Guidance on the use of complex systems models for economic evaluations of public health interventions.

To help health economic modelers respond to demands for greater use of complex systems models in public health. To propose identifiable features of such models and support researchers to plan public health modeling projects using these models. A working group of experts in complex systems modeling and economic evaluation was brought together to develop and jointly write guidance for the use of complex systems models for health economic analysis. The content of workshops was informed by a scoping review. A public health complex systems model for economic evaluation is defined as a quantitative, dynamic, non-linear model that incorporates feedback and interactions among model elements, in order to capture emergent outcomes and estimate health, economic and potentially other consequences to inform public policies. The guidance covers: when complex systems modeling is needed; principles for designing a complex systems model; and how to choose an appropriate modeling technique. This paper provides a definition to identify and characterize complex systems models for economic evaluations and proposes guidance on key aspects of the process for health economics analysis. This document will support the development of complex systems models, with impact on public health systems policy and decision making.

The Cost-Effectiveness of Expanding the UK Newborn Bloodspot Screening Programme to Include Five Additional Inborn Errors of Metabolism.

Glutaric aciduria type 1, homocystinuria, isovaleric acidaemia, long-chain hydroxyacyl CoA dehydrogenase deficiency and maple syrup urine disease are all inborn errors of metabolism that can be detected through newborn bloodspot screening. This evaluation was undertaken in 2013 to provide evidence to the UK National Screening Committee for the cost-effectiveness of including these five conditions in the UK Newborn Bloodspot Screening Programme. A decision-tree model with lifetable estimates of outcomes was built with the model structure and parameterisation informed by a systematic review and expert clinical judgment. A National Health Service/Personal Social Services perspective was used, and lifetime costs and quality-adjusted life years (QALYs) were discounted at 1.5%. Uncertainty in the results was explored using expected value of perfect information analysis methods together with a sensitivity analysis using the screened incidence rate in the UK from 2014 to 2018. The model estimates that screening for all the conditions is more effective and cost saving when compared to not screening for each of the conditions, and the results were robust to the updated incidence rates. The key uncertainties included the sensitivity and specificity of the screening test and the estimated costs and QALYs.

The SIPHER Consortium: Introducing the new UK hub for systems science in public health and health economic research.

The conditions in which we are born, grow, live, work and age are key drivers of health and inequalities in life chances. To maximise health and wellbeing across the whole population, we need well-coordinated action across government sectors, in areas including economic, education, welfare, labour market and housing policy. Current research struggles to offer effective decision support on the cross-sector strategic alignment of policies, and to generate evidence that gives budget holders the confidence to change the way major investment decisions are made. This open letter introduces a new research initiative in this space. The SIPHER ( Systems Science in Public Health and Health Economics Research) Consortium brings together a multi-disciplinary group of scientists from across six universities, three government partners at local, regional and national level, and ten practice partner organisations. The Consortium's vision is a shift from health policy to healthy public policy, where the wellbeing impacts of policies are a core consideration across government sectors. Researchers and policy makers will jointly tackle fundamental questions about: a) the complex causal relationships between upstream policies and wellbeing, economic and equality outcomes; b) the multi-sectoral appraisal of costs and benefits of alternative investment options; c) public values and preferences for different outcomes, and how necessary trade-offs can be negotiated; and d) creating the conditions for intelligence-led adaptive policy design that maximises progress against economic, social and health goals. Whilst our methods will be adaptable across policy topics and jurisdictions, we will initially focus on four policy areas: Inclusive Economic Growth, Adverse Childhood Experiences, Mental Wellbeing and Housing.

Effect of Reflection and Deliberation on Health State Values: A Mixed-Methods Study.

