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.

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.

Relationship Between Standardized Measures of Chronic Kidney Disease-associated Pruritus Intensity and Health-related Quality of Life Measured with the EQ-5D Questionnaire: A Mapping Study.

Chronic kidney disease-associated pruritus is linked with decreased health-related quality of life assessed using disease-specific instruments. The extent to which worsening pruritus reduces generic quality of life assessed using the EQ-5D instrument is unknown. Prevalent kidney failure patients receiving in-centre haemodialysis from 5 centres completed the EQ-5D-5L quality of life measure, worst Itching Intensity Numerical Rating Scale and 5-D itch pruritus instruments. Latent class models were used to identify clusters of patients with similarly affected body parts, and mixture models were used to map the pruritus measures to the EQ-5D. Data on 487 respondents were obtained. Latent class analysis identified 3 groups of patients who had progressively worsening severity and an increasing number of body parts affected. Although the worst itching intensity numerical rating scale and 5-D itch instruments correlated with each other, only the latter had a strong relationship with EQ-5D. When controlling for age, sex, diabetes and years receiving dialysis, the meanpredicted EQ-5D utility (1: perfect health, 0: dead) decreased progressively from 0.69 to 0.41. These findings suggest that pruritus instruments that include domains capturing how the individual is physically, mentally and socially affected by their pruritus, in addition to severity, more closely approximate the EQ-5D generic quality of life measure.

Does Hospital Admission/Observation for Chest Pain Improve Patient Outcomes after Emergency Department Evaluation for Suspected Acute Coronary Syndrome?

BACKGROUND: Chest pain is the top reason for hospitalization/observation in the USA, but it is unclear if this strategy improves patient outcomes. OBJECTIVE: The objective of this study was to compare 30-day outcomes for patients admitted versus discharged after a negative emergency department (ED) evaluation for suspected acute coronary syndrome. DESIGN: A retrospective, multi-site, cohort study of adult encounters with chest pain presenting to one of 13 Kaiser Permanente Southern California EDs between January 1, 2015, and December 1, 2017. Instrumental variable analysis was used to mitigate potential confounding by unobserved factors. PATIENTS: All adult patients presenting to an ED with chest pain, in whom an acute myocardial infarction was not diagnosed in the ED, were included. MAIN MEASURES: The primary outcome was 30-day acute myocardial infarction or all-cause mortality, and secondary outcomes included 30-day revascularization and major adverse cardiac events. KEY RESULTS: In total, 77,652 patient encounters were included in the study (n=11,026 admitted, 14.2%). Three hundred twenty-two (0.4%) had an acute myocardial infarction (n=193, 0.2%) or death (n=137, 0.2%) within 30 days of ED visit (1.5% hospitalized versus 0.2% discharged). Very few (0.3%) patients underwent coronary revascularization within 30 days (0.7% hospitalized versus 0.2% discharged). Instrumental variable analysis found no adjusted differences in 30-day patient outcomes between the hospitalized cohort and those discharged (risk reduction 0.002, 95% CI -0.002 to 0.007). Similarly, there were no differences in coronary revascularization (risk reduction 0.003, 95% CI -0.002 to 0.007). CONCLUSION: Among ED patients with chest pain not diagnosed with an acute myocardial infarction, risk of major adverse cardiac events is quite low, and there does not appear to be any benefit in 30-day outcomes for those admitted or observed in the hospital compared to those discharged with outpatient follow-up.

Topic selection process in health technology assessment agencies around the world: a systematic review.

OBJECTIVE: The purpose of this study was to systematically review the process for topic selection by health technology assessment (HTA) agencies around the world to provide the knowledge base for the improvement of topic selection frameworks in HTA agencies. METHODS: A systematic search was conducted in PubMed and EMBASE to identify papers up to February 2019. Gray literature was identified by screening the Web sites of HTA agencies on the nonprofit member list of the International Network of Agencies for Health Technology Assessment (INAHTA). Data were extracted for each HTA agency and synthesized, with issues including general contextual information about each agency and the process of topic selection. RESULTS: Out of forty-nine nonprofit members of INAHTA, a total of seventeen HTA agencies with a framework for topic selection were identified from twenty-two included papers/documents. Multiple criteria were used for topic selection in all frameworks and agencies undertook multiple steps, which could include the specification of criteria for topic selection, identification of topics, short listing of potential topics, scoping of potential topics, scoring and ranking of potential topics, and deliberation and decision on final topics for HTA. Shortcomings were found in relation to methods of scoring and ranking as well as lack of monitoring and the evaluation of the process. CONCLUSIONS: Our study provides insights into the current practice of topic selection in HTA agencies. Multiple criteria decision analysis methodology appears highly relevant to these processes. A consensus approach for the development of methods of topic selection would be valuable for the HTA community.

