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

A comprehensive review on applications of multi-criteria decision-making methods in healthcare waste management

Effective management of healthcare waste (HCW) imposes a great challenge to all countries. Specially in the developing countries, it is often mixed with municipal waste, adversely affecting the health and safety of the medical personnel, general public and environment. Healthcare waste management (HCWM) basically deals with segregation, collection and storage, routing and transportation, treatment and safe disposal of HCW, while obeying some national legislation. In every stage of HCWM, there are several alternative choices/strategies to be evaluated against a set of conflicting criteria. Numerous multi-criteria decision-making (MCDM) methods have appeared to resolve the issue. This article reviews 101 articles available in Scopus and other scholarly databases on applications of MCDM techniques in solving HCWM problems. Those articles are classified into six groups: (a) selection of the most effective HCW treatment technology, (b) identification of the best HCW disposal site, (c) assessment of the best-performing healthcare unit adopting ideal HCWM strategies, (d) selection of third party logistics providers, (e) identification of HCWM barriers and (f) evaluation of specific HCWM plans. It is observed that the past researchers have mostly preferred to apply MCDM tools for solving HCW treatment technology selection problems, whereas analytic hierarchy process, decision-making trial and evaluation laboratory and best-worst method and fuzzy set theory have been the mostly favoured MCDM tool, criteria weight measurement techniques and uncertainty model, respectively. The outcomes of this article would help the healthcare personnel/policymakers in unveiling the current status of HCWM research, exploring extant research gaps and challenges and providing future directions leading to sustainable environment.

Value contribution of leniolisib in the Treatment of Activated PI3Kδ syndrome (APDS) in Spain using Multi-Criteria Decision Analysis (MCDA)

Background

Activated phosphoinositide 3-kinase (PI3K) δ Syndrome (APDS) is an ultra-rare, potentially life-threatening disease that lacks approved treatments in Spain. This study aimed to apply Multi-Criteria Decision Analysis (MCDA) to assess the value of the first pharmacological treatment for APDS in Spain.

Methods

A multidisciplinary group of 8 experts evaluated the selective PI3Kδ inhibitor leniolisib against Standard of Care (SoC). An MCDA framework tailored for Orphan Drugs (ODs), consisting of 5 comparative and 2 quantitative non-comparative criteria, was used. Re-scoring followed a group discussion.

Results

Leniolisib scored higher than SoC in all criteria, including efficacy and safety. It was deemed highly valuable as the first disease-modifying treatment, with a positive therapeutic impact and potential to improve patients' quality of life. Additionally, leniolisib may lead to cost savings. The supporting data was considered of high quality.

Conclusion

Based on MCDA methodology and stakeholder experience in APDS management, leniolisib is seen as a value-added treatment option compared to SoC in Spain.

Development of a Prioritization Framework to Aid Healthcare Funding Decision Making in Health Technology Assessment in Australia: Application of Multicriteria Decision Analysis

OBJECTIVES

This study develops a prioritization framework to aid healthcare funding decision making in health technology assessment (HTA) in Australia using a multiple criteria decision analysis (MCDA) approach.

METHODS

MCDA frameworks for HTAs were reviewed through literature survey to identify the initial criteria and levels within each criterion. Key stakeholders and experts were consulted to confirm these criteria and levels. A conjoint analysis using 1000Minds was undertaken with policy makers from the Department of Health to establish ranking criteria and weighting scores. Monte Carlo simulations were used to examine the sensitivity of findings to factors affecting the ranking and weighting scores. The MCDA was then applied to 6 examples of chronic care models or technologies projects to demonstrate the performance of this approach.

RESULTS

Five criteria (clinical efficacy/effectiveness, safety and tolerability, severity of the condition, quality/uncertainty, and direct impact on healthcare costs) were consistently ranked highest by healthcare decision makers. Among the criteria, patient-level health outcomes were considered the most important, followed by social and ethical values. The analyses were robust to inform the uncertainty in the parameter.

CONCLUSIONS

This study has developed an MCDA tool that effectively integrates key priorities for HTA reviews, reflecting the values and preferences of healthcare stakeholders in Australia. Although this tool aims to align the assessment process more closely with health benefits, it also highlights the importance of considering other criteria.

Scenario analysis and multi-criteria decision analysis to explore alternative reimbursement pathways for whole genome sequencing for blood cancer patients

BACKGROUND

Whole genome sequencing (WGS) has transformative potential for blood cancer management, but reimbursement is hindered by uncertain benefits relative to added costs. This study employed scenario planning and multi-criteria decision analysis (MCDA) to evaluate stakeholders' preferences for alternative reimbursement pathways, informing future health technology assessment (HTA) submission of WGS in blood cancer.

METHODS

Key factors influencing WGS reimbursement in blood cancers were identified through a literature search. Hypothetical scenarios describing various evidential characteristics of WGS for HTA were developed using the morphological approach. An online survey, incorporating MCDA weights, was designed to gather stakeholder preferences (consumers/patients, clinicians/health professionals, industry representatives, health economists, and HTA committee members) for these scenarios. The survey assessed participants' approval of WGS reimbursement for each scenario, and scenario preferences were determined using the geometric mean method, applying an algorithm to improve reliability and precision by addressing inconsistent responses.

RESULTS

Nineteen participants provided complete survey responses, primarily clinicians or health professionals (n = 6; 32 %), consumers/patients and industry representatives (both at n = 5; 26 %). "Clinical impact of WGS results on patient care" was the most critical criterion (criteria weight of 0.25), followed by "diagnostic accuracy of WGS" (0.21), "cost-effectiveness of WGS" (0.19), "availability of reimbursed treatment after WGS" (0.16), and "eligibility criteria for reimbursed treatment based on actionable WGS results" and "cost comparison of WGS" (both at 0.09). Participants preferred a scenario with substantial clinical evidence, high access to reimbursed targeted treatment, cost-effectiveness below $50,000 per quality-adjusted life year (QALY) gained, and affordability relative to standard molecular tests. Reimbursement was initially opposed until criteria such as equal cost to standard tests and better treatment accessibility were met.

CONCLUSION

Payers commonly emphasize acceptable cost-effectiveness, but strong clinical evidence for many variants and comparable costs to standard tests are likely to drive positive reimbursement decisions for WGS.

The Knowledge and Application of Economics in Healthcare in a High-Income Country Today: The Case of Belgium

Healthcare is a huge business sector in many countries, focusing on the social function of delivering quality health when people develop illness. The system is essentially financed by public funds based on the solidarity principle. With a large financial outlay, the sector must use economic evaluation methods to achieve better efficiency. The objective of our study was to evaluate and to understand how health economics is used today, taking Belgium as an example of a high-income country. The evaluation started with a historical view of healthcare development and ended with potential projections for its future. A literature review focused on country-specific evaluation reports to identify the health economic methods used, with a search for potential gaps. The first results indicated that Belgium in 2021 devoted 11% of its GDP, 17% of its total tax revenue, and 30% of the national Social Security Fund to health-related activities, totalizing EUR 55.5 billion spending. The main health economic method used was a cost-effectiveness analysis linked to budget impact, assigning reimbursable monetary values to new products becoming available. However, these evaluation methods only impacted at most 20% of the money circulating in healthcare. The remaining 80% was subject to financial regulations (70%) and budgeting (10%), which could use many other techniques of an economic analysis. The evaluation indicated two potentially important changes in health economic use in Belgium. One was an increased focus on budgeting with plans, time frames, and quantified treatment objectives on specific disease problems. Economic models with simulations are very supportive in those settings. The other was the application of constrained optimization methods, which may become the new standard of practice when switching from fee-for-service to pay-per-performance as promoted by value-based healthcare and value-based health management. This economic refocusing to a more constrained approach may help to keep the healthcare system sustainable and affordable in the face of the many future challenges including ageing, climate change, migration, pandemics, logistical limitations, and financial instability.

