of Brazil to validate the suggested method. The WAI is based on a combined method of multicriteria decision analysis (MCDA), Geographic Information System (GIS), cluster analysis (CA) using Ward's agglomeration method and participation of rural inhabitants. The data for calculating the WAI were obtained by conducting interviews following a script of themes in the structured questionnaire closed to 370 residents of the communities evaluated. To calculate the WAI, weightings were used, in which the scores of the indicators and the weights of the dimensions were determined and analyzed using the Delphi method, what found to be a valid method for calculating the dimensions and indicators weights. Due to difficulty of rural population to have water access and suffer from drought, the proposed model showed appropriate to conduct a robust and well-structured decision-making. The main contributions were the study in region suffering from drought and difficulty in water access, as well as the combination of MCDA, SIG, CA and participation of rural inhabitants methods to aid in this problem. For use in other areas, researchers need to conduct public and specialized consultations to adjust the dimension weights, so the WAI method can estimate the water access situation and generate maps anywhere in the world for decision-making.

A sustainability assessment-based methodology for the prioritization of contaminated site risk management options

Contaminated site management is a multiple objective decision-making that generally involves different factors, such as performance of technology, environmental effects, cost, and social influence. In this study, we developed a sustainability assessment-based methodology for the prioritization of contaminated site risk management options. We integrate remediation sustainable assessment and redevelopment sustainable assessment in one framework and allow the optimization of indicators. The framework started with the definition of site management type, then investigating site characterization, screening indicators, quantifying of indicator, selecting assessment model, selecting primary options, assessment with uncertainty analysis, and determining of preferred options. To demonstrate the utility of the framework, results are presented in a contaminate site in southwest China for two risk management decisions, site remediation and site redevelopment. We used different approaches to evaluate the stability and robustness of assessment results, including Monte Carlo simulation, scenario analysis, and sensitivity analysis. The demonstration showed that attention has to be paid to the proper description of the site, the principles of the procedure, and the decision criteria.

Evaluating preferences for colorectal cancer screening in individuals under age 50 using the Analytic Hierarchy Process

BACKGROUND

In 2021, the United States Preventive Services Task Force updated their recommendation, stating that individuals ages 45-49 should initiate screening for colorectal cancer. Since several screening strategies are recommended, making a shared decision involves including an individual's preferences. Few studies have included individuals under age 50. In this study, we use a multicriteria decision analysis technique called the Analytic Hierarchy Process to explore preferences for screening strategies and evaluate whether preferences vary by age.

METHODS

Participants evaluated a hierarchy with 3 decision alternatives (colonoscopy, fecal immunochemical test, and computed tomography colonography), 3 criteria (test effectiveness, the screening plan, and features of the test) and 7 sub-criteria. We used the linear fit method to calculate consistency ratios and the eigenvector method for group preferences. We conducted sensitivity analysis to assess whether results are robust to change and tested differences in preferences by participant variables using chi-square and analysis of variance.

RESULTS

Of the 579 individuals surveyed, 556 (96%) provided complete responses to the AHP portion of the survey. Of these, 247 participants gave responses consistent enough (CR < 0.18) to be included in the final analysis. Participants that were either white or have lower health literacy were more likely to be excluded due to inconsistency. Colonoscopy was the preferred strategy in those < 50 and fecal immunochemical test was preferred by those over age 50 (p = 0.002). These results were consistent when we restricted analysis to individuals ages 45-55 (p = 0.011). Participants rated test effectiveness as the most important criteria for making their decision (weight = 0.555). Sensitivity analysis showed our results were robust to shifts in criteria and sub-criteria weights.

CONCLUSIONS

We reveal potential differences in preferences for screening strategies by age that could influence the adoption of screening programs to include individuals under age 50. Researchers and practitioners should consider at-home interventions using the Analytic Hierarchy Process to assist with the formulation of preferences that are key to shared decision-making. The costs associated with different preferences for screening strategies should be explored further if limited resources must be allocated to screen individuals ages 45-49.

A multi-stakeholder multicriteria decision analysis for the reimbursement of orphan drugs (FinMHU-MCDA study)

Background

Patient access to orphan medicinal products (OMPs) is limited and varies between countries, reimbursement decisions on OMPs are complex, and there is a need for more transparent processes to know which criteria should be considered to inform these decisions. This study aimed to determine the most relevant criteria for the reimbursement of OMPs in Spain, from a multi-stakeholder perspective, and using multicriteria decision analysis (MCDA).

