Into the Jungle of Biological Agents of Foodborne Diseases: Time to Put Some Order for the French Risk Manager.

Consumers can be exposed to many foodborne biological hazards that cause diseases with varying outcomes and incidence and, therefore, represent different levels of public health burden. To help the French risk managers to rank these hazards and to prioritize food safety actions, we have developed a three-step approach. The first step was to develop a list of foodborne hazards of health concern in mainland France. From an initial list of 335 human pathogenic biological agents, the final list of "retained hazards" consists of 24 hazards, including 12 bacteria (including bacterial toxins and metabolites), 3 viruses and 9 parasites. The second step was to collect data to estimate the disease burden (incidence, Disability Adjusted Life Years) associated with these hazards through food during two time periods: 2008-2013 and 2014-2019. The ranks of the different hazards changed slightly according to the considered period. The third step was the ranking of hazards according to a multicriteria decision support model using the ELECTRE III method. Three ranking criteria were used, where two reflect the severity of the effects (Years of life lost and Years lost due to disability) and one reflects the likelihood (incidence) of the disease. The multicriteria decision analysis approach takes into account the preferences of the risk managers through different sets of weights and the uncertainties associated with the data. The method and the data collected allowed to estimate the health burden of foodborne biological hazards in mainland France and to define a prioritization list for the health authorities.

Determining value in the treatment of activated PI3Kδ syndrome in Spain: a multicriteria decision analysis from the perspective of key stakeholders.

Introduction: Activated phosphoinositide 3-kinase (PI3K)δ syndrome (APDS) is an ultra-rare inborn error of immunity (IEI) combining immunodeficiency and immune dysregulation. This study determined what represents value in APDS in Spain from a multidisciplinary perspective applying multicriteria decision analysis (MCDA) methodology. Methods: A multidisciplinary committee of nine experts scored the evidence matrix. A specific framework for orphan drug evaluation in Spain and the weights assigned by a panel of 98 evaluators and decision-makers was used. Re-evaluation of scores was performed. Results: APDS is considered a very severe disease with important unmet needs, including misdiagnosis and diagnostic delay. Current management is limited to treatment of symptoms with off-label use of therapies supported by limited evidence. Therapeutic benefit is partial, resulting in limited disease control. Haematopoietic stem cell transplantation (HSCT), the only potential curative alternative, is restricted to a reduced patient population and without evidence of long-term efficacy or safety. All options present a limited safety profile. Data on patients' quality of life are lacking. APDS is associated with high pharmacological, medical and indirect costs. Conclusions: APDS is considered a severe disease, with limited understanding by key stakeholders of how treatment success is assessed in clinical practice, the serious impact that has on patients and the associated high economic burden. This study brings to light how MCDA methodology could represent a useful tool to complement current clinical and decision-making methods used by APDS experts and evaluators.

Development of a Value Assessment Framework for Pediatric Health Technologies Using Multicriteria Decision Analysis: Expanding the Value Lens for Funding Decision Making.

OBJECTIVES: A health technology assessment (HTA) does not systematically account for the circumstances and needs of children and youth. To supplement HTA processes, we aimed to develop a child-tailored value assessment framework using a multicriteria decision analysis approach. METHODS: We constructed a multicriteria-decision-analysis-based model in multiple phases to create the Comprehensive Assessment of Technologies for Child Health (CATCH) framework. Using a modified Delphi process with stakeholders having broad disciplinary and geographic variation (N = 23), we refined previously generated criteria and developed rank-based weights. We established a criterion-pertinent scoring rubric for assessing incremental benefits of new drugs. Three clinicians independently assessed comprehension by pilotscoring 9 drugs. We then validated CATCH for 2 childhood cancer therapies through structured deliberation with an expert panel (N = 10), obtaining individual scores, consensus scores, and verbal feedback. Analyses included descriptive statistics, thematic analysis, exploratory disagreement indices, and sensitivity analysis. RESULTS: The modified Delphi process yielded 10 criteria, based on absolute importance/relevance and agreed importance (median disagreement indices = 0.34): Effectiveness, Child-specific Health-related Quality of Life, Disease Severity, Unmet Need, Therapeutic Safety, Equity, Family Impacts, Life-course Development, Rarity, and Fair Share of Life. Pilot scoring resulted in adjusted criteria definitions and more precise score-scaling guidelines. Validation panelists endorsed the framework's key modifiers of value. Modes of their individual prescores aligned closely with deliberative consensus scores. CONCLUSIONS: We iteratively developed a value assessment framework that captures dimensions of child-specific health and nonhealth gains. CATCH could improve the richness and relevance of HTA decision making for children in Canada and comparable health systems.