Personalized Timing for Allogeneic Stem-Cell Transplantation in Hematologic Neoplasms: A Target Trial Emulation Approach Using Multistate Modeling and Microsimulation

PURPOSE

Decision about the optimal timing of a treatment procedure in patients with hematologic neoplasms is critical, especially for cellular therapies (most including allogeneic hematopoietic stem-cell transplantation [HSCT]). In the absence of evidence from randomized trials, real-world observational data become beneficial to study the effect of the treatment timing. In this study, a framework to estimate the expected outcome after an intervention in a time-to-event scenario is developed, with the aim of optimizing the timing in a personalized manner.

METHODS

Retrospective real-world data are leveraged to emulate a target trial for treatment timing using multistate modeling and microsimulation. This case study focuses on myelodysplastic syndromes, serving as a prototype for rare cancers characterized by a heterogeneous clinical course and complex genomic background. A cohort of 7,118 patients treated according to conventional available treatments/evidence across Europe and United States is analyzed. The primary clinical objective is to determine the ideal timing for HSCT, the only curative option for these patients.

RESULTS

This analysis enabled us to identify the most appropriate time frames for HSCT on the basis of each patient's unique profile, defined by a combination relevant patients' characteristics.

CONCLUSION

The developed methodology offers a structured framework to address a relevant clinical issue in the field of hematology. It makes several valuable contributions: (1) novel insights into how to develop decision models to identify the most favorable HSCT timing, (2) evidence to inform clinical decisions in a real-world context, and (3) the incorporation of complex information into decision making. This framework can be applied to provide medical insights for clinical issues that cannot be adequately addressed through randomized clinical trials.

Multi-criteria decision analysis method for differential diagnosis of tropical febrile diseases

This paper employs the Analytical Hierarchy Process (AHP) to enhance the accuracy of differential diagnosis for febrile diseases, particularly prevalent in tropical regions where misdiagnosis may have severe consequences. The migration of health workers from developing countries has resulted in frontline health workers (FHWs) using inadequate protocols for the diagnosis of complex health conditions. The study introduces an innovative AHP-based Medical Decision Support System (MDSS) incorporating disease risk factors derived from physicians' experiential knowledge to address this challenge. The system's aggregate diagnostic factor index determines the likelihood of febrile illnesses. Compared to existing literature, AHP models with risk factors demonstrate superior prediction accuracy, closely aligning with physicians' suspected diagnoses. The model's accuracy ranges from 85.4% to 96.9% for various diseases, surpassing physicians' predictions for Lassa, Dengue, and Yellow Fevers. The MDSS is recommended for use by FHWs in communities lacking medical experts, facilitating timely and precise diagnoses, efficient application of diagnostic test kits, and reducing overhead expenses for administrators.

Measuring the overall performance of mental healthcare providers

To date there have been no attempts to construct composite measures of healthcare provider performance which reflect preferences for health and non-health benefits, as well as costs. Health and non-health benefits matter to patients, healthcare providers and the general public. We develop a novel provider performance measurement framework that combines health gain, non-health benefit, and cost and illustrate it with an application to 54 English mental health providers. We apply estimates from a discrete choice experiment eliciting the UK general population's valuation of non-health benefits relative to health gains, to administrative and patient survey data for years 2013-2015 to calculate equivalent health benefit (eHB) for providers. We measure costs as forgone health and quantify the relative performance of providers in terms of equivalent net health benefit (eNHB): the value of the health and non-health benefits minus the forgone benefit equivalent of cost. We compare rankings of providers by eHB, eNHB, and by the rankings produced by the hospital sector regulator. We find that taking account of the non-health benefits in the eNHB measure makes a substantial difference to the evaluation of provider performance. Our study demonstrates that the provider performance evaluation space can be extended beyond measures of health gain and cost, and that this matters for comparison of providers.

Spatial multi-criteria decision analysis for the selection of sentinel regions in tick-borne disease surveillance

BACKGROUND

The implementation of cost-effective surveillance systems is essential for tracking the emerging risk of tick-borne diseases. In Canada, where Lyme disease is a growing public health concern, a national sentinel surveillance network was designed to follow the epidemiological portrait of this tick-borne disease across the country. The surveillance network consists of sentinel regions, with active drag sampling carried out annually in all regions to assess the density of Ixodes spp. ticks and prevalence of various tick-borne pathogens in the tick population. The aim of the present study was to prioritize sentinel regions by integrating different spatial criteria relevant to the surveillance goals.

METHODS

We used spatially-explicit multi-criteria decision analyses (MCDA) to map priority areas for surveillance across Canada, and to evaluate different scenarios using sensitivity analyses. Results were shared with stakeholders to support their decision making for the selection of priority areas to survey during active surveillance activities.

RESULTS

Weights attributed to criteria by decision-makers were overall consistent. Sensitivity analyses showed that the population criterion had the most impact on rankings. Thirty-seven sentinel regions were identified across Canada using this systematic and transparent approach.

CONCLUSION

This novel application of spatial MCDA to surveillance network design favors inclusivity of nationwide partners. We propose that such an approach can support the standardized planning of spatial design of sentinel surveillance not only for vector-borne disease BDs, but more broadly for infectious disease surveillance where spatial design is an important component.

Adding new childhood vaccines to China's National Immunization Program: evidence, benefits, and priorities

China's National Immunization Program has made remarkable achievements but does not include several important childhood vaccines that are readily available in the private market, such as pneumococcal conjugate vaccine (PCV), rotavirus vaccine, Haemophilus influenzae serotype b (Hib) vaccine, and varicella vaccine. We reviewed the literature to assess these four non-National Immunization Program vaccines in terms of their disease burdens, coverage, inequalities, and cost-effectiveness in China and aimed to recommend priorities for introducing them to the National Immunization Program. Based on our calculations using the available evidence, incorporating these vaccines into China's National Immunization Program in 2019 could have averted 11 761 deaths among children younger than 5 years, accounting for 10·29% of the total deaths in children younger than 5 years and reducing the mortality rate from 7·8 per 1000 to 7·0 per 1000. The review showed that 13-valent PCV (PCV13) had the lowest and most inequitable coverage but could prevent the highest number of deaths. In a budgetary analysis for the cohort of newborns in 2023, we estimated that the projected aggregate government costs were US$1954·92 million for PCV13, $1273·13 million for pentavalent rotavirus vaccine, $415·30 million for Hib vaccine, and $221·64 million for varicella vaccine. Our overall multicriteria decision analysis suggested the following priority order for introducing these four non-programme vaccines to the National Immunization Program to benefit the Chinese population: PCV13, rotavirus vaccine, Hib vaccine, and varicella vaccine.