The CAPACITI Decision-Support Tool for National Immunization Programs.

OBJECTIVES: Immunization programs in low-income and middle-income countries (LMICs) are faced with an ever-growing number of vaccines of public health importance recommended by the World Health Organization, while also financing a greater proportion of the program through domestic resources. More than ever, national immunization programs must be equipped to contextualize global guidance and make choices that are best suited to their setting. The CAPACITI decision-support tool has been developed in collaboration with national immunization program decision makers in LMICs to structure and document an evidence-based, context-specific process for prioritizing or selecting among multiple vaccination products, services, or strategies. METHODS: The CAPACITI decision-support tool is based on multi-criteria decision analysis, as a structured way to incorporate multiple sources of evidence and stakeholder perspectives. The tool has been developed iteratively in consultation with 12 countries across Africa, Asia, and the Americas. RESULTS: The tool is flexible to existing country processes and can follow any type of multi-criteria decision analysis or a hybrid approach. It is structured into 5 sections: decision question, criteria for decision making, evidence assessment, appraisal, and recommendation. The Excel-based tool guides the user through the steps and document discussions in a transparent manner, with an emphasis on stakeholder engagement and country ownership. CONCLUSIONS: Pilot countries valued the CAPACITI decision-support tool as a means to consider multiple criteria and stakeholder perspectives and to evaluate trade-offs and the impact of data quality. With use, it is expected that LMICs will tailor steps to their context and streamline the tool for decision making.

Cost-effectiveness of out-of-hospital continuous positive airway pressure for acute respiratory failure: decision analytic modelling using data from a feasibility trial.

BACKGROUND: Standard prehospital management for Acute respiratory failure (ARF) involves controlled oxygen therapy. Continuous positive airway pressure (CPAP) is a potentially beneficial alternative treatment, however, it is uncertain whether this could improve outcomes and provide value for money. This study aimed to evaluate the cost-effectiveness of prehospital CPAP in ARF. METHODS: A cost-utility economic evaluation was performed using a probabilistic decision tree model synthesising available evidence. The model consisted of a hypothetical cohort of patients in a representative ambulance service with undifferentiated ARF, receiving standard oxygen therapy or prehospital CPAP. Costs and quality adjusted life years (QALYs) were estimated using methods recommended by NICE. RESULTS: In the base case analysis, using CPAP effectiveness estimates form the ACUTE trial, the mean expected costs of standard care and prehospital CPAP were £15,201 and £14,850 respectively and the corresponding mean expected QALYs were 1.190 and 1.128, respectively. The mean ICER estimated as standard oxygen therapy compared to prehospital CPAP was £5685 per QALY which indicated that standard oxygen therapy strategy was likely to be cost-effective at a threshold of £20,000 per QALY (67% probability). The scenario analysis, using effectiveness estimates from an updated meta-analysis, suggested that prehospital CPAP was more effective (mean incremental QALYs of 0.157), but also more expensive (mean incremental costs of £1522), than standard care. The mean ICER, estimated as prehospital CPAP compared to standard care, was £9712 per QALY. At the £20,000 per QALY prehospital CPAP was highly likely to be the most cost-effective strategy (94%). CONCLUSIONS: Cost-effectiveness of prehospital CPAP depends upon the estimate of effectiveness. When based on a small pragmatic feasibility trial, standard oxygen therapy is cost-effective. When based on meta-analysis of heterogeneous trials, CPAP is cost-effective. Value of information analyses support commissioning of a large pragmatic effectiveness trial, providing feasibility and plausibility conditions are met.

Developing Markov Models From Real-World Data: A Case Study of Heart Failure Modeling Using Administrative Data.