Methods

An MCDA was developed in 3 phases and included 28 stakeholders closely related to the field of rare diseases (6 physicians, 5 hospital pharmacists, 7 health economists, 4 patient representatives and 6 members from national and regional health authorities). Initially [phase A], a bibliographic review was conducted to identify the potential reimbursement criteria. Then, a reduced advisory board (8 members) proposed, selected, and defined the final list of criteria that could be relevant for reimbursement. A discrete choice experiment (DCE) [phase B] was developed to determine the relevance and relative importance weight of such criteria according to the stakeholders’ preferences by choosing between pairs of hypothetical financing scenarios. A multinomial logit model was fitted to analyze the DCE responses. Finally [phase C], the advisory board review the results using a deliberative process.

Results

Thirteen criteria were selected, related to 4 dimensions: patient population, disease, treatment, and economic evaluation. Nine criteria were deemed relevant for decision-making and associated with a higher relative importance: Health-related quality of life (HRQL) (23.53%), treatment efficacy (14.64%), availability of treatment alternatives (13.51%), disease severity (12.62%), avoided costs (11.21%), age of target population (7.75%), safety (seriousness of adverse events) (4.72%), quality of evidence (3.82%) and size of target population (3.12%). The remaining criteria had a < 3% relative importance: economic burden of disease (2.50%), cost of treatment (1.73%), cost-effectiveness (0.83%) and safety (frequency of adverse events) (0.03%).

Conclusion

The reimbursement of OMPs in Spain should be determined by its effect on patient’s HRQL, the extent of its therapeutic benefit from efficacy and the availability of other therapeutic options. Furthermore, the severity of the rare disease should also influence the decision along with the potential of the treatment to avoid associated costs.

A decision support system for territorial resilience assessment and planning: An application to the Douro Valley (Portugal)

This paper aims to assess the territorial resilience of a socio-ecological system through an innovative integrated evaluation framework to aid the decision-making process in the planning of transformation scenarios. This framework employs a set of resilience indicators through a Multicriteria Decision Analysis (MCDA) coupled with a Lotka-Volterra mathematical model of cooperative type. The set of indicators aims to calculate a composite index of Territorial Resilience (TRI), whereas the mathematical model is an extension of an existing model, aimed to predict possible long-time scenarios. The proposed operational framework for rural and vineyard landscapes aims to bridge the existing gap between territorial resilience theory and practice, with an innovative Decision Support System able to assist Decision Makers and territory planners in the planning and management of resilient territorial systems. This integrated evaluation framework is applied to a famous wine region in Portugal, the Douro Valley, where Port-wine grows. Such framework, especially in a context of adaptive governance, proves to be a suitable support in the field of landscape and urban planning to evaluate the dynamics of socio-ecological systems and to envision long-term policies and actions.

Selecting Image-Guided Surgical Technologies in Oncology: A Surgeon's Perspective

BACKGROUND

To improve surgical performance, image-guided (IG) technologies are increasingly introduced. Yet, it is unknown which oncological procedures yield most value from these technologies. This study aimed to select the most promising IG technology per oncologic indication.

METHODS

An Analytic Hierarchical Process was used to evaluate three IG technologies: navigation, optical imaging, and augmented reality, in five oncologic indications compared with usual care. Sixteen decision criteria were selected. The relative importance of the criteria and the expected performance of the technologies were evaluated among surgeons. The combination of these scores gives the expected value per technology.

RESULTS

On criteria level, sparing critical tissue (9%-18%) and reducing the risk of local recurrence (11%-27%) were most important. Navigation was preferred in three indications-removal of lymph nodes (42%), liver (47%), and rectal tumors (33%). In removing rectal tumors, optical imaging was equally preferred (34%). In removing breast and tongue tumors, no technology was clearly preferred.

CONCLUSIONS

In selecting IG technologies, especially optical and navigation technologies are expected to add value in addition to usual care. Further development of those technologies for the preferred indications seems valuable. Multi-attribute analysis showed to be useful in prioritization of conducting clinical studies and steer research and development initiatives.

A methodology of evaluating sustainability index of a biomass processing enterprise: a case study of native cow dung-urine biorefinery

Agriculture and its allied sector contribute significantly to the gross domestic product of every country. Several small-scale enterprises engaged in waste biomass processing have been setup recently. Such industrial setups not only help in solving the waste management issues but also play an important role in offering employment at the grass root level generating a significant social impact along with economic advantage to the local entrepreneur. Hence, assessment of such biomass processing enterprise (BPE) based on economic, environment, and social parameters has become necessary. In this paper, a general framework for sustainability assessment is discussed using a case study of cow dung-urine biorefinery as a representative BPE. Real-time data of BPE has been collected for evaluation and a sustainability index (SI) is evaluated using multicriteria decision method. The SI is calculated as per the weightage assigned and value function of the indicator and criteria. The SI for the BPE was observed to be 0.69 for the chosen set of criteria and indicator and weightages. A sensitivity analysis has been performed to check the dependence of the results on the weightages assigned to various criteria and indicators. It was also observed that the results were more sensitive to the indicators having a low value function.