Value of concerted and hospital hemodialysis through a multi-criteria decision analysis

OBJECTIVE

To evaluate the value of the provision of contracted versus hospital dialysis services for the treatment of chronic kidney disease in Spain using the multicriteria decision analysis methodology.

METHOD

The EVIDEM (Evidence and Value: Impact on Decision Making) evaluation framework was used to calculate the estimated value of both dialysis delivery models (arranged vs. hospital) through a virtual workshop in which different profiles participated: directors and managers, professionals and heads of units and representatives of patients and relatives. The scores were combined using an additive lineal model, which combined the weight of the model with the individual score of the criteria, and each value was transformed to a scale between 0 and 1.

RESULTS

The estimated value for arranged dialysis was 0.29 (DS: ±0.2) and 0.39 (DS: ±0.2) for hospital dialysis. All profiles gave a higher value to hospital hemodialysis compared to contracted hemodialysis. The highest value for hospital dialysis was for patients (0.44), with the lowest mean value for directors (0.36) and the range for arranged dialysis being between patients (0.31) and intermediate positions (0.27).

CONCLUSIONS

Hospital hemodialysis obtained a higher value than concerted dialysis. In general, the panelists affirmed that it is a useful and interesting exercise and that, to a certain extent, it provides security in decision-making, since it allows ordering, rationalizing and considering, in an explicit and transparent manner, the different criteria involved.

A data-driven approach to optimizing clinical study eligibility criteria

OBJECTIVE

Feasible, safe, and inclusive eligibility criteria are crucial to successful clinical research recruitment. Existing expert-centered methods for eligibility criteria selection may not be representative of real-world populations. This paper presents a novel model called OPTEC (OPTimal Eligibility Criteria) based on the Multiple Attribute Decision Making method boosted by an efficient greedy algorithm.

METHODS

It systematically identifies the optimal criteria combination for a given medical condition with the optimal tradeoff among feasibility, patient safety, and cohort diversity. The model offers flexibility in attribute configurations and generalizability to various clinical domains. The model was evaluated on two clinical domains (i.e., Alzheimer's disease and Neoplasm of pancreas) using two datasets (i.e., MIMIC-III dataset and NewYork-Presbyterian/Columbia University Irving Medical Center (NYP/CUIMC) database).

RESULTS

We simulated the process of automatically optimizing eligibility criteria according to user-specified prioritization preferences and generated recommendations based on the top-ranked criteria combination accordingly (top 0.41-2.75%) with OPTEC. Harnessing the power of the model, we designed an interactive criteria recommendation system and conducted a case study with an experienced clinical researcher using the think-aloud protocol.

CONCLUSIONS

The results demonstrated that OPTEC could be used to recommend feasible eligibility criteria combinations, and to provide actionable recommendations for clinical study designers to construct a feasible, safe, and diverse cohort definition during early study design.

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.

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.

Efficacy and safety of pharmacological interventions for managing sickle cell disease complications in children and adolescents: Systematic review with network meta-analysis

This study aimed to synthesize the evidence on the effects of disease-modifying agents for managing sickle cell disease (SCD) in children and adolescents by means of a systematic review with network meta-analyses, surface under the cumulative ranking curve (SUCRA) and stochastic multicriteria acceptability analyses (SMAA) (CRD42022328471). Eightteen randomized controlled trials (hydroxyurea [n = 7], l-arginine [n = 3], antiplatelets [n = 2], immunotherapy/monoclonal antibodies [n = 2], sulfates [n = 2], docosahexaenoic acid [n = 1], niprisan [n = 1]) were analyzed. SUCRA and SMAA demonstrated that hydroxyurea at higher doses (30 mg/kg/day) or at fixed doses (20 mg/kg/day) and immunotherapy/monoclonal antibodies are more effective for preventing vaso-occlusive crisis (i.e., lower probabilities of incidence of this event; 14, 25, and 30%, respectively), acute chest syndrome (probabilities ranging from 8 to 30%), and needing of transfusions (11-31%), while l-arginine (100-200 mg/kg) and placebo were more prone to these events. Therapies were overall considered safe; however, antiplatelets and sulfates may lead to more severe adverse events. Although the evidence was graded as insufficient and weak, hydroxyurea remains the standard of care for this population, especially if a maximum tolerated dose schedule is considered.

Smoking Bans and Circulatory System Disease Mortality Reduction in Macao (China): Using GRA Models

This study evaluates the association between smoking rates and mortality from circulatory system diseases (CSD) after implementing a series of smoking bans in Macao (China). (1) Background: Macao phased in strict total smoking bans since 2012. During the past decade, smoking rates among Macao women have dropped by half. CSD mortalities in Macao also show a declining trend. (2) Method: Grey relational analysis (GRA) models were adopted to rank the importance of some key factors, such as income per capita, physician density, and smoking rates. Additionally, regressions were performed with the bootstrapping method. (3) Results: Overall, smoking rate was ranked as the most important factor affecting CSD mortality among the Macao population. It consistently remains the primary factor among Macao's female population. Each year, on average 5 CSD-caused deaths were avoided among every 100,000 women, equivalent to about 11.45% of the mean annual CSD mortality. (4) Conclusions: After the implementation of smoking bans in Macao, the decrease in smoking rate among women plays a primary role in the reduction in CSD mortality. To avoid excess CSD mortality due to smoking, Macao needs to continue to promote smoking cessation among the male population.

Multi-criteria decision-making methods applied in health-insurance underwriting

This study attempts to structure methodologically the health insurance underwriting process by applying Multi-criteria Decision-making (MCDM) analysis in health insurance underwriting. This is done by assigning a score to each health insurance applicant which can be used to determine whether he or she is accepted, rejected or accepted with special terms and conditions (such as exclusions, additional waiting periods and/ or surcharge). The introduction of MCDM approaches in health insurance underwriting enables the quantification of the selection criteria, the increased standardization and automation of the process and its alignment through quantitative indicators with the risk tolerance/ risk appetite of the insurer, and there lie the novelties of this research. The proposed methodology can be readily implemented by insurers with added value in the underwriting, risk management and distribution (sales & marketing) functions, as well as in the profitability of the company or the level of premium paid by the insured.

Classification of medicines and materials in hospital inventory management: a multi-criteria analysis

BACKGROUND

In the hospital environment, to achieve an optimum level of operations and service, it is necessary to develop adequate inventory management system. Stocks can be managed, amongst other ways, through inputs classification, which is generally carried out based on a single criterion, such as monetary value, demand or criticality, which does not fully address the complexity of a hospital's inventory management system. Thus, the present study proposes a multi-criteria decision support model to help classify the stock of medicines and materials, enabling a more effective inventory management system for hospitals.

METHODS

Methodologically, the study followed 3 stages: (1) preliminary phase; (2) modelling and choice phase; and (3) finalization phase. Each stage had a set of specific steps that were followed. The first stage identified the actors of the process, objectives, criteria and alternatives, establishing 5 criteria and 48 alternatives; the second stage was the choice and execution of the multi-criteria decision method to solve the problem. It was decided to use the Flexible and Interactive Tradeoff method for the sorting problematic. Finally, in the third stage, the sensitivity analysis for the developed model and the validation of the results with decision makers were carried out. In the study, 48 medicines and materials were included to validate the proposed model; however, the model could be used for more items.