BACKGROUND: Health economists ask members of the general public to value health states, but it is recognized that individuals construct their preferences during the valuation tasks. Conventional methods rely on one-off interviews that do not give participants time to reflect and deliberate on their preferences. OBJECTIVE: This study investigates the effect of reflection and deliberation on health state preferences using the EQ-5D questionnaire and time trade-off valuation method. METHODS: A novel concurrent explanatory mixed-methods design is used to investigate the explanation for the quantitative findings. RESULTS: A total of 57 participants in the United Kingdom valued health states before and after a group-based deliberation exercise. There were large changes in health state values at the individual level, but the changes canceled out at the aggregate level. The mixed-methods findings suggest deliberation did not reveal new information or reduce inconsistencies in reasoning but rather focused on an exchange of personal subjective beliefs. In cases of disagreement, the participants accepted but did not adopt other participants' opinions. Participants remained uncertain about the relevance of their experiences and about their values. CONCLUSIONS: The evidence suggests that reflection and deliberation, as designed in this study, are unlikely to result in large systematic changes of health state values. The uncertainties expressed by participants means future research should investigate whether preferences are informed or whether providing participants with more information helps them construct their preferences with more certainty. The mixed-methods design used is a promising design to help elucidate the reasons for quantitative findings.

Identification, Review, and Use of Health State Utilities in Cost-Effectiveness Models: An ISPOR Good Practices for Outcomes Research Task Force Report.

Cost-effectiveness models that present results in terms of cost per quality-adjusted life-year for health technologies are used to inform policy decisions in many parts of the world. Health state utilities (HSUs) are required to calculate the quality-adjusted life-years. Even when clinical studies assessing the effectiveness of health technologies collect data on HSUs to populate a cost-effectiveness model, which rarely happens, analysts typically need to identify at least some additional HSUs from alternative sources. When possible, HSUs are identified by a systematic review of the literature, but, again, this rarely happens. In 2014, ISPOR established a Good Practices for Outcome Research Task Force to address the use of HSUs in cost-effectiveness models. This task force report provides recommendations for researchers who identify, review, and synthesize HSUs for use in cost-effectiveness models; analysts who use the results in models; and reviewers who critically appraise the suitability and validity of the HSUs selected for use in models. The associated Minimum Reporting Standards of Systematic Review of Utilities for Cost-Effectiveness checklist created by the task force provides criteria to judge the appropriateness of the HSUs selected for use in cost-effectiveness models and is suitable for use in different international settings.

Rheumatoid arthritis treated with 6-months of first-line biologic or biosimilar therapy: an updated systematic review and network meta-analysis.

OBJECTIVES: The aim of this study was to estimate the effectiveness of first-line biologic disease modifying drugs(boDMARDs), and their approved biosimilars (bsDMARDs), compared with conventional (csDMARD) treatment, in terms of ACR (American College of Rheumatology) and EULAR (European League against Rheumatism) responses. METHODS: Systematic literature search, on eight databases to January 2017, sought ACR and EULAR data from randomized controlled trials (RCTs) of boDMARDs / bsDMARDs (in combination with csDMARDs, or monotherapy). Two adult populations: methotrexate (MTX)-naïve patients with severe active RA; and csDMARD-experienced patients with moderate-to-severe active RA. Network meta-analyses (NMA) were conducted using a Bayesian Markov chain Monte Carlo simulation using a random effects model with a probit link function for ordered categorical. RESULTS: Forty-six RCTs met the eligibility criteria. In the MTX-naïve severe active RA population, no biosimilar trials meeting the inclusion criteria were identified. MTX plus methylprednisolone (MP) was most likely to achieve the best ACR response. There was insufficient evidence that combination boDMARDs was superior to intensive (two or more) csDMARDs. In the csDMARD-experienced, moderate-to-severe RA population, the greatest effects for ACR responses were associated with tocilizumab (TCZ) monotherapy, and combination therapy (plus MTX) with bsDMARD etanercept (ETN) SB4, boDMARD ETN and TCZ. These treatments also had the greatest effects on EULAR responses. No clear differences were found between the boDMARDs and their bsDMARDs. CONCLUSIONS: In MTX-naïve patients, there was insufficient evidence that combination boDMARDs was superior to two or more csDMARDs. In csDMARD-experienced patients, boDMARDs and bsDMARDs were comparable and all combination boDMARDs / bsDMARDs were superior to single csDMARD.

Toward a theory-led metaframework for considering socioeconomic health inequalities within systematic reviews.