OBJECTIVES: Markov models characterize disease progression as specific health states based on clinical or biological measures. However, these measures are not always collected outside clinical trials. In this article, an alternative approach is presented that uses real-world data to define the health states and to model transitions between them, specific to a local setting, to estimate the cost-effectiveness of telemonitoring (TM) versus no TM for heart failure. METHODS: The incidence of hospitalization for usual care was estimated from hospital episode statistics (HES) data in the United Kingdom and converted into a monthly transition matrix with 5 health states (4 states are defined based on the number of hospitalizations in the previous year and death) to estimate the cost-effectiveness of TM in a local UK primary care trust (PCT) using probabilistic sensitivity analysis from a healthcare perspective. RESULTS: Geographical variation in hospitalization rates were present, which led to different health state transition matrices in different localities. In the PCT that was evaluated, TM accrued mean additional costs of £3610 and 0.075 additional quality-adjusted life-years (QALYs) compared with usual care per patient, resulting in a mean incremental cost effectiveness ratio of £48 172/QALY. CONCLUSIONS: The use of administrative data to define health states and transition matrices based on health service events is feasible, and TM was not cost-effective in our analysis. Given the increasing emphasis on using real-world evidence, it is likely that these approaches will be used more in the future.

Cost effectiveness of nusinersen for patients with infantile-onset spinal muscular atrophy in US.

BACKGROUND: Patients with infantile-onset spinal muscular atrophy (SMA), a rare, genetic neuromuscular disease, do not achieve key motor function milestones (e.g., sitting) and have short life expectancy in the absence of treatment. Nusinersen is a disease-modifying therapy for patients with SMA. OBJECTIVE: The aim of this study was to estimate the cost-effectiveness of nusinersen compared to best supportive care (BSC) in patients diagnosed with infantile-onset SMA in the US. METHODS: A de novo economic model was developed with the following health states: "permanent ventilation", "not sitting", "sitting", "walking", and "death". Short-term data were sourced from the pivotal clinical trials and studies of nusinersen (ENDEAR and SHINE). Motor function milestones achieved at the end of follow-up in the clinical trials were assumed to be sustained until death. Mortality risks were based on survival modelling of relevant published Kaplan-Meier data. Costs, life years (LYs), and quality-adjusted life years (QALYs) were discounted at 3% per annum, and the analyses were performed from a US health care sector perspective. Scenario analyses and sensitivity analyses were conducted to assess the robustness of the results to key parameters. RESULTS: In our base-case analysis, nusinersen treatment achieves greater QALYs and more LYs (3.24 and 7.64, respectively) compared with BSC (0.46 QALYs and 2.40 LYs, respectively), resulting in an incremental cost per QALY gained of approximately $1,112,000 and an incremental cost per LY gained of $590,000 for nusinersen compared to BSC. The incremental cost effectiveness ratios did not fall below $990,000 per QALY gained in scenario and sensitivity analyses. Results were most sensitive to the length of survival, background health care costs, and utility in the "not sitting" and "sitting" health states. CONCLUSIONS: The estimated incremental cost-effectiveness of nusinersen from a US health care sector perspective exceeded traditional cost-effectiveness thresholds. Cost-effectiveness was dependent on assumptions made regarding survival, costs, utilities, and whether the motor function milestones were sustained over lifetime. Given the relatively short-term effectiveness data available for the treatment, a registry to collect long-term data of infantile-onset SMA patients is recommended.

Direct medical costs in the preceding, event and subsequent years of a first severe hypoglycaemia episode requiring hospitalization: A population-based cohort study.

AIMS: We aimed to estimate the use of healthcare services and the direct medical costs accrued by patients with diabetes mellitus (DM) during the year of the first severe hypoglycaemia (SH) event, as well as during the years before and after the event year. MATERIALS AND METHODS: We analysed a population-based, retrospective cohort including all adults with DM managed in the primary care setting from the Hong Kong Hospital Authority between 2006 and 2013. DM patients for whom SH was first recorded during the designated period were identified and matched to a control group of patients who had not experienced an SH event using the propensity score method. Direct medical costs in the years before, during and after the first SH event were determined by totalling the costs of health services utilized within respective years. RESULTS: After matching, a total of 22 694 DM patients were divided into the first recorded-SH group (n = 11 347) and the non-SH control group (n = 11 347). Patients for whom SH was first recorded, on average, made 7.85 outpatient clinic visits, made 1.89 emergency visits and spent 17.75 nights hospitalized during the event year. Mean direct medical costs during the event year were 11 751 US$, more than 2-fold that during the preceding year (4846 US$; P < 0.001) and subsequent years (4198-4700 US$; P < 0.001) and was 4.5 times that 2 years before the event (2481 US$; P < 0.001). Incremental costs of SH patients vs matched controls during the event year and the preceding year were 10 873 US$ (P < 0.001) and 3974 US$ (P < 0.001), respectively. CONCLUSIONS: SH is associated with excessive hospital admission rates and direct medical costs during the event year and, in particular, during the year before as compared to patients who had not experienced an SH event.