RESULTS

From the total of 48 medicines and hospital medical materials selected for the study, the classification of 34 of these alternatives to a single class was obtained through modelling and the other 14 alternatives were destined to two possible classes; moreover, the sensitivity analysis performed showed robust results. The items classified in class W should receive special attention by the stock manager; therefore, they should be monitored weekly. Items classified in class B should be monitored biweekly and finally, items classified in class M, should be monitored monthly.

CONCLUSIONS

The classification of medicines and materials developed according to the inventory demands allowed more efficient purchasing decisions, optimizing the stock of materials and medicines at the hospital while optimizing the inventory manager's activities, saving time. Consequently, the proposed model can support the development of other multicriteria models in different hospital scenarios.

A multicriteria decision analysis (MCDA) tool to purchase implantable medical devices in Egypt

Background

With the availability of several similar medical devices performing the same function, choosing one for reimbursement is not easy, especially if purchased for a large number of patients. The objective of this project was to create a multicriteria decision analysis (MCDA) tool, that captures and compares all implantable medical devices’ attributes, to provide an objective method for choosing among the available options in Egypt.

Method

We conducted a systematic review and expert interviews, to identify the relevant criteria for inclusion in the tool. Subsequently, a workshop was conducted, that involved experts in procuring and tendering medical devices. Experts chose the criteria, ranked them, assigned weights and scoring functions for each criterion, and then created the draft tool. A pilot phase followed; then, another workshop was conducted to fine-tune the tool. We readjusted the tool based on experts’ experience with the draft tool.

Results

The final tool included eight criteria, arranged according to their weightage: technical characteristics (29.4%), country of origin (19.5%), use in reference countries (14.9%), supply reliability (11.7%), previous use in tenders (9.0%), instant replacement within product variety (6.9%), pharmacovigilance (4.6%), and refund or replacement (4.0%). Each medical device was assessed on these eight criteria to achieve a final score, that was compared to the alternative devices’ scores. Price is not included in the MCDA tool, but it will be added in the financial evaluation phase.

Conclusion

Decisionmakers could use the MCDA tool, to make evidence-based and objective decisions for purchasing implantable devices, in the Egyptian public sector. Post price evaluation, the product with the best value will be chosen for reimbursement.

Highlights

We created an MCDA tool to help decision makers choose between alternative implantable medical devices in Egypt.

The MCDA tool includes eight criteria, where price is evaluated as a separate step.

“Technical characteristics” and “country of origin” criteria carried the highest weights, thus representing approximately 50% of the decision.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-022-02025-y.

Particulate air pollution and metabolic risk factors: Which are more prone to cardiac mortality

This study explored multiplex, country-level connections between a wide range of cardiac risk factors and associated mortality within the South Asian Association for Regional Cooperation (SAARC) countries. The grey relational analysis (GRA) methodology is used to evaluate data from 2001 to 2018 to compute scores and rank countries based on cardiac mortality. Subsequently, we used the conservative (Min-Max) technique to determine which South Asian country contributes the most to cardiac mortality. The Hurwicz criterion is further applied for optimization by highlighting the risk factors with the highest impact on cardiac mortality. Empirical findings revealed that India and Nepal are the leading drivers of cardiovascular disease (CVD) mortality among all SAARC nations based on the results of the GRA methodology. Moreover, the outcomes based on the Hurwicz criterion and the conservative criterion indicated that CVD mortality is considerably impacted by household air pollution from the combustion of solid fuel, with India as a potential contributor in the SAARC region. The outcomes of this research may enable international organizations and public health policymakers to make better decisions and investments within the SAARC region to minimize the burden of CVD while also strengthening environmentally sustainable healthcare practices.

Knowledge Mapping of Multicriteria Decision Analysis in Healthcare: A Bibliometric Analysis

Objective

Multicriteria decision analysis (MCDA) is a useful tool in complex decision-making situations, and has been used in medical fields to evaluate treatment options and drug selection. This study aims to provide valuable insights into MCDA in healthcare through examining the research focus of existing studies, major fields, major applications, most productive authors and countries, and most common journals in the domain.

Methods

A bibliometric analysis was conducted on the publication related to MCDA in healthcare from the Web of Science Core Collection (WoSCC) database on 14 July 2021. Three bibliometric software (VOSviewer, R-bibliometrix, and CiteSpace) were used to conduct the analysis including years, countries, institutes, authors, journals, co-citation references, and keywords.

Results

A total of 410 publications were identified with an average yearly growth rate of 32% (1999-2021), from 196 academic journals with 23,637 co-citation references by 871 institutions from 70 countries/regions. The United States was the most productive country (n = 80). Universiti Pendidikan Sultan Idris (n = 16), Université de Montréal (n = 13), and Syreon Research Institute (n = 12) were the top productive institutions. A A Zaidan, Mireille Goetghebeur and Zoltan Kalo were the biggest nodes in every cluster of authors' networks. The top journals in terms of the number of articles (n = 17) and citations (n = 1,673) were Value in Health and Journal of Medical Systems, respectively. The extant literature has focused on four aspects, including the analytic hierarchy process (AHP), decision-making, health technology assessment, and healthcare waste management. COVID-19 and fuzzy TOPSIS received careful attention from MCDA applications recently. MCDA in big data, telemedicine, TOPSIS, and fuzzy AHP is well-developed and an important theme, which may be the trend in future research.

Conclusion

This study uncovers a holistic picture of the performance of MCDA-related literature published in healthcare. MCDA has a broad application on different topics and would be helpful for practitioners, researchers, and decision-makers working in healthcare to advance the wheel of medical complex decision-making. It can be argued that the door is still open for improving the role of MCDA in healthcare, whether in its methodology (e.g., fuzzy TOPSIS) or application (e.g., telemedicine).

Supporting rehabilitation stakeholders in making service delivery decisions: a rapid review of multi-criteria decision analysis methods

PURPOSE

This review aimed to synthesize knowledge about multi-criteria decision analysis methods for supporting rehabilitation service design and delivery decisions, including: (1) describing the use of these methods within rehabilitation, (2) identifying decision types that can be supported by these methods, (3) describing client and family involvement, and (4) identifying implementation considerations.

METHODS

We conducted a rapid review in collaboration with a knowledge partner, searching four databases for peer-reviewed articles reporting primary research. We extracted relevant data from included studies and synthesized it descriptively and with conventional content analysis.

RESULTS

We identified 717 records, of which 54 met inclusion criteria. Multi-criteria decision analysis methods were primarily used to understand the strength of clients' and clinicians' preferences (n = 44), and five focused on supporting decision making. Shared decision making with stakeholders was evident in only two studies. Clients and families were mostly engaged in data collection and sometimes in selecting the relevant criteria. Good practices for supporting external validity were inconsistently reported. Implementation considerations included managing cognitive complexity and offering authentic choices.

CONCLUSIONS

Multi-criteria decision analysis methods are promising for better understanding client and family preferences and priorities across rehabilitation professions, contexts, and caseloads. Further work is required to use these methods in shared decision making, for which increased use of qualitative methods and stakeholder engagement is recommended. IMPLICATIONS FOR REHABILITATIONMulti-criteria decision analysis methods are promising for evidence-based, shared decision making for rehabilitation.However, most studies to date have focused on estimating stakeholder preferences, not supporting shared decision making.Cognitive complexity and modelling authentic and realistic decision choices are major barriers to implementation.Stakeholder-engagement and qualitative methods are recommended to address these barriers.