OBJECTIVES: To develop a theory-led framework to inform reviewers' understanding of what, how, and why health care interventions may lead to differential effects across socioeconomic groups. STUDY DESIGN AND SETTING: A metaframework approach combined two theoretical perspectives (socioeconomic health inequalities and complex interventions) into a single framework to inform socioeconomic health inequality considerations in systematic reviews. RESULTS: Four theories relating to complexity within systematic reviews and 16 health inequalities intervention theories informed the development of a metaframework. Factors relating to the type of intervention, implementation, context, participant response, and mechanisms associated with differential effects across socioeconomic groups were identified. The metaframework can inform; reviewer discussions around how socioeconomic status (SES) can moderate intervention effectiveness during question formulation, approaches to data extraction and help identify a priori analysis considerations. CONCLUSION: The metaframework offers a transparent, practical, theory-led approach to inform a program theory for what, how, and why interventions work for different SES groups in systematic reviews. It can enhance existing guidance on conducting systematic reviews that consider health inequalities, increase awareness of how SES can moderate intervention effectiveness, and encourage a greater engagement with theory throughout the review process.

Use of programme theory to understand the differential effects of interventions across socio-economic groups in systematic reviews-a systematic methodology review.

BACKGROUND: Systematic review guidance recommends the use of programme theory to inform considerations of if and how healthcare interventions may work differently across socio-economic status (SES) groups. This study aimed to address the lack of detail on how reviewers operationalise this in practice. METHODS: A methodological systematic review was undertaken to assess if, how and the extent to which systematic reviewers operationalise the guidance on the use of programme theory in considerations of socio-economic inequalities in health. Multiple databases were searched from January 2013 to May 2016. Studies were included if they were systematic reviews assessing the effectiveness of an intervention and included data on SES. Two reviewers independently screened all studies, undertook quality assessment and extracted data. A narrative approach to synthesis was adopted. RESULTS: A total of 37 systematic reviews were included, 10 of which were explicit in the use of terminology for 'programme theory'. Twenty-nine studies used programme theory to inform both their a priori assumptions and explain their review findings. Of these, 22 incorporated considerations of both what and how interventions do/do not work in SES groups to both predict and explain their review findings. Thirteen studies acknowledged 24 unique theoretical references to support their assumptions of what or how interventions may have different effects in SES groups. Most reviewers used supplementary evidence to support their considerations of differential effectiveness. The majority of authors outlined a programme theory in the "Introduction" and "Discussion" sections of the review to inform their assumptions or provide explanations of what or how interventions may result in differential effects within or across SES groups. About a third of reviews used programme theory to inform the review analysis and/or synthesis. Few authors used programme theory to inform their inclusion criteria, data extraction or quality assessment. Twenty-one studies tested their a priori programme theory. CONCLUSIONS: The use of programme theory to inform considerations of if, what and how interventions lead to differential effects on health in different SES groups in the systematic review process is not yet widely adopted, is used implicitly, is often fragmented and is not implemented in a systematic way.

The Identification, Review and Synthesis of Health State Utility Values from the Literature.

Systematic literature reviews of health-related quality of life (HRQoL) evidence that are to inform economic models can be challenging due to the volume of hits identified in searches using generic terms for HRQoL. Nevertheless, a robust review of the literature is required to ensure that the health state utility values (HSUVs) used in the economic model are the most appropriate available. This article provides a synopsis of literature relating to identifying, reviewing and synthesising HSUVs. The process begins with scoping the needs of the economic model, including the definitions of health states and the requirements of any reimbursement agencies. A sequence of searches may be required as the economic model evolves. The terminology used for HRQoL measures may be problematic, and as there is no robust HRQoL filter [equivalent to that applied for randomised control trial (RCTs)], sifting the results of sensitive searches can be resource intensive. Alternative approaches such as forward and backward citation searches may reduce the resources required, while maintaining the integrity of the search. Any included studies should be assessed in terms of quality using a recommended checklist, and insufficient detail in the primary studies should be noted as a short-coming in this exercise. Subject to homogeneity (similar populations, same measure and preference weights) evidence can be pooled in some way, although methodological research into the appropriateness of alternative techniques for meta-analysis is in its infancy. Reporting standards are key and as a minimum should include details on searches, inclusion/exclusion criteria (together with rationale for exclusion at each stage), assessment of quality and relevance of included studies, and justification for the choice of final HSUVs.