Multicriteria Decision Analysis to Support Health Technology Assessment Agencies: Benefits, Limitations, and the Way Forward.

OBJECTIVE: Recent years have witnessed an increased interest in the use of multicriteria decision analysis (MCDA) to support health technology assessment (HTA) agencies for setting healthcare priorities. However, its implementation to date has been criticized for being "entirely mechanistic," ignoring opportunity costs, and not following best practice guidelines. This article provides guidance on the use of MCDA in this context. METHODS: The present study was based on a systematic review and consensus development. We developed a typology of MCDA studies and good implementation practice. We reviewed 36 studies over the period 1990 to 2018 on their compliance with good practice and developed recommendations. We reached consensus among authors over the course of several review rounds. RESULTS: We identified 3 MCDA study types: qualitative MCDA, quantitative MCDA, and MCDA with decision rules. The types perform differently in terms of quality, consistency, and transparency of recommendations on healthcare priorities. We advise HTA agencies to always include a deliberative component. Agencies should, at a minimum, undertake qualitative MCDA. The use of quantitative MCDA has additional benefits but also poses design challenges. MCDA with decision rules, used by HTA agencies in The Netherlands and the United Kingdom and typically referred to as structured deliberation, has the potential to further improve the formulation of recommendations but has not yet been subjected to broad experimentation and evaluation. CONCLUSION: MCDA holds large potential to support HTA agencies in setting healthcare priorities, but its implementation needs to be improved.

Direct medical costs of diabetes mellitus in the year of mortality and year preceding the year of mortality.

AIM: To report the health resource use and estimate the direct medical costs among patients with diabetes mellitus (DM) in the year of mortality and the year preceding the year of mortality. MATERIALS AND METHODS: We analysed data from a population-based, retrospective cohort study including all adults with a DM diagnosis in Hong Kong between 2009 and 2013, and who died between January 1, 2010 and December 31, 2013. The annual direct medical costs in the year of mortality and the year preceding the year of mortality were determined by summing the costs of health services utilized within the respective year. The costs were analysed by gender, the presence of comorbidities, diabetic complications and primary cause of death. RESULTS: A total of 10 649 patients met the eligibility criteria for analysis. On average, the direct medical costs in the year of death were 1.947 times higher than those in the year before death. Men and women with DM incurred similar costs in the year preceding the year of mortality and in the mortality year. Patients with any diabetic complications incurred greater costs in the year of mortality and the year before mortality than those without. CONCLUSIONS: This analysis provides new evidence on incorporating additional direct medical costs in the mortality year, and refining the structure of total cost estimates for use in costing and cost-effectiveness analyses of interventions for DM.

Application of Constrained Optimization Methods in Health Services Research: Report 2 of the ISPOR Optimization Methods Emerging Good Practices Task Force.

BACKGROUND: Constrained optimization methods are already widely used in health care to solve problems that represent traditional applications of operations research methods, such as choosing the optimal location for new facilities or making the most efficient use of operating room capacity. OBJECTIVES: In this paper we illustrate the potential utility of these methods for finding optimal solutions to problems in health care delivery and policy. To do so, we selected three award-winning papers in health care delivery or policy development, reflecting a range of optimization algorithms. Two of the three papers are reviewed using the ISPOR Constrained Optimization Good Practice Checklist, adapted from the framework presented in the initial Optimization Task Force Report. The first case study illustrates application of linear programming to determine the optimal mix of screening and vaccination strategies for the prevention of cervical cancer. The second case illustrates application of the Markov Decision Process to find the optimal strategy for treating type 2 diabetes patients for hypercholesterolemia using statins. The third paper (described in Appendix 1) is used as an educational tool. The goal is to describe the characteristics of a radiation therapy optimization problem and then invite the reader to formulate the mathematical model for solving it. This example is particularly interesting because it lends itself to a range of possible models, including linear, nonlinear, and mixed-integer programming formulations. From the case studies presented, we hope the reader will develop an appreciation for the wide range of problem types that can be addressed with constrained optimization methods, as well as the variety of methods available. CONCLUSIONS: Constrained optimization methods are informative in providing insights to decision makers about optimal target solutions and the magnitude of the loss of benefit or increased costs associated with the ultimate clinical decision or policy choice. Failing to identify a mathematically superior or optimal solution represents a missed opportunity to improve economic efficiency in the delivery of care and clinical outcomes for patients. The ISPOR Optimization Methods Emerging Good Practices Task Force's first report provided an introduction to constrained optimization methods to solve important clinical and health policy problems. This report also outlined the relationship of constrained optimization methods relative to traditional health economic modeling, graphically illustrated a simple formulation, and identified some of the major variants of constrained optimization models, such as linear programming, dynamic programming, integer programming, and stochastic programming. The second report illustrates the application of constrained optimization methods in health care decision making using three case studies. The studies focus on determining optimal screening and vaccination strategies for cervical cancer, optimal statin start times for diabetes, and an educational case to invite the reader to formulate radiation therapy optimization problems. These illustrate a wide range of problem types that can be addressed with constrained optimization methods.