Revision of Malawi's Health Benefits Package: A Critical Analysis of Policy Formulation and Implementation.

OBJECTIVES: Health benefits packages (HBPs), which define specific health services that can be offered for free or at a reduced cost to fit within public revenues, have been recommended for over 30 years to maximize population health in resource-limited settings. However, there remain gaps in defining and operationalizing HBPs. We propose a combination of design and prioritization methods along with practical strategies to improve the implementation of future iterations of the HBP in Malawi. METHODS: For HBP development for Malawi's Third Health Sector Strategic Plan, we combined cost-effectiveness analysis with a quantitative, consultative multicriteria decision analysis. Throughout the process of development, we documented challenges and opportunities to improve HBP design and application. RESULTS: The primary and secondary HBP included 115 interventions. However, the definition of an HBP is just one step toward focusing limited resources, with functional operationalization as the most critical component. Full implementation of previous HBPs has been limited by challenges in aid coordination with the misalignment of nonfungible vertical donor funding for the HBP without accounting for the complexity and interconnectedness of the health system. Opportunities for improved application include creation of a complementary minimum health service package to guide overall resource inputs through an integrative approach. CONCLUSIONS: We believe that expanded participatory HBP methods that consider value, equity, and social considerations, along with a shift to providing integrated health service packages at all levels of care, will improve the efficiency of using scarce resources along the journey to universal health coverage.

Advancing hospital-based health technology assessment: evaluating genomic panel contracting strategies for blood tumors through a multimethodology.

INTRODUCTION: The adoption of genomic technologies in the context of hospital-based health technology assessment presents multiple practical and organizational challenges. OBJECTIVE: This study aimed to assist the Instituto Português de Oncologia de Lisboa Francisco Gentil (IPO Lisboa) decision makers in analyzing which acute myeloid leukemia (AML) genomic panel contracting strategies had the highest value-for-money. METHODS: A tailored, three-step approach was developed, which included: mapping clinical pathways of AML patients, building a multicriteria value model using the MACBETH approach to evaluate each genomic testing contracting strategy, and estimating the cost of each strategy through Monte Carlo simulation modeling. The value-for-money of three contracting strategies - "Standard of care (S1)," "FoundationOne Heme test (S2)," and "New diagnostic test infrastructure (S3)" - was then analyzed through strategy landscape and value-for-money graphs. RESULTS: Implementing a larger gene panel (S2) and investing in a new diagnostic test infrastructure (S3) were shown to generate extra value, but also to entail extra costs in comparison with the standard of care, with the extra value being explained by making available additional genetic information that enables more personalized treatment and patient monitoring (S2 and S3), access to a broader range of clinical trials (S2), and more complete databases to potentiate research (S3). CONCLUSION: The proposed multimethodology provided IPO Lisboa decision makers with comprehensive and insightful information regarding each strategy's value-for-money, enabling an informed discussion on whether to move from the current Strategy S1 to other competing strategies.

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.

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.

Stakeholder opinion-led study to identify canine priority diseases for surveillance and control in the UK.

BACKGROUND: Many pathogens cause disease in dogs; however, meaningful surveillance in small companion animals is often only possible for the most impactful diseases. We describe the first stakeholder opinion-led approach to identify which canine infectious diseases should be prioritised for inclusion in surveillance and control strategies in the UK. METHODS: Participants were identified through a stakeholder analysis. A multicriteria decision analysis was undertaken to establish and weight epidemiological criteria for evaluating diseases, and a Delphi technique was employed to achieve a consensus among participants on the top-priority canine diseases. RESULTS: Nineteen stakeholders from multiple backgrounds participated in this study. Leptospirosis and parvovirus were identified as the top two endemic diseases of concern, while leishmaniosis and babesiosis were the top two exotic diseases. Respiratory and gastrointestinal diseases were identified as the top two syndromes of concern. LIMITATIONS: Due to the COVID-19 pandemic, the number of participants was reduced. Despite this, a representative multidisciplinary sample of relevant stakeholders contributed to the present study. CONCLUSIONS: Findings from this study are being used to inform the development of a future UK-wide epidemic response strategy. This methodology could provide a blueprint for other countries.