Dataset for the model of a municipality competitiveness in relation to the geothermal resources exploitation in Poland

This dataset corresponds with the manuscript "The impact of geothermal resources on the competitiveness of municipalities: evidence from Poland" [1]. In the paper, the geothermal resources are assumed as a local competitive advantage for the municipalities that exploit them. In order to examine the relation between the exploitation of the geothermal resources and local competitiveness we determine a model of municipality competitiveness in Poland. Concept of the local competitiveness is referred to place-based measures (Lovering [2], Mytelka and Farinelli [3], Plummer and Taylor [4], Kitson et al.[5]) and it is related to the management of local resources (Malecki [6], Turok [7]). Literature review suggests that the local competitiveness is best reflected in the indicators of economic welfare and sustainability (Meyer-Stamer [8], Audretsch et al.[9]). Therefore, we use an expert method to build the model of a municipality competitiveness indicators on the example of Poland. Throughout the Analytical Hierarchy Process (AHP) method engaged experts select the 24 indicators of local competitiveness. This method serves in situations of a problem complexity (Kamenetzky [10], Saaty [11]) and as a multicriteria method in the regional studies (Dinc et al. [12]). Aggregation of the AHP selected indicators yields a synthetic competitiveness index for each of the municipalities that we examine. This index constitutes the model dependent variable in the related research article. This procedure of building municipality competitiveness model sets an example of approaching a complex phenomenon such as the local competitiveness definition. The versatility of this method enables its application into related research cases.

Exploratory analysis and ranking of analytical procedures for short-chain chlorinated paraffins determination in environmental solid samples

Short-chain chlorinated paraffins are ones of the most recent chemical compounds that have been classified as persistent organic pollutants. They have various applications and are emitted to the environment. Despite the fact, that the content levels of these compounds in the environmental compartments should be monitored, there is still a lack of well-defined and validated analytical procedures, proposed or suggested by the national or international environmental protection agencies. Finding an appropriate analytical procedure (sensitive and green at the same time) from many available ones is very often a difficult task. Therefore it can be supported with multicriteria decision analysis. The dataset consisting of 22 procedures was described by 7 criteria, mainly referring to procedures greenness. The data treatment with cluster analysis and principal component analysis revealed the internal structure of the dataset. Moreover, both statistical tools allowed for reduction of dataset criteria to three. This was used for applying ternary plot to show the multicriteria decision analysis results within all possible weights. With the aid of chemometric and multicriteria decision analysis tools it was easy to assess the set of analytical procedure. Depending on the applied weights to assessment criteria different analytical procedures are the most appropriate (winners).

Multi-criteria analysis in the health area: selection of the most appropriate triage system for the emergency care units in natal

Background

Multiobjective decision-making processes present a high degree of complexity in their solution, and tools such as multicriteria decision analysis appear as a way to facilitate the decision-makers’ solution and ensure that the decision is made cohesively and efficiently. In the public health sector, decisions are even more delicate because they work not only with the direct influence of human needs, but also with limited financial resources. An important point for the emergency care units is the triage system, which consists of a pre-evaluation of the patients, classifying them according to the degree of life risk. Through triage, the patient can be attended more quickly and efficiently, streamlining the whole process. Thus, the present research endeavored to determine the most appropriate triage protocol for emergency healthcare units in Natal-RN city in Brazil and may help others less advanced countries to determine the most appropriate triage protocol for emergency healthcare.

Methods

In this study, we used the multicriteria analysis method known as FITradeoff. In addition, interviews and structured questionnaires applied with nurses, specialists and directors.

Results

Based on the questionnaires and preferences presented by the decision-makers, the Spanish Triage System was the most suitable protocol for the emergency care units, which presented with high ease of use and implementation.

Conclusions

This study reached its main objective, which was to determine the most appropriate triage protocol. In addition, it was observed the possibility of new research, such as the development of a specific protocol for this emergency care units and the creation of an application software for this new protocol.

Wind farm investments portfolio formation using GIS-based suitability analysis and simulation procedures

The use of renewable energy sources instead of conventional energy sources is at the core of policy actions to reduce dependency on fossil fuels worldwide. As a result, especially during the last decade, the cost of renewable energy has significantly decreased, enriching renewable energy cost-competitiveness. Due to the spatial nature of renewable energy sector-related decisions, the synergy of geographical information systems (GIS) and Multiple Criteria Decision Analysis (MCDA) models can enrich the quality of the related decisions given their ability to effectively support land management considerations. Moreover, their implementation significantly enriches the performance of the traditional capital projects evaluation methods (CPEM) by providing physical data to the sizing process in a quick and accurate manner. Thus, decision-making frameworks that combine GIS-based suitability analysis with traditional financial evaluation techniques can significantly enrich the planning phase to achieve efficient installations in terms of required area reduction, power generation maximization and local characteristics examination. With respect to the realization of wind energy exploitation projects, the paper at hand proposes a framework capable of expanding the use of the traditional GIS-based derived suitability index to establishing portfolios. Moreover, the proposed framework is enriched by robust analysis using Monte Carlo Simulation (MCS), which provides significant insights regarding the stability of the derived portfolios and the projects that they comprise. The proposed framework is illustrated through a case study in the Thrace region in northeastern Greece.