Adalimumab, etanercept, infliximab, certolizumab pegol, golimumab, tocilizumab and abatacept for the treatment of rheumatoid arthritis not previously treated with disease-modifying antirheumatic drugs and after the failure of conventional disease-modifying antirheumatic drugs only: systematic review and economic evaluation.

OBJECTIVES: Rheumatoid arthritis (RA) is a chronic inflammatory disease associated with increasing disability, reduced quality of life and substantial costs (as a result of both intervention acquisition and hospitalisation). The objective was to assess the clinical effectiveness and cost-effectiveness of seven biologic disease-modifying antirheumatic drugs (bDMARDs) compared with each other and conventional disease-modifying antirheumatic drugs (cDMARDs). The decision problem was divided into those patients who were cDMARD naive and those who were cDMARD experienced; whether a patient had severe or moderate to severe disease; and whether or not an individual could tolerate methotrexate (MTX). DATA SOURCES: The following databases were searched: MEDLINE from 1948 to July 2013; EMBASE from 1980 to July 2013; Cochrane Database of Systematic Reviews from 1996 to May 2013; Cochrane Central Register of Controlled Trials from 1898 to May 2013; Health Technology Assessment Database from 1995 to May 2013; Database of Abstracts of Reviews of Effects from 1995 to May 2013; Cumulative Index to Nursing and Allied Health Literature from 1982 to April 2013; and TOXLINE from 1840 to July 2013. Studies were eligible for inclusion if they evaluated the impact of a bDMARD used within licensed indications on an outcome of interest compared against an appropriate comparator in one of the stated population subgroups within a randomised controlled trial (RCT). Outcomes of interest included American College of Rheumatology (ACR) scores and European League Against Rheumatism (EULAR) response. Interrogation of Early Rheumatoid Arthritis Study (ERAS) data was undertaken to assess the Health Assessment Questionnaire (HAQ) progression while on cDMARDs. METHODS: Network meta-analyses (NMAs) were undertaken for patients who were cDMARD naive and for those who were cDMARD experienced. These were undertaken separately for EULAR and ACR data. Sensitivity analyses were undertaken to explore the impact of including RCTs with a small proportion of bDMARD experienced patients and where MTX exposure was deemed insufficient. A mathematical model was constructed to simulate the experiences of hypothetical patients. The model was based on EULAR response as this is commonly used in clinical practice in England. Observational databases, published literature and NMA results were used to populate the model. The outcome measure was cost per quality-adjusted life-year (QALY) gained. RESULTS: Sixty RCTs met the review inclusion criteria for clinical effectiveness, 38 of these trials provided ACR and/or EULAR response data for the NMA. Fourteen additional trials contributed data to sensitivity analyses. There was uncertainty in the relative effectiveness of the interventions. It was not clear whether or not formal ranking of interventions would result in clinically meaningful differences. Results from the analysis of ERAS data indicated that historical assumptions regarding HAQ progression had been pessimistic. The typical incremental cost per QALY of bDMARDs compared with cDMARDs alone for those with severe RA is > £40,000. This increases for those who cannot tolerate MTX (£50,000) and is > £60,000 per QALY when bDMARDs were used prior to cDMARDs. Values for individuals with moderate to severe RA were higher than those with severe RA. Results produced using EULAR and ACR data were similar. The key parameter that affected the results is the assumed HAQ progression while on cDMARDs. When historic assumptions were used typical incremental cost per QALY values fell to £38,000 for those with severe disease who could tolerate MTX. CONCLUSIONS: bDMARDs appear to have cost per QALY values greater than the thresholds stated by the National Institute for Health and Care Excellence for interventions to be cost-effective. Future research priorities include: the evaluation of the long-term HAQ trajectory while on cDMARDs; the relationship between HAQ direct medical costs; and whether or not bDMARDs could be stopped once a patient has achieved a stated target (e.g. remission). STUDY REGISTRATION: This study is registered as PROSPERO CRD42012003386. FUNDING: The National Institute for Health Research Health Technology Assessment programme.