Prioritization of vegetable-borne biological hazards in Argentina using a multicriteria decision analysis tool.

Vegetables, especially those eaten raw, have been implicated in several foodborne disease outbreaks. Since multiple vegetable matrices and hazards are involved, risk managers have to prioritize those with the greatest impact on public health to design control strategies. In this study, a scientific-based risk ranking of foodborne pathogens transmitted by leafy green vegetables in Argentina was performed. The prioritization process included hazard identification, evaluation criteria identification and definition, criteria weighting, expert survey design and selection and call for experts, hazard score calculation, hazard ranking and variation coefficient, and result analysis. Regression tree analysis determined four risk clusters: high (Cryptosporidum spp., Toxoplasma gondii, Norovirus), moderate (Giardia spp., Listeria spp., Shigella sonnei), low (Shiga toxin-producing Escherichia coli, Ascaris spp., Entamoeba histolytica, Salmonella spp., Rotavirus, Enterovirus) and very low (Campylobacter jejuni, hepatitis A virus and Yersinia pseudotuberculosis). Diseases caused by Norovirus, Cryptosporidium spp. and T. gondii do not require mandatory notification. Neither viruses nor parasites are included as microbiological criteria for foodstuff. The lack of outbreak studies did not allow to accurately identify vegetables as a source of Norovirus disease. Information on listeriosis cases or outbreaks due to vegetable consumption was not available. Shigella spp. was the main responsible for bacterial diarrhea, but it has not been epidemiologically associated with vegetable consumption. The quality of the available information for all hazards studied was very low and low. The implementation of good practice guidelines throughout the entire vegetable production chain could prevent the presence of the identified hazards. The current study allowed the identification of vacancy areas and could help reinforce the need for performing epidemiological studies on foodborne diseases potentially associated with vegetable consumption in Argentina.

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.

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.

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.

Quantitative Benefit-Risk Assessment in Medical Product Decision Making: A Good Practices Report of an ISPOR Task Force.

Benefit-risk assessment is commonly conducted by drug and medical device developers and regulators, to evaluate and communicate issues around benefit-risk balance of medical products. Quantitative benefit-risk assessment (qBRA) is a set of techniques that incorporate explicit outcome weighting within a formal analysis to evaluate the benefit-risk balance. This report describes emerging good practices for the 5 main steps of developing qBRAs based on the multicriteria decision analysis process. First, research question formulation needs to identify the needs of decision makers and requirements for preference data and specify the role of external experts. Second, the formal analysis model should be developed by selecting benefit and safety endpoints while eliminating double counting and considering attribute value dependence. Third, preference elicitation method needs to be chosen, attributes framed appropriately within the elicitation instrument, and quality of the data should be evaluated. Fourth, analysis may need to normalize the preference weights, base-case and sensitivity analyses should be conducted, and the effect of preference heterogeneity analyzed. Finally, results should be communicated efficiently to decision makers and other stakeholders. In addition to detailed recommendations, we provide a checklist for reporting qBRAs developed through a Delphi process conducted with 34 experts.

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.

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.

Illustrating Emerging Good Practices for Quantitative Benefit-Risk Assessment: A Hypothetical Case Study of Systemic Biologic Treatments for Plaque Psoriasis.