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.

A Rapid Literature Review of Multi-Criteria Decision Support Methods in the Context of One Health for All-Hazards Threat Prioritization

Background

Multi-Criteria Decision Analysis (MCDA) is a decision support tool that can be used in public health emergency management. The use of a One Health lens in MCDA can support the prioritization of threats and interventions which cut across the human, animal, and environmental domains. Previous literature reviews have focused on creating a snapshot of MCDA methodological trends. Our study provides an update to the MCDA methods literature with key considerations from a One Health perspective and addresses the application of MCDA in an all-hazards decision-making context.

Methods

We conducted a literature search on MEDLINE, EMBASE, SCOPUS, the CAB database, and a limited online gray literature search in partnership with a librarian from Health Canada. Articles were limited to those published in the year 2010 or later in a high-income setting (OECD member countries).

Results

Sixty-two articles were included for synthesis. Of these articles, most were Canadian studies (20%); and prioritized health risks, threats, and interventions in the human domain (69%). Six commonly used prioritization criteria were identified: threat, health, intervention, strategic, social, and economic impact. Stakeholders were engaged in 85% of studies and commonly consisted of government groups, non-governmental groups, subject matter experts, and the public. While most articles (65%) included elements of One Health based on our definition, only 5 studies (9%) explicitly acknowledged One Health as a guiding principle for the study. Forty seven percentage of studies noted that MCDA was beneficial in supporting the decision-making process.

Conclusion

Current literature on health prioritization presents some variability in the depth of integration of the One Health framework and on the use of various MCDA methodologies given prioritization objectives. Studies which applied a comprehensive One Health approach, prioritized disparate threats, or conducted cyclical prioritizations for governing bodies were broad in scope, but sparse. The results of our review indicate the need for better guidance on the integration of a One Health approach and the use of various MCDA methods given the main prioritization objectives.

Priorities in the Prevention Strategies for Medication Error Using the Analytical Hierarchy Process Method

As medication error is inherently "preventable", we should try to minimize errors to improve patient safety and quality of care. The aim of this study was to prioritize strategies to prevent medication errors using the analytic hierarchy process (AHP) method. The hierarchy structure consisted of three stages: goal of the decision, decision criteria, and alternatives. Ten experts of patient safety research or clinical pharmacology compared each pair of criteria and alternatives and assigned a nine-point numerical scale. We used the eigenvector method to aggregate the pairwise comparisons obtained from experts and to estimate the weights of each criterion and alternative. Among the decision criteria, system improvement in reporting was the most preferred criterion, followed by cultural improvement and system improvement in the counterplan. The preferred alternative was a counterplan by healthcare institutions, followed by a change from a blame culture to safety culture and the building of a reporting system. A sensitivity analysis indicated that priorities were generally robust in the methods used for calculating the integrated matrices. We have suggested the priority of preventive strategies against medication errors using the AHP method. The prioritization of preventive strategies could help policymakers understand current needs and therefore develop evidence-based policies on patient safety.

A multi-criteria decision analysis (MCDA) tool for purchasing off-patent oncology medicines in Egypt

Background

Multi- criteria decision analysis (MCDA) can assist policymakers in objectively choosing between alternative therapeutic options based on multiple value attributes. Our aim was to create an MCDA tool for the national tenders of off-patent oncology medicines in Egypt.

Methods

An initial list of criteria was developed through a literature review complemented by local expert interviews. Price or cost-related criteria were excluded to abide by the national regulations of the tender process. Next, a workshop hosting diversified stakeholders representing different governmental bodies was held. Anonymous voting was used to rank and weigh the criteria as well as assigning scores. Price was added as a separate step to identify best option based on price per point. The tool was then tested on a national tender sample of off-patent oncology medicines to assess its performance, and it was readjusted accordingly in a second workshop.

Results

Seven non-price criteria were selected, including use in reference countries (23.49% weight), equivalence with the reference product (18.79%), manufacturing quality (15.53%), provision of pharmacovigilance services (12.94%), supply reliability (10.78%), previous use in local settings (9.8%) and macroeconomic benefit (8.67%).

A medicine receives a score ranging from 0 to 100% of each criterion’s weight. The aggregated score is calculated on a hundred-point scale. Based on participants’ consensus, an overall score of 65 was set as a cut-off for passing the technical eligibility phase of the tendering process. Any product receiving a lower score would be disqualified from the tender. For qualified products, the lower price per point represents preferential option for the national tender.

Conclusions

The created MCDA tool is capable of objectively comparing similar off-patent oncology medicines by considering multiple value attributes and providing reliable scoring functions for each.

Prioritisation of Provinces for African Swine Fever Intervention in South Africa through Decision Matrix Analysis

South Africa has experienced an increase in the number of African swine fever (ASF) outbreaks in domestic pigs in the last ten years. Intervention will be needed in the form of control and prevention strategies to minimise the impact of this disease in the country. The aim of this study is to prioritise which provinces resources should be allocated to for ASF intervention strategies, based on the risk factors identified as pertinent in South Africa. A multi-criteria decision analysis approach was followed using an analytic hierarchy process (AHP) method to determine the perceived risk of ASF outbreaks in domestic pigs per province. Nine risk factors applicable to the South African context were identified from literature. Data on the presence of these risk factors per province were collected from records and by means of a questionnaire. The risk factors were weighted by means of an AHP. The decision matrix determined that ASF intervention and prevention resources should be focused on Mpumalanga, Free State and Gauteng provinces in South Africa. Specific intervention strategies should be focused on the confinement of pigs, swill-feeding of pigs and buying/selling of pigs at auctions through a participatory approach with stakeholders.

Application of the QFD-fuzzy-SERVQUAL methodology as a quality planning tool at the surgical centre of a public teaching hospital

BACKGROUND

In Brazil, many public hospitals face constant problems related to high demand vis-à-vis an overall scarcity of resources, which hinders the operations of different sectors such as the surgical centre, as it is considered one of the most relevant pillars for the proper hospital functioning, due to its complexity, criticality as well as economic and social importance. Proper asset management based on well-founded decisions is, therefore, a sine-qua-non condition for addressing such demands. However, subjectivity and other difficulties present in decisions make the management of hospital resources a constant challenge.

METHODS

Thus, the present work proposes the application of a hybrid approach, formed by the QFD tools, fuzzy logic and SERVQUAL as a decision support tool for the quality planning of the surgical centre of the Onofre Lopes Teaching Hospital (Hospital Universitário Onofre Lopes-HUOL). To accomplish such objective, it was necessary to discover and analyse the main needs of the medical team working in the operating room, through the application of the SERVQUAL questionnaire, associated with fuzzy logic.

RESULTS

Then, the most relevant deficiencies were transformed into entries for the QFD-fuzzy, where they were translated into project requirements. Soon after, the analysis of the existing relationships between the inputs and these requirements was carried out, generating the ranking of actions with the greatest impact on the improvement of the surgical centre overall quality.

CONCLUSIONS

As a result, it was found that the proposed methodology can optimize the decision process to which hospital managers are submitted, improving the surgical centre operation efficiency.