Identification of Evidence for Key Parameters in Decision-Analytic Models of Cost Effectiveness: A Description of Sources and a Recommended Minimum Search Requirement.

This paper proposes recommendations for a minimum level of searching for data for key parameters in decision-analytic models of cost effectiveness and describes sources of evidence relevant to each parameter type. Key parameters are defined as treatment effects, adverse effects, costs, resource use, health state utility values (HSUVs) and baseline risk of events. The recommended minimum requirement for treatment effects is comprehensive searching according to available methodological guidance. For other parameter types, the minimum is the searching of one bibliographic database plus, where appropriate, specialist sources and non-research-based and non-standard format sources. The recommendations draw on the search methods literature and on existing analyses of how evidence is used to support decision-analytic models. They take account of the range of research and non-research-based sources of evidence used in cost-effectiveness models and of the need for efficient searching. Consideration is given to what constitutes best evidence for the different parameter types in terms of design and scientific quality and to making transparent the judgments that underpin the selection of evidence from the options available. Methodological issues are discussed, including the differences between decision-analytic models of cost effectiveness and systematic reviews when searching and selecting evidence and comprehensive versus sufficient searching. Areas are highlighted where further methodological research is required.

Improving search efficiency for systematic reviews of diagnostic test accuracy: an exploratory study to assess the viability of limiting to MEDLINE, EMBASE and reference checking.

BACKGROUND: Increasing numbers of systematic reviews evaluating the diagnostic test accuracy of technologies are being published. Currently, review teams tend to apply conventional systematic review standards to identify relevant studies for inclusion, for example sensitive searches of multiple bibliographic databases. There has been little evaluation of the efficiency of searching only one or two such databases for this type of review. The aim of this study was to assess the viability of an approach that restricted searches to MEDLINE, EMBASE and the reference lists of included studies. METHODS: A convenience sample of nine Health Technology Assessment (HTA) systematic reviews of diagnostic test accuracy, with 302 included citations, was analysed to determine the number and proportion of included citations that were indexed in and retrieved from MEDLINE and EMBASE. An assessment was also made of the number and proportion of citations not retrieved from these databases but that could have been identified from the reference lists of included citations. RESULTS: 287/302 (95 %) of the included citations in the nine reviews were indexed across MEDLINE and EMBASE. The reviews' searches of MEDLINE and EMBASE accounted for 85 % of the included citations (256/302). Of the forty-six (15 %) included citations not retrieved by the published searches, 24 (8 %) could be found in the reference lists of included citations. Only 22/302 (7 %) of the included citations were not found by the proposed, more efficient approach. CONCLUSIONS: The proposed approach would have accounted for 280/302 (93 %) of included citations in this sample of nine systematic reviews. This exploratory study suggests that there might be a case for restricting searches for systematic reviews of diagnostic test accuracy studies to MEDLINE, EMBASE and the reference lists of included citations. The conduct of such reviews might be rendered more efficient by using this approach.

ITERATIVE SIFTING IN THE SELECTION OF RESEARCH EVIDENCE: IMPLICATIONS FOR REVIEWS AND OTHER DECISION PROBLEMS.

OBJECTIVES: A rapid scoping review was performed to support the development of a new clinical technology platform. An iterative sifting approach was adopted to address the challenges posed by the nature of the review question and the extremely large volume of search results to be sifted within the timescales of the review. METHODS: This study describes the iterative sifting approach applied in the scoping review and a preliminary validation of the methods applied. RESULTS: The searches performed for the rapid scoping review retrieved 27,198 records. This was the full set of records subjected to the staged, iterative sifting approach and the subsequent validation process. The iterative sifting approach involved the screening for relevance of 17,354 (i.e., 63.8 percent) of the 27,198 records. A list of fifty-three potential biomarker names was generated as a result of this iterative sifting method, of which nineteen were selected by clinical specialists for further scrutiny. The preliminary validation involved the exhaustive sifting of the remaining 9,844 previously unsifted records. The validation process identified sixteen additional potential biomarker names not identified by the iterative sifting process. The clinical specialists subsequently concluded that none were of further clinical interest. CONCLUSIONS: This study describes an approach to the screening of search records that can be successfully applied in appropriate review and decision problems to allow the prioritization of the most relevant search records and achieve time savings. Following further refinement and standardization, this iterative sifting method may have potential for further applications in reviews and other decision problems.