Stakeholder involvement in Multi-Criteria Decision Analysis.

This brief perspective highlights the importance of decision maker buy-in and ownership through stakeholder engagement in the co-construction of the multi-criteria decision analysis (MCDA) model. A brief historical overview of MCDA is presented before outlining the importance of bridging the gap (and to gain trust) between the tool developers and users. The issues with the current MCDA tool development and testing efforts are highlighted, and the ownership and routine adoption of the MCDA process is discussed.

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

BACKGROUND: Multicriteria decision analysis (MCDA) has the potential to bring more structure and transparency to health technology assessment (HTA). The objective of this paper is to highlight key methodological and practical challenges facing the use of MCDA for HTA, with a particular focus on lower and middle-income countries (LMICs), and to highlight potential solutions to these challenges. METHODOLOGICAL CHALLENGES: Key lessons from existing applications of MCDA to HTA are summarized, including: that the socio-technical design of the MCDA reflect the local decision problem; the criteria set properties of additive models are understood and applied; and the alternative approaches for estimating opportunity cost, and the challenges with these approaches are understood. PRACTICAL CHALLENGES: Existing efforts to implement HTA in LMICs suggest a number of lessons that can help overcome the practical challenges facing the implementation of MCDA in LMICs, including: adapting inputs from other settings and from expert opinion; investing in technical capacity; embedding the MCDA in the decision-making process; and ensuring that the MCDA design reflects local cultural and social factors. CONCLUSION: MCDA has the potential to improve decision making in LMICs. For this potential to be achieved, it is important that the lessons from existing applications of MCDA are learned.

Interventions to improve patient flow in emergency departments: an umbrella review.

OBJECTIVES: Patient flow and crowding are two major issues in ED service improvement. A substantial amount of literature exists on the interventions to improve patient flow and crowding, making it difficult for policymakers, managers and clinicians to be familiar with all the available literature and identify which interventions are supported by the evidence. This umbrella review provides a comprehensive analysis of the evidence from existing quantitative systematic reviews on the interventions that improve patient flow in EDs. METHODS: An umbrella review of systematic reviews published between 2000 and 2017 was undertaken. Included studies were systematic reviews and meta-analyses of quantitative primary studies assessing an intervention that aimed to improve ED throughput. RESULTS: The search strategy yielded 623 articles of which 13 were included in the umbrella review. The publication dates of the systematic reviews ranged from 2006 to 2016. The 13 systematic reviews evaluated 26 interventions: full capacity protocols, computerised provider order entry, scribes, streaming, fast track and triage. Interventions with similar characteristics were grouped together to produce the following categories: diagnostic services, assessment/short stay units, nurse-directed interventions, physician-directed interventions, administrative/organisational and miscellaneous. The statistical evidence from 14 primary randomised controlled trials (RCTs) was evaluated to determine if correlation or clustering of observations was considered. Only the fast track intervention had moderate evidence to support its use but the RCTs that assessed the intervention did not use statistical tests that considered correlation. CONCLUSIONS: Overall, the evidence supporting the interventions to improve patient flow is weak. Only the fast track intervention had moderate evidence to support its use but correlation/clustering was not taken into consideration in the RCTs examining the intervention. Failure to consider the correlation of the data in the primary studies could result in erroneous conclusions of effectiveness.

Constrained Optimization Methods in Health Services Research-An Introduction: Report 1 of the ISPOR Optimization Methods Emerging Good Practices Task Force.