Smart Environments and Techno-centric and Human-Centric Innovations for Industry and Society 5.0: A Quintuple Helix Innovation System View Towards Smart, Sustainable, and Inclusive Solutions

The paper investigates the aviation sector, as a case in point for a Smart environment and as an example for Industry 5.0 and Society 5.0 purposes. In the smart complex environments, a systemic vision of the elements, which act and are acted within a given territory, should be the basis of a hypothesis of joint growth. Indeed, the synergies activated by the system can be seen as the product of the application of a particular knowledge-based open innovation strategy, as an orientation capable of transforming theoretical assumptions into concrete operational innovation paths. Through the evidence emerged from an important case study and the application of an MCDA methodology, we have tried to identify which are the optimal solutions for the implementation of the new human-centric logics of I5.0, analyzing them on the basis of the actual benefits for the ecosystem, going beyond the self-referential aptitude of the firm to instill technological changes and managerial visions. Knowledge circulation, dialogue between sub-systems, and the ability to adapt technology and entrepreneurial strategies to the environment in which it operates (with the users as first stakeholders) seem to be necessary practices in knowledge-based innovation, prioritization, and decision-making processes, for smart, sustainable, and inclusive solutions.

Socioeconomic Influence on Cardiac Mortality in the South Asian Region: New Perspectives from Grey Modeling and G-TOPSIS

Background

Measuring the potential socioeconomic factors of cardiac mortality is fundamental to identifying treatments, setting priorities, and effectively allocating resources to minimize disease burden. The study sought to present a methodology that explores the connections between urbanization, population growth, human development index (HDI), access to energy, unemployment, and cardiovascular disease (CVD) mortality within the South Asian Association for Regional Cooperation (SAARC) nations to mitigate the cardiac disease burden.

Methods

This investigation uses multiple-criteria decision-making methodologies to analyze data between 2001 and 2017 commencing with a mathematical grey incidence analysis (GIA) methodology to estimate weights and rank nations based on CVD mortality. Then, utilizing the conservative min-max model approach, we sought to determine which country contributes the most to CVD mortality among all South Asian nations. The grey preference by similarity to ideal solution (G-TOPSIS) method is adopted for further optimization by prioritizing the selected factors that have the greatest influence on CVD mortality.

Results

The estimated statistic highlights that, among SAARC nations, Pakistan has a significant proportion of the disease burden attributable to cardiac events. In addition, HDI showed a significant contribution in the reduction of CVD mortality, whereas unemployment showed a significant contribution in the rise of CVD mortality among all selected variables.

Conclusions

This investigation may facilitate researchers with a multiple-criteria decision-making roadmap to help them enhance the quality of their studies and their understanding of how to use multiple-criteria decision-making techniques to evaluate and prioritize the influencing factors of disease mortality in healthcare research. Further, the study outcomes provide additional practical knowledge for appropriate policy solutions.

Optimisation of maintenance in delivery systems for cytostatic medicines

BACKGROUND

The real-world application of maintenance in organisations brings together a number of maintenance policies in order to achieve the desired availability, efficiency and profitability. However, the literature mostly chooses a single maintenance policy, and so the decision process is not suited to the real conditions in the company to which it is applied. Our study takes a combination of maintenance policies as alternatives, and so conforms to the actual practice of maintenance in organisations. Furthermore, it introduces the possibility of including extra spare parts, or outsourcing maintenance policies. Although the selection of maintenance policies has been applied to many kinds of business and of machine, there is almost no instance of its application to hospitals, and it has never been applied to delivery systems for cytostatic drugs.

METHODS

The model uses the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), which is recognised as being highly suitable for solving group decision-making problems in a fuzzy environment. Fuzzy set theory is also considered to be more proficient than crisp numbers for handling the ambiguity, imprecisions, data scarcity, and uncertainty inherent in decisions made by human beings. The judgements required were obtained from a decision group comprising the heads of facilities maintenance, maintenance of medical equipment, health and safety at work, environment, and programming-admission. The group also included care staff; specifically, the heads of the main clinical services, and the medical supervisors. The model includes original criteria, such as Quality of health care, which measures impact on care as a function of mean availability of each alternative. It also considers Impact on hospital management via the criteria: Working environment in the organisation and Impact on health care; the former criterion measures equality among care services in the hospital, while the latter assesses the effect on regional health cover. The model was built using real data obtained from a state hospital in Spain. The model can also be easily applied to other national and international healthcare organisations, providing weights specific to the criteria. These are produced by a decision group from each healthcare organisation and the alternatives are updated in accordance with what is considered important in each hospital.

RESULTS

The results obtained from the model recommend changing the alternative that is currently in use, Corrective and Preventive Maintenance, to Corrective and Preventive Maintenance plus two spare hoods. This alternative would lead to an availability of 1 (the highest possible) in the systems for preparing personalised cytotoxic drugs, and so the quality of service is therefore very high. Additionally, it could offer services to all the users of the hospital, and also offer cover in the preparation of cytotoxic medicines to other hospitals in the catchment area.

CONCLUSIONS

The results suggest the possibility that improvements to the support and logistical systems, which include maintenance, traditionally held to have no effect on quality of care, may be key to improving care quality, but also in reducing risk to patients, care and non-care staff, and the environment.

Bedside Evaluation of Early VAS/NRS Based Protocols for Intravenous Morphine in the Emergency Department: Reasons for Poor Follow-Up and Targeted Practices

Intravenous (IV) morphine protocols based on patient-reported scores, immediately at triage, are recommended for severe pain in Emergency Departments. However, a low follow-up is observed. Scarce data are available regarding bedside organization and pain etiologies to explain this phenomenon. The objective was the real-time observation of motivations and operational barriers leading to morphine avoidance. In a single French hospital, 164 adults with severe pain at triage were included in a cross-sectional study of the prevalence of IV morphine titration; caregivers were interviewed by real-time questionnaires on “real” reasons for protocol avoidance or failure. IV morphine prevalence was 6.1%, prescription avoidance was mainly linked to “Pain reassessment” (61.0%) and/or “alternative treatment prioritization” (49.3%). To further evaluate the organizational impact on prescription decisions, a parallel assessment of “simulated” prescription conditions was simultaneously performed for 98/164 patients; there were 18 titration decisions (18.3%). Treatment prioritization was a decision driver in the same proportion, while non-eligibility for morphine was more frequently cited (40.6% p = 0.001), with higher concerns about pain etiologies. Anticipation of organizational constraints cannot be excluded. In conclusion, IV morphine prescription is rarely based on first pain scores. Triage assessment is used for screening by bedside physicians, who prefer targeted practices to automatic protocols.

Clinical decision-making for shoulder surgery referral: An art or a science?

RATIONALE

Decision-making in musculoskeletal health care is complex, with discrepancy among clinical providers and variation in the per cent of referrals for specialist care. To date, there is an increased focus on specialist referrals, risking overuse of expensive testing and contributing to unnecessary treatment.