OBJECTIVES: Quantitative benefit-risk assessment (qBRA) is a structured process to evaluate the benefit-risk balance of treatment options to support decision making. The ISPOR qBRA Task Force was recently established to provide recommendations for the design, conduct, and reporting of qBRA. This report presents a hypothetical case study illustrating how to apply the Task Force's recommendations toward a qBRA to inform the benefit-risk assessment of brodalumab at the time of initial marketing approval. The qBRA evaluated 2 dosing regimens of brodalumab (210 mg or 140 mg twice weekly) compared with weight-based dosing of ustekinumab and placebo. METHODS: We followed the 5 steps recommended by the Task Force. Attributes included treatment response (≥75% improvement in Psoriasis Area and Severity Index), suicidal ideation and behavior, and infections. Performance data were drawn from pivotal clinical trials of brodalumab. The qBRA used multicriteria decision analysis and preference weights from a hypothetical discrete choice experiment. Sensitivity analyses examined the robustness of benefit-risk ranking to uncertainty in clinical effect and preference estimates, consideration of a subgroup (nail psoriasis), and the maintenance phase of treatment (52 weeks instead of 12). RESULTS: Results from this hypothetical qBRA suggest that brodalumab 210 mg had a more favorable benefit-risk profile compared with ustekinumab and placebo. Ranking of brodalumab compared with ustekinumab was dependent on brodalumab's dose. Sensitivity analyses demonstrated robustness of benefit-risk ranking to uncertainty in clinical effect and preference estimates, as well as choice of attributes and length of follow-up. CONCLUSION: This case study demonstrates how to implement the ISPOR Task Force's good practice recommendations on qBRA.

Suitability of Preference Methods Across the Medical Product Lifecycle: A Multicriteria Decision Analysis.

OBJECTIVES: This study aimed to understand the importance of criteria describing methods (eg, duration, costs, validity, and outcomes) according to decision makers for each decision point in the medical product lifecycle (MPLC) and to determine the suitability of a discrete choice experiment, swing weighting, probabilistic threshold technique, and best-worst scale cases 1 and 2 at each decision point in the MPLC. METHODS: Applying multicriteria decision analysis, an online survey was sent to MPLC decision makers (ie, industry, regulatory, and health technology assessment representatives). They ranked and weighted 19 methods criteria from an existing performance matrix about their respective decisions across the MPLC. All criteria were given a relative weight based on the ranking and rating in the survey after which an overall suitability score was calculated for each preference elicitation method per decision point. Sensitivity analyses were conducted to reflect uncertainty in the performance matrix. RESULTS: Fifty-nine industry, 29 regulatory, and 5 health technology assessment representatives completed the surveys. Overall, "estimating trade-offs between treatment characteristics" and "estimating weights for treatment characteristics" were highly important criteria throughout all MPLC decision points, whereas other criteria were most important only for specific MPLC stages. Swing weighting and probabilistic threshold technique received significantly higher suitability scores across decision points than other methods. Sensitivity analyses showed substantial impact of uncertainty in the performance matrix. CONCLUSION: Although discrete choice experiment is the most applied preference elicitation method, other methods should also be considered to address the needs of decision makers. Development of evidence-based guidance documents for designing, conducting, and analyzing such methods could enhance their use.

The Use of Multicriteria Decision Analysis to Support Decision Making in Healthcare: An Updated Systematic Literature Review.

OBJECTIVES: Multicriteria decision analysis (MCDA) is increasingly used for decision making in healthcare. However, its application in different decision-making contexts is still unclear. This study aimed to provide a comprehensive review of MCDA studies performed to inform decisions in healthcare and to summarize its application in different decision contexts. METHODS: We updated a systematic review conducted in 2013 by searching Embase, MEDLINE, and Google Scholar for MCDA studies in healthcare, published in English between August 2013 and November 2020. We also expanded the search by reviewing grey literature found via Trip Medical Database and Google, published between January 1990 and November 2020. A comprehensive template was developed to extract information about the decision context, criteria, methods, stakeholders involved, and sensitivity analyses conducted. RESULTS: From the 4295 identified studies, 473 studies were eligible for full-text review after assessing titles and abstracts. Of those, 228 studies met the inclusion criteria and underwent data extraction. The use of MCDA continues to grow in healthcare literature, with most of the studies (49%) informing priority-setting decisions. Safety, cost, and quality of care delivery are the most frequently used criteria, although there are considerable differences across decision contexts. Almost half of the MCDA studies used the linear additive model whereas scales and the analytical hierarchy process were the most used techniques for scoring and weighting, respectively. Not all studies report on each one of the MCDA steps, consider axiomatic properties, or justify the methods used. CONCLUSIONS: A guide on how to conduct and report MCDA that acknowledges the particularities of the different decision contexts and methods needs to be developed.