Providing health services with the greatest possible value to patients and society given the constraints imposed by patient characteristics, health care system characteristics, budgets, and so forth relies heavily on the design of structures and processes. Such problems are complex and require a rigorous and systematic approach to identify the best solution. Constrained optimization is a set of methods designed to identify efficiently and systematically the best solution (the optimal solution) to a problem characterized by a number of potential solutions in the presence of identified constraints. This report identifies 1) key concepts and the main steps in building an optimization model; 2) the types of problems for which optimal solutions can be determined in real-world health applications; and 3) the appropriate optimization methods for these problems. We first present a simple graphical model based on the treatment of "regular" and "severe" patients, which maximizes the overall health benefit subject to time and budget constraints. We then relate it back to how optimization is relevant in health services research for addressing present day challenges. We also explain how these mathematical optimization methods relate to simulation methods, to standard health economic analysis techniques, and to the emergent fields of analytics and machine learning.

Cost effectiveness of using cognitive screening tests for detecting dementia and mild cognitive impairment in primary care.

INTRODUCTION: We estimated the cost effectiveness of different cognitive screening tests for use by General Practitioners (GPs) to detect cognitive impairment in England. METHODS: A patient-level cost-effectiveness model was developed using a simulated cohort that represents the elderly population in England (65 years and older). Each patient was followed over a lifetime period. Data from published sources were used to populate the model. The costs include government funded health and social care, private social care and informal care. Patient health benefit was measured and valued in Quality Adjusted Life Years (QALYs). RESULTS: Base-case analyses found that adopting any of the three cognitive tests (Mini-Mental State Examination, 6-Item Cognitive Impairment Test or GPCOG (General Practitioner Assessment of Cognition)) delivered more QALYs for patients over their lifetime and made savings across sectors including healthcare, social care and informal care compared with GP unassisted judgement. The benefits were due to early access to medications. Among the three cognitive tests, adopting the GPCOG was considered the most cost-effective option with the highest Incremental Net Benefit (INB) at the threshold of £30 000 per QALY from both the National Health Service and Personal Social Service (NHS PSS) perspective (£195 034 per 1000 patients) and the broader perspective that includes private social care and informal care (£196 251 per 1000 patients). Uncertainty was assessed in both deterministic and probabilistic sensitivity analyses. CONCLUSIONS: Our analyses indicate that the use of any of the three cognitive tests could be considered a cost-effective strategy compared with GP unassisted judgement. The most cost-effective option in the base-case was the GPCOG. Copyright © 2016 John Wiley & Sons, Ltd.

Multiple Criteria Decision Analysis for Health Care Decision Making--Emerging Good Practices: Report 2 of the ISPOR MCDA Emerging Good Practices Task Force.

Health care decisions are complex and involve confronting trade-offs between multiple, often conflicting objectives. Using structured, explicit approaches to decisions involving multiple criteria can improve the quality of decision making. A set of techniques, known under the collective heading, multiple criteria decision analysis (MCDA), are useful for this purpose. In 2014, ISPOR established an Emerging Good Practices Task Force. The task force's first report defined MCDA, provided examples of its use in health care, described the key steps, and provided an overview of the principal methods of MCDA. This second task force report provides emerging good-practice guidance on the implementation of MCDA to support health care decisions. The report includes: a checklist to support the design, implementation and review of an MCDA; guidance to support the implementation of the checklist; the order in which the steps should be implemented; illustrates how to incorporate budget constraints into an MCDA; provides an overview of the skills and resources, including available software, required to implement MCDA; and future research directions.

Multiple Criteria Decision Analysis for Health Care Decision Making--An Introduction: Report 1 of the ISPOR MCDA Emerging Good Practices Task Force.

Health care decisions are complex and involve confronting trade-offs between multiple, often conflicting, objectives. Using structured, explicit approaches to decisions involving multiple criteria can improve the quality of decision making and a set of techniques, known under the collective heading multiple criteria decision analysis (MCDA), are useful for this purpose. MCDA methods are widely used in other sectors, and recently there has been an increase in health care applications. In 2014, ISPOR established an MCDA Emerging Good Practices Task Force. It was charged with establishing a common definition for MCDA in health care decision making and developing good practice guidelines for conducting MCDA to aid health care decision making. This initial ISPOR MCDA task force report provides an introduction to MCDA - it defines MCDA; provides examples of its use in different kinds of decision making in health care (including benefit risk analysis, health technology assessment, resource allocation, portfolio decision analysis, shared patient clinician decision making and prioritizing patients' access to services); provides an overview of the principal methods of MCDA; and describes the key steps involved. Upon reviewing this report, readers should have a solid overview of MCDA methods and their potential for supporting health care decision making.