Assessing the sustainability of advanced materials using multicriteria decision analysis and the triple bottom line

Although advanced materials (AdMs) are beneficial in many applications, questions remain as to whether they are more or less sustainable than the conventional materials that they may replace. Currently, there is no available tool to provide clarity to these questions. Traditional approaches for evaluating the sustainability of a chemical or material are usually not standardized, and as a result, the metrics used in sustainability measurements are subjective and often vary from assessor to assessor. Additionally, sustainability characterizations resulting from these approaches are typically presented qualitatively and are often vaguely drawn, making it difficult to confidently and transparently conclude that 1 material is more sustainable than another. This paper aims to address these gaps by enabling stakeholders involved in the production, use, or governance of AdMs to assess the sustainability of AdMs in a consistent, objective, and quantitative way using a multicriteria decision analysis (MCDA)-based model. The model proposed herein adapts a triple-bottom-line (TBL) framework from the Institution of Chemical Engineers (IChemE) and incorporates criteria weights identified through a stakeholder values assessment conducted by surveying AdM practitioners. Results from the stakeholder values assessment show that the perceived importance of the economic component of the TBL varies the most across stakeholders, and that practitioners providing responses from the perspective of a nongovernmental environmental advocacy group or a regulator of AdMs such as the United States Environmental Protection Agency were more likely to score and weigh economic indicators lower and environmental indicators higher compared to when responding from a business owner perspective. The resulting MCDA-based model allows stakeholders to assess the sustainability of an AdM or AdM-enabled product and compare it to product alternatives, predict how other stakeholders might score a product by identifying the extent to which components of the TBL are valued by other stakeholders, and identify which subcriteria contribute most to an improvement in a product's sustainability score. Integr Environ Assess Manag 2019;00:1-8. © 2019 SETAC.

Multicriteria Decision Analysis Characterization of Chemical Hazard Assessment Data Sources

Chemical hazard assessment (CHA), which aims to investigate the inherent hazard potential of chemicals, has been developed with the purpose of promoting safer consumer products. Despite the increasing use of CHA in recent years, finding adequate and reliable toxicity data required for CHA is still challenging due to issues regarding data completeness and data quality. Also, collecting data from primary toxicity reports or literature can be time consuming, which promotes the use of secondary data sources instead. In this study, we evaluate and characterize numerous secondary data sources on the basis of 5 performance attributes: reliability, adequacy, transparency, volume, and ease of use. We use GreenScreen for Safer Chemicals v1.4 as the CHA framework, which defines the endpoints of interest used in this analysis. We focused upon 34 data sources that reflect 3 types of secondary data: chemical-oriented data sources, hazard-trait-oriented data sources, and predictive data sources. To integrate and analyze the evaluation results, we applied 2 multicriteria decision analysis (MCDA) methodologies: multiattribute utility theory (MAUT) and stochastic multiobjective acceptability analysis (SMAA). Overall, the findings in this research program allow us to explore the relative importance of performance criteria and the data source quality for effectively conducting CHA. Integr Environ Assess Manag 2019;00:1-14. © 2019 SETAC.

Ventilator-associated pneumonia diagnosis: a prioritization exercise based on multi-criteria decision analysis

The aim was to provide global experts ranking on priorities in diagnostic tools for VAP in clinical practice. A multiple criteria decision analysis (MCDA) was performed to identify diagnosis tools for VAP diagnosis. Priority factors were identified after literature review. An international, multidisciplinary expert panel reviewed variables and ranked diagnostic tools. Experts from ten European hospitals participated. Regarding bedside clinical practices, seven required chest X-ray use in all patients, whereas six reported the use of blood cultures and endotracheal aspirate in all patients. Invasive techniques were routinely performed in seven sites. CRP, PCT, and Gram stains were performed in all patients by 5, 2, and 8, respectively. Impact on patient outcomes, safety, and impact on the decision to start antibiotic therapy were ranked as the top three relevant concerns (7.7/10, 7/10, and 6.9/10, respectively). Chest X-ray was ranked as the most important imaging technique to diagnose VAP (score 251.7). Apart from blood cultures, endotracheal aspirate culture was identified as the main collection method for the microbiological testing (scores of 274.8 and 246.8, respectively). Mini-BAL was the preferred invasive technique with a score of 208. Top three biomarkers were CRP (score 184.3), PCT (181.3), and WBC (166.4). Gram stain (192.5) was prioritized among laboratory diagnostic techniques. Using MCDA, it is recommended to perform a combination of diagnostic techniques including images (chest X-ray), culture of clinical specimens (blood cultures and endotracheal aspirate), and biomarkers (CRP or PCT) for VAP diagnosis at the bedside. Gram stain was ranked as the preferred laboratory technique.