AIMS AND OBJECTIVES

This report will considerer the difficulties of primary care musculoskeletal decision-making using shoulder injuries as an example, presenting a solution based on multi-criteria decision-making analysis with online software. The associated issues involved in clinical decision-making are complex. Contributing to the components of complexity are; the multifaceted aetiology of shoulders, the experience and knowledge of providers, and the burden of patient demands. Notwithstanding, funding considerations, resource allocation availability and other associated issues around clinical decision-making. Considering the many facets and complexities of clinical decision-making, this is an area where multi-criteria decision-making analysis (MCDM) may be appropriate. The MCDM analysis approach is increasingly being used in health care and can assist in the organizing and weighting of identified key clinical factors. MCDM could be applied to the challenges of musculoskeletal care with the potential to decrease decision-making variability. Furthermore, the significance of each key clinical factor that musculoskeletal decision-making is based on are to date unclear.

CONCLUSION

Therefore, this preliminary report offers a start towards clarifying key factors and an approach for implementing improved shoulder clinical care decision-making which could then be adapted and applied to other body sites.

Evaluation of criteria and COVID-19 patients for intensive care unit admission in the era of pandemic: A multi-criteria decision making approach

BACKGROUND AND OBJECTIVE

The COVID-19 pandemic results in an intense flow of patients to hospitals especially to the intensive care units (ICUs) to be treated. The ICUs will therefore be confronted with a massive influx of patients (e.g. Spain and Italy). However, if the number of patients is higher than the resources available in ICUs, rationing decisions such as determining and evaluating the criteria for ICU admission becomes essential. In this case, the decision of which patients will be admitted to the ICUs may put significant pressure on healthcare personnel. The goal of this paper is to determine the criteria to be used in the decision of admission of COVID-19 patients to the ICUs.

METHODS

A three-step methodology is applied. In the first step, the evaluation criteria are determined, and then the criteria are prioritized using a fuzzy analytical hierarchy process (AHP) in an uncertain and multiple-criteria environment choice. Finally, COVID-19 patients are ranked using the Multi-Objective Optimization Method by Ratio Analysis to find out which patient is more urgent.

RESULTS

According to experts' evaluation of ICU admission criteria, "increment of >2 in SOFA score" seems the most dominant factor among others. The proposed methodology is tested on 10 anonymous COVID-19 positive patients being treated in a public hospital and the ICU admission results are discussed.

CONCLUSIONS

Obtained priorities and ranking is in line with the hospitals' behavior that potentially depicts the usefulness and validity of the proposed approach.

The Inflection Point Model: a Model to Explore the Hidden Burdens of Non-Cancerous Genitourinary Conditions

OBJECTIVE

To propose a conceptual model to identify points along the condition course where actions or inaction affect downstream burdens of non-cancerous genitourinary conditions (NCGUC).

MATERIALS AND METHODS

The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) convened an interdisciplinary meeting to comprehensively consider the burdens of NCGUCs. Subsequently, the authors met monthly to conceptualize the model.

RESULTS

Inflection points (IP) describe time points during a condition course that are sensitive to change. Our proposed Inflection Point Model (IPM) helps conceptualize burden/benefit trade-offs in any related decision and provides a platform to identify the downstream aggregate burden of a NCGUC across multiple socio-ecological levels at a single time point, which may be summed across the condition course to measure cumulative burden. Two personae demonstrate the utility of this model to better understand impacts of two common NCGUCs.

CONCLUSIONS

The IPM may be applied in multiple contexts: narrowly to explore burden of a single NCGUC at a single IP; or more broadly, to address multiple conditions, multiple IPs, or multiple domains/levels of social ecology. Applying the IPM may entail combining population data describing prevalence of NCGUCs, associated behaviors, and resulting outcome patterns that can be combined with suitable mathematical models to quantify aggregate and cumulative burden. The IPM challenges stakeholders to expand from the individual to include broader levels of social ecology. Application of the IPM will undoubtedly identify data gaps and research needs that must be fulfilled to delineate and address the burden of NCGUCs.

Cost analysis and critical success factors of the use of oxygen concentrators versus cylinders in sub-divisional hospitals in Fiji

Background

Oxygen is vital in the treatment of illnesses in children and adults, yet is lacking in many low and middle-income countries health care settings. Oxygen concentrators (OCs) can increase access to oxygen, compared to conventional oxygen cylinders. We investigated the costs and critical success factors of OCs in three hospitals in Fiji, and extrapolated these to estimate the oxygen delivery cost to all Sub-Divisional hospitals (SDH) nationwide.

Methods

Data sources included key personnel interviews, and data from SDH records, Ministry of Health and Medical Services, and a non-governmental organisation. We used Investment Logic Mapping (ILM) to define key issues. An economic case was developed to identify the investment option that optimised value while incorporating critical success factors identified through ILM. A fit-for-purpose analysis was conducted using cost analysis of four short-listed options. Sensitivity analyses were performed by altering variables to show the best or worst case scenario. All costs are presented in Fijian dollars.

Results

Critical success factors identifed included oxygen availability, safety, ease of use, feasibility, and affordability. Compared to the status quo of having only oxygen cylinders, an option of having a minimum number of concentrators with cylinder backup would cost $434,032 (range: $327,940 to $506,920) over 5 years which would be 55% (range: 41 to 64%) of the status quo cost.

Conclusion

Introducing OCs into all SDHs in Fiji would reduce overall costs, while ensuring identified critical success factors are maintained. This study provides evidence for the benefits of OCs in this and similar settings.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06687-8.

Proposal for capturing patient experience through extended value frameworks of health technologies

BACKGROUND: Inclusion of patient experience (PEx) in health technology assessment (HTA) has become increasingly important; however, no harmonized approach exists to help manufacturers or decision makers ensure PEx considerations are fair, consistent, and thorough within global HTA frameworks. OBJECTIVE: To develop a proposal for including PEx in the HTA frameworks of health technologies. METHODS: A systematic literature review (SLR) on existing value frameworks (VFs) was conducted to capture how PEx-related value judgment is currently considered. Guided by the results of the SLR, a research group including HTA experts and patient representatives used an iterative process to develop potential value domains to capture PEx, in accordance with international guidelines. Subsequently, a panel of international payer experts was used to challenge the proposed PEx domains and provide recommendations for implementation. RESULTS: The SLR found 61 VFs and multi-criteria decision analyses (MCDAs) that considered PEx; however, PEx-related value elements were often referred to superficially, without clear definitions. Five potential PEx domains, with proposed measures for each, were developed and refined using expert feedback: (1) responsiveness to patient's individual needs, (2) improved health literacy and empowerment, (3) patient and caregiver reported outcomes, (4) household's financial burden, and (5) improved access for vulnerable patient populations. A flexible approach for framework implementation was proposed. CONCLUSIONS: Proposed PEx domains could be implemented at multiple levels of healthcare decision making to formalize consideration of PEx in the assessment of value, either through the extension of existing VFs or to create new PEx-focused VFs and more holistic decision making tools. DISCLOSURES: This study was funded and sponsored by UCB Pharma. The funding agreement ensured the authors' independence in designing the study, interpreting the data, writing, and publishing the report. Charokopou, Mountain, and Szegvari are employed by UCB Pharma. Inotai, Jakab, and Kalo are employed by Syreon Research Institute, which received funding from UCB Pharma for this research. Brixner has received fees from AbbVie, Elevar, Millcreek Outcomes Group, Novartis, Sanofi, UCB Pharma, and Xcenda. Campbell has received grants and contracts from the PhRMA Foundation and the Institute for Clinical and Economic Review. During a sabbatical leave, Campbell collaborated with Syreon Research Institute on research projects that included funding from UCB Pharma. Hawkins has received consultancy fees from UCB Pharma. Kristensen has received speakers bureau fees from Pfizer, AbbVie, Amgen, UCB Pharma, Celgene, Bristol-Myers Squibb, MSD, Novartis, Eli Lilly, and Janssen Pharmaceuticals and consultancy fees from UCB Pharma.