Identification and review of cost-effectiveness model parameters: a qualitative study.

OBJECTIVES: Health economic models are developed as part of the health technology assessment process to determine whether health interventions represent good value for money. These models are often used to directly inform healthcare decision making and policy. The information needs for the model require the use of other types of information beyond clinical effectiveness evidence to populate the model's parameters. The purpose of this research study was to explore issues concerned with the identification and use of information for the development of such models. METHODS: Three focus groups were held in February 2011 at the University of Sheffield with thirteen UK HTA experts. Attendees included health economic modelers, information specialists and systematic reviewers. Qualitative framework analysis was used to analyze the focus group data. RESULTS: Six key themes, with related sub-themes, were identified dealing with decisions and judgments; searching methods; selection and rapid review of evidence; team communication; modeler experience and clinical input and reporting methods. There was considerable overlap between themes. CONCLUSIONS: Key issues raised by the respondents included the need for effective communication and teamwork throughout the model development process, the importance of using clinical experts as well as the need for transparent reporting of methods and decisions.

A systematic review, psychometric analysis and qualitative assessment of generic preference-based measures of health in mental health populations and the estimation of mapping functions from widely used specific measures.

BACKGROUND: Generic preference-based measures of health like the EQ-5D and SF-6D(®) are increasingly being used in economic evaluation and outcome assessment. However, there are concerns as to whether or not these generic measures are appropriate for use in people with mental health problems. OBJECTIVES: The EQ-5D and SF-36(®) (including its derivatives the SF-12(®) and SF-6D) were assessed using the psychometric criteria of validity and responsiveness using quantitative and qualitative methods. Another aim was to estimate mapping functions between the EQ-5D and SF-6D and condition-specific measures, where appropriate. DESIGN: Four studies were undertaken to examine the appropriateness of the measures: (1) a systematic review of quantitative evidence on validity and responsiveness; (2) a further quantitative assessment of these criteria using existing data sets; (3) a review of qualitative research on the quality of life of people with mental health problems; and (4) qualitative semistructured interviews of people with a full range of problems. A fifth study estimated mapping functions between mental health-specific measures and the EQ-5D and SF-6D. SETTING: A choice of venue was offered for the interviews including the participant's own home, a room at the university or a centre frequently used by mental health services. PARTICIPANTS: The interviews were undertaken with 19 people with a broad range of mental health problems at varying levels of severity. MAIN OUTCOME MEASURES: The reviews included the EQ-5D and SF-36 (and the SF-12 and SF-6D). The psychometric analysis included the Hospital Anxiety and Depression Scale (HADS), Clinical Outcomes in Routine Evaluation - Outcome Measure (CORE-OM), Generalised Anxiety Disorder Assessment (GAD-7), General Health Questionnaire (GHQ-12) and Patient Health Questionnaire (PHQ-9). RESULTS: (1) and (2) The EQ-5D and SF-36 achieved an adequate level of performance in depression, and to some extent in anxiety and personality disorder. Results from the psychometric analyses in schizophrenia and bipolar disorder have been more mixed. (3) A framework analysis of 13 studies identified six major themes. (4) The interview data fitted the themes from the review well and resulted in minor modifications to the themes. The final set of themes comprised: well-being and ill-being; control, autonomy and choice; self-perception; belonging; activity; hope and hopelessness; and physical health. CONCLUSIONS: The EQ-5D and SF-36 achieved mixed results in the quantitative testing against psychometric criteria. The qualitative analysis suggests this is because they provide a very limited coverage of themes identified by people with mental health problems. Recommendations for future work include the development of new preference-based measures in mental health that are based on, or substantially revise, an existing measure. FUNDING: The Medical Research Council.

Reviewing the evidence to inform the population of cost-effectiveness models within health technology assessments.

OBJECTIVES: Health technology assessments (HTAs) typically require the development of a cost-effectiveness model, which necessitates the identification, selection, and use of other types of information beyond clinical effectiveness evidence to populate the model parameters. The