A Multicriteria Decision Framework for the Selection of Biomass Separation Equipment

For the first time, a two‐stage decision support framework for equipment selection, applied to biomass separation, is presented. In the first stage, the framework evaluates from a number of equipment based on the process requirements and outputs only those that offer a technically feasible separation. In the second stage, the analytic hierarchy process is applied for performing a multicriteria decision analysis to select amongst the feasible equipment based on separation performance and energy consumption criteria. This approach systematically considers the relative importance of those different alternatives and selection criteria by pairwise comparisons. The output of the framework is an overall ranking of equipment as well as a sensitivity analysis of the results for different weighting of the criteria. These results can be used to equip practitioners in the field of bioseparations with a tool for making more consistent and better‐informed equipment selection decisions.

Framework for determining optimal strategy for sustainable remediation of contaminated sediment: A case study in Northern Taiwan

Contaminated sediment may pose a serious threat to human health and ecosystems. However, sediment remediation is typically an expensive and time-consuming process. Therefore, an effective decision-making process for the remediation of contaminated sediment is essential for identifying the optimal approach. Since a single assessment for sediment remediation may be insufficient, combining different analytical approaches is highly recommended. The objective of this study was to develop a comprehensive assessment framework based on the concept of green and sustainable remediation that considers various environmental, economic, and social aspects for the management of contaminated sediment. We propose a framework based on human health risk assessment (HHRA) and cost-benefit analysis (CBA) and apply the multicriteria decision analysis (MCDA) technique to implement integrated and sustainable strategies for sediment management. We used the framework to determine the best alternative for managing heavy-metal-contaminated sediment in a river in Northern Taiwan. The results of the pre-remediation HHRA indicated an unacceptably high cancer risk to children, while the CBA revealed that a remediation project was economically feasible. Moreover, the results of the MCDA revealed that a strategy involving in-situ capping with anthracite-based activated carbon would be relatively inexpensive and result in low risk to human health. In addition, this strategy would have a higher environmental impact and greater public acceptance as compared to a method involving the dredging and washing of soil. Thus, in this case study, in-situ capping using anthracite-based activated carbon was identified as the preferable remediation alternative from multiple perspectives. The proposed framework should allow decision-makers to choose the optimal integrated management strategy for similar river sites with contaminated sediment.

Landslide susceptibility mapping in an area of underground mining using the multicriteria decision analysis method

Landslides are geomorphological phenomena that affect anthropogenic and natural features on the Earth's surface. Many previous studies have identified several factors that have contributed to landslides. Among these factors are physical characteristics, such as slope, aspect, and land cover, of Earth's surface. Moreover, landslides can be triggered by human activities such as underground mining. This study aims to identify landslide susceptibility areas by analyzing landslide-related factors, including land subsidence triggered by underground mining. The area of interest was Kozlu, Turkey, where underground mining has been in progress for the past 100 years. Thus, to identify landslide risk zones, the multicriteria decision analysis method, together with the analytical hierarchy method, was used. The datasets included were topography, land cover, geological settings, and mining-induced land subsidence. The spatial extent of land subsidence was estimated using a previously published model. A landslide susceptibility map (LSM) was developed using a purposely developed GIS-based software. The results were compared with a terrain deformation map, which was developed in a separate study using the differential synthetic aperture radar interferometry (DInSAR) technique. The results showed a substantial correlation between the LSM and DInSAR map. Furthermore, it was found that ~ 88% of the very high and high landslide risk areas coincided with location of the past landslide events. These facts suggest that the algorithm and data sources used were sufficient to produce a sufficiently accurate LSM, which may be used for various purposes such as urban planning.

Incorporating MCDA into HTA: challenges and potential solutions, with a focus on lower income settings

Background

Multicriteria decision analysis (MCDA) has the potential to bring more structure and transparency to health technology assessment (HTA). The objective of this paper is to highlight key methodological and practical challenges facing the use of MCDA for HTA, with a particular focus on lower and middle-income countries (LMICs), and to highlight potential solutions to these challenges.

Methodological challenges

Key lessons from existing applications of MCDA to HTA are summarized, including: that the socio-technical design of the MCDA reflect the local decision problem; the criteria set properties of additive models are understood and applied; and the alternative approaches for estimating opportunity cost, and the challenges with these approaches are understood.

Practical challenges

Existing efforts to implement HTA in LMICs suggest a number of lessons that can help overcome the practical challenges facing the implementation of MCDA in LMICs, including: adapting inputs from other settings and from expert opinion; investing in technical capacity; embedding the MCDA in the decision-making process; and ensuring that the MCDA design reflects local cultural and social factors.

Conclusion

MCDA has the potential to improve decision making in LMICs. For this potential to be achieved, it is important that the lessons from existing applications of MCDA are learned.

MCDA or preference-based social welfare functions?

Preference-based social welfare functions (pbSWF) perform better at reconciling competing personal and social goals than typical forms of MCDA. Its virtues are (a) its respect for people’s own judgments about the relative values of health, wealth, and other broad benefits within their lives (non-paternalism) and (b) its conformity with reasonable ethical axioms. Any discrepancy between an MCDA objective function and that implied by pbSWF suggests the former’s failure to respect non-paternalism and reasonable ethical principles. The pbSWF approach is implementable using micro-econometric evidence on personal preferences over health, wealth, and other broad benefits; and surveys of the general population or their representatives to ascertain the social acceptability of certain ethical axioms and the degree of inequality aversion.

Multicriteria decision analysis (MCDA) in health care: a systematic review of the main characteristics and methodological steps

Background

The health area is one of the most affected systems on the perspective of decision-making with multiobjectives, thus becoming prone to errors in the final solution, however, multicriteria decision analysis (MDCA) appears as an aid tool for this process decision-making. Therefore,the present study aims to analyze and synthesize articles found in the literature, involing MCDA in health care, evaluating general issues and methodological aspects, structuring them in a single work.

Methods

Surveys in the bibliographic databases SCOPUS and PUBMED indicated 1852 documents on the subject, however after a careful verificatios, 66 studies were selected to be analyzed completely. The data extracted from the included articles were organized into a spreadsheet for the preparation of analysis, and the technique used was descriptive statistics.

Results

It was possible to identify a growth trend in the application of the MCDA in the health area, but no dominance was identified in relation to the authors of the publication and the periodicals where they are published, but some countries stood out in terms of the number of published researches, such as: Canada and Turkey. In defining the decision problem, and in defining criteria, the “literature” presented the greatest demand for those who wish to structure their decision problem. Finally, it was verified by the analysis of the problem, that the MCDA to solve the problems of ranking has comprehensive application and that there is a greater incidence in the use of the AHP and Logic methods Fuzzy.

Conclusion

With this, it is possible to observe, through the data of this review, that more than the multicriteria methods, the multicriteria decision model has been highlighted, also in the health area. In addition, the study can guide new applications and techniques using MCDA in the health care.

A multicriteria resource allocation model for the redesign of services following birth

BACKGROUND

Many healthcare services are under considerable pressure to reduce costs while improving quality. This is particularly true in the United Kingdom's National Health Service where postnatal care is sometimes viewed as having a low priority. There is much debate about the service's redesign and the reallocation of resources, both along care pathways and between groups of mothers and babies with different needs. The aim of this study was to develop a decision support tool that would encourage a systemic approach to service redesign and that could assess the various quality and financial implications of service change options making the consequent trade-offs explicit. The paper describes the development process and an initial implementation as a preliminary exploration of the possible merits of this approach.

METHODS

Other studies have suggested that combining multicriteria decision analysis with programme budgeting and marginal analysis might offer a suitable basis for resource allocation decisions in healthcare systems. The Postnatal care Resource Allocation Model incorporated this approach in a decision support tool to analyse the consequences of varying design parameters, notably staff contacts and time, on the various quality domains and costs. The initial phase of the study focussed on mapping postnatal care, involving interviews and workshops with a variety of stakeholders. This was supplemented with a literature review and the resultant knowledge base was encoded in the decision support tool. The model was then tested with various stakeholders before being used in an NHS Trust in England.

RESULTS

The model provides practical support, helping staff explore options and articulate their proposals for the redesign of postnatal care. The integration of cost and quality domains facilitates trade-offs, allowing staff to explore the benefits of reallocating resources between hospital and community-based care, and different patient-categories.

CONCLUSIONS

The main benefits of the model include its structure for assembling the key data, sharing evidence amongst multi-professional teams and encouraging constructive, systemic debate. Although the model was developed in the context of the routine maternity services for mothers and babies in the days following birth it could be adapted for use in other health care services.

Integrating social justice concerns into economic evaluation for healthcare and public health: A systematic review

Social justice is the moral imperative to avoid and remediate unfair distributions of societal disadvantage. In priority setting in healthcare and public health, social justice reaches beyond fairness in the distribution of health outcomes and economic impacts to encompass fairness in the distribution of policy impacts upon other dimensions of well-being. There is an emerging awareness of the need for economic evaluation to integrate all such concerns. We performed a systematic review (1) to describe methodological solutions suitable for integrating social justice concerns into economic evaluation, and (2) to describe the challenges that those solutions face. To be included, publications must have captured fairness considerations that (a) involve cross-dimensional subjective personal life experience and (b) can be manifested at the level of subpopulations. We identified relevant publications using an electronic search in EMBASE, PubMed, EconLit, PsycInfo, Philosopher's Index, and Scopus, including publications available in English in the past 20 years. Two reviewers independently appraised candidate publications, extracted data, and synthesized findings in narrative form. Out of 2388 publications reviewed, 26 were included. Solutions sought either to incorporate relevant fairness considerations directly into economic evaluation or to report them alongside cost-effectiveness measures. The majority of reviewed solutions, if adapted to integrate social justice concerns, would require their explicit quantification. Four broad challenges related to the implementation of these solutions were identified: clarifying the normative basis; measuring and determining the relative importance of criteria representing that basis; combining the criteria; and evaluating trade-offs. All included solutions must grapple with an inherent tension: they must either face the normative and operational challenges of quantifying social justice concerns or accede to offering incomplete policy guidance. Interdisciplinary research and broader collaborations are crucial to address these challenges and to support due attention to social justice in priority setting.

Individual Trade-Offs Between Possible Benefits and Risks of Cancer Treatments: Results from a Stated Preference Study with Patients with Multiple Myeloma

The objectives of this study were to ascertain the treatment preferences of patients with multiple myeloma, considering benefits and risks of particular cancer treatments, and to illustrate how such data may be used to estimate patients' acceptance of new treatments.

Background.

The objectives of this study were to elicit the preferences of patients with multiple myeloma regarding the possible benefits and risks of cancer treatments and to illustrate how such data may be used to estimate patients’ acceptance of new treatments.

Patients and Methods.

Patients with multiple myeloma from the cancer charity Myeloma UK were invited to participate in an online survey based on multicriteria decision analysis and swing weighting to elicit individual stated preferences for the following attributes: (a) 1‐year progression‐free survival (PFS, ranging from 50% to 90%), (b) mild or moderate toxicity for 2 months or longer (ranging from 85% to 45%), and (c) severe or life‐threatening toxicity (ranging from 80% to 20%).

Results.

A total of 560 participants completed the survey. The average weight given to PFS was 0.54, followed by 0.32 for severe or life‐threatening toxicity and 0.14 for mild or moderate chronic toxicity. Participants who ranked severe or life‐threatening toxicity above mild or moderate chronic toxicity (56%) were more frequently younger, working, and looking after dependent family members and had more frequently experienced severe or life‐threatening side effects. The amount of weight given to PFS did not depend on any of the collected covariates. The feasibility of using the collected preference data to estimate the patients’ acceptance of specific multiple myeloma treatments was demonstrated in a subsequent decision analysis example.

Conclusion.

Stated preference studies provide a systematic approach to gain knowledge about the distribution of preferences in the population and about what this implies for patients’ acceptance of specific treatments.

Implications for Practice.

This study demonstrated how quantitative preference statements from a large group of participants can be collected through an online survey and how such information may be used to explore the acceptability of specific treatments based on the attributes studied. Results from such studies have the potential to become an important new tool for gathering patient views and studying heterogeneity in preferences in a systematic way, along with other methods, such as focus groups and expert opinions.

Potential of an outranking multi-criteria approach to support the participatory assessment of land management actions

We evaluated the potential of an outranking Multi-Criteria Decision Analysis approach for assisting in the participatory assessment of dryland management actions implemented in the San Simon watershed, in southeastern Arizona, USA. We compared an outranking-facilitated assessment of actions with a simple and direct (baseline) ranking of the same actions by the participating stakeholders in terms of: 1) internal homogeneity of each assessment approach, (2) similarity of individual assessments between methods, and (3) effects of the use of implicit/explicit assessment criteria. The actions assessed combined various management approaches, including livestock management (rotation, resting), vegetation management (grass seeding, brush control), and hydraulic structures (dams, dykes). The outranking-facilitated assessment discriminated better between actions and reduced the variability of results between individual stakeholders as compared with the direct ranking of actions. In general, the two assessments significantly differed in the relative preference of the five management actions assessed, yet both assessments identified rotational grazing combined with vegetation management (grass seeding and brush control) as the most preferred management action in the study area. The comparative analysis revealed inconsistencies between the use of implicit and explicit assessment criteria. Our findings highlight the opportunities offered by outranking approaches to help capture, structure, and make explicit stakeholder perspectives in the framework of a participatory environmental assessment process, which may facilitate the understanding of the multiple preferences involved. The outranking integration process, which resembles a voting procedure, proved simple and transparent, with potential for contributing to stakeholder engagement and trust in participatory assessment.

A simple way to unify multicriteria decision analysis (MCDA) and stochastic multicriteria acceptability analysis (SMAA) using a Dirichlet distribution in benefit-risk assessment

Quantitative methodologies have been proposed to support decision making in drug development and monitoring. In particular, multicriteria decision analysis (MCDA) and stochastic multicriteria acceptability analysis (SMAA) are useful tools to assess the benefit-risk ratio of medicines according to the performances of the treatments on several criteria, accounting for the preferences of the decision makers regarding the relative importance of these criteria. However, even in its probabilistic form, MCDA requires the exact elicitations of the weights of the criteria by the decision makers, which may be difficult to achieve in practice. SMAA allows for more flexibility and can be used with unknown or partially known preferences, but it is less popular due to its increased complexity and the high degree of uncertainty in its results. In this paper, we propose a simple model as a generalization of MCDA and SMAA, by applying a Dirichlet distribution to the weights of the criteria and by making its parameters vary. This unique model permits to fit both MCDA and SMAA, and allows for a more extended exploration of the benefit-risk assessment of treatments. The precision of its results depends on the precision parameter of the Dirichlet distribution, which could be naturally interpreted as the strength of confidence of the decision makers in their elicitation of preferences.

Sustainability assessment and prioritisation of e-waste management options in Brazil

Brazil has an increasing rate of e-waste generation, but there are currently few adequate management systems in operation, with the largest share of Waste Electrical and Electronic Equipment (WEEE) going to landfill sites or entering informal chains. The National Solid Waste Policy (2010) enforces the implementation of reverse logistics systems under the shared responsibility of consumers, companies and governments. The objective of this paper is to assess sustainability and prioritise system alternatives for potential implementation in the metropolitan region of Rio de Janeiro. Sustainability criteria and decision alternatives were defined by elicitation of stakeholders. The adopted multicriteria approach combines Life Cycle Assessment with qualitative evaluations by a small sample of regional experts with knowledge of the problem. The recommended system consists of a hybrid WEEE collection scheme with delivery points at shops, metro stations and neighbourhood centres; a pre-treatment phase with the involvement of private companies, cooperatives and social enterprises; and full recycling of all components in the country.

Social life cycle assessment and participatory approaches: A methodological proposal applied to citrus farming in Southern Italy

Recently, Social Life Cycle Assessment (S-LCA) has been developed under the methodological framework of Life Cycle Thinking (LCT) to evaluate the social impacts that emerge during the overall life cycle of a product or service. There is not yet a standardized methodology for S-LCA as there is for environmental LCA (eLCA), due to the nature of social impacts that do not depend only on the processes themselves, but also on the behavior and context of actors (manufactures, consumers, local community members, etc.). One of the most critical steps in the application of S-LCA concerns the choice of criteria for selecting affected actors, impact categories, subcategories, and the taxonomic relation among them. Moreover, the importance (in terms of weight) of these impacts may be felt differently by affected actors, confirming the importance of the context within which impacts arise. In this sense, the integration of participatory tools can be useful in making the S-LCA more locally relevant. The aim of the present study is twofold. First, we will outline a methodology that combines S-LCA with two research tools. The first is the focus group, adopted from qualitative research. The second is the Analytic Hierarchy Process (AHP), adopted from operational research, which belongs to the framework of Multicriteria Decision Analysis (MCDA). These have been used to make the S-LCA more locally relevant and to legitimate the criteria used. Second, we will test this methodology by applying it to a specific field, i.e., 3 production areas and 3 different crop systems of citrus growing in the Calabria region in Southern Italy. Citrus growing is one of the most important agricultural sectors at regional level, and it is also well known for issues of social concern, particularly in relation to immigrant workers. The results show a number of differences between cases and could offer useful insights to both local decision makers, such as agricultural entrepreneurs, and to those public decision makers that design and implement territorial planning strategies. Results have allowed the authors to rank the social performance of each case and to reflect on the most critical steps in conducting an S-LCA.

KEY FINDINGS

The integration of qualitative techniques and a multicriteria in sLCA allows catching local specificities by involving local experts and stakeholders Results highlighted that impact categories mostly contributed to performance differences Public deciders can be supported in deciding which farming practices should be encouraged, which social domains must be paid more attention, and where social problems mostly occur The methodological application allowed the authors also to foresee the feasibility of the integration of LCA and LCC results as inputs in sLCA to conduct a Life Cycle Sustainability Assessment (LCSA).