The Application of Multicriteria Decision Analysis Methods in Health Care: A Literature Review

OBJECTIVES

The main objectives of this article are 2-fold. First, we explore the application of multicriteria decision analysis (MCDA) methods in different areas of health care, particularly the adoption of various MCDA methods across health care decision making problems. Second, we report on the publication trends on the application of MCDA methods in health care.

METHOD

PubMed was searched for literature from 1960 to 2019 in the English language. A wide range of keywords was used to retrieve relevant studies. The literature search was performed in September 2019. Articles were included only if they have reported an MCDA case in health care.

RESULTS AND CONCLUSION

The search yielded 8,318 abstracts, of which 158 fulfilled the inclusion criteria and were considered for further analysis. Hybrid methods are the most widely used methods in health care decision making problems. When it comes to single methods, analytic hierarchy process (AHP) is the most widely used method followed by TOPSIS (technique for order preference by similarity to ideal solution), multiattribute utility theory, goal programming, EVIDEM (evidence and value: impact on decision making), evidential reasoning, discrete choice experiment, and so on. Interestingly, the usage of hybrid methods has been high in recent years. AHP is most widely applied in screening and diagnosing and followed by treatment, medical devices, resource allocation, and so on. Furthermore, treatment, screening and diagnosing, medical devices, and drug development and assessment got more attention in the MCDA context. It is indicated that the application of MCDA methods to health care decision making problem is determined by the nature and complexity of the health care problem. However, guidelines and tools exist that assist in the selection of an MCDA method.

Meta-Decision in Healthcare

Meta-decision as a junction between evidence and its rightful implementation is suggested in this review as a structured framework applied in healthcare, valuable to clinicians and healthcare decision-makers. The process of meta-decision requires optimum measurements to provide data necessary for identifying and developing decision alternatives and explicitly reflect on its value and choose the optimum decision. The location of value in the meta-decision framework is core component. Of equal importance are prerequisites for decision-makers' abilities to make meta-decisions and focus on optimum team environments. As well as improving their decision-making process through reflection and learning.

Priority setting in the Brazilian emergency medical service: a multi-criteria decision analysis (MCDA)

BACKGROUND

Despite the proven value of multicriteria decision analysis in the health field, there is a lack of studies focused on prioritising victims in the Emergency Medical Service, EMS. With this, and knowing that the decision maker needs a direction on which choice may be the most appropriate, based on different and often conflicting criteria. The current work developed a new model for prioritizing victims of SAMU/192, based on the multicriteria decision methodology, taking into account the scarcity of resources.

METHODS

An expert panel and a discussion group were formed, which defined the limits of the problem, and identified the evaluation criteria for choosing a victim, amongst four alternatives illustrated from hypothetical scenarios of emergency situations-clinical and traumatic diseases of absolute priority. For prioritization, an additive mathematical method was used that aggregates criteria in a flexible and interactive version, FITradeoff.

RESULTS

The structuring of the problem led the researchers to identify twenty-five evaluation criteria, amongst which ten were essential to guide decisions. As a result, in the simulation of prioritization of four requesting victims in view of the availability of only one ambulance, the proposed model supported the decision by suggesting the prioritization of one of the victims.

CONCLUSIONS

This work contributed to the prioritization of victims using multicriteria decision support methodology. Selecting and weighing the criteria in this study indicated that the protocols that guide regulatory physicians do not consider all the criteria for prioritizing victims in an environment of scarcity of resources. Finally, the proposed model can support crucial decision based on a rational and transparent decision-making process that can be applied in other EMS.

Which Criteria are Considered and How are They Evaluated in Health Technology Assessments? A Review of Methodological Guidelines Used in Western and Asian Countries

OBJECTIVES

This study aimed to provide an exhaustive description of criteria and methodological recommendations for evaluating them in health technology assessment (HTA) in Western and Asian countries.

METHODS

We conducted a system literature review of HTA-related guidelines by searching the websites of HTA agencies and related data sources. The guidelines, reports, or recommendations introducing the HTA evaluation methods, processes, decision-making frameworks, and criteria for priority setting were eligible to be included. The review was limited to guidelines from countries belonging to the European Network for Health Technology Assessment (EUnetHTA) and HTAsiaLink organisations and other countries with well-established available guidelines.

RESULTS

A total of 52 guidelines from 24 countries were identified, including 13 countries from the EUnetHTA organisation, 9 countries from the HTAsiaLink organisation and 2 other countries (Canada and the USA). A strong consensus was observed among the HTA agencies on the core set of criteria including efficacy or effectiveness, cost-effectiveness, safety, and budget impact. More similarities were observed than differences in methodological recommendations for clinical and economic evaluations among the agencies.

CONCLUSIONS

Substantial convergence is seen in the criteria included in the HTA process, as well as the methods to evaluate and quantify them. Further efforts are needed to verify whether the criteria identified from the guidelines are incorporated in real HTA decisions, and how they are assessed and weighted in practice.

A Vulnerability Analysis for the Management of and Response to the COVID-19 Epidemic in the Second Most Populous State in Brazil

The COVID-19 pandemic has the potential to affect all individuals, however in a heterogeneous way. In this sense, identifying specificities of each location is essential to minimize the damage caused by the disease. Therefore, the aim of this research was to assess the vulnerability of 853 municipalities in the second most populous state in Brazil, Minas Gerais (MG), in order to direct public policies. An epidemiological study was carried out based on Multi-Criteria Decision Analysis (MCDA) using indicators with some relation to the process of illness and death caused by COVID-19. The indicators were selected by a literature search and categorized into: demographic, social, economic, health infrastructure, population at risk and epidemiological. The variables were collected in Brazilian government databases at the municipal level and evaluated according to MCDA, through the Program to Support Decision Making based on Indicators (PRADIN). Based on this approach, the study performed simulations by category of indicators and a general simulation that allowed to divide the municipalities into groups of 1-5, with 1 being the least vulnerable and 5 being the most vulnerable. The groupings of municipalities were exposed in their respective mesoregions of MG in a thematic map, using the software Tabwin 32. The results revealed that the mesoregion of Norte de Minas stands out with more than 40% of its municipalities belonging to group 5, according to economic, social and health infrastructure indicators. Similarly, the Jequitinhonha mesoregion exhibited almost 60% of the municipalities in this group for economic and health infrastructure indicators. For demographic and epidemiological criteria, the Metropolitana de Belo Horizonte was the most vulnerable mesoregion, with 42.9 and 26.7% of the municipalities in group 5, respectively. Considering the presence of a population at risk, Zona da Mata reported 42.3% of the municipalities in the most vulnerable group. In the joint analysis of data, the Jequitinhonha, Vale do Mucuri and Vale do Rio Doce mesoregions were the most vulnerable in the state of MG. Thus, through the outlined profile, the present study proved how socioeconomic diversity affects the vulnerability of the municipalities to face COVID-19 outbreak, highlighting the need for interventions directed to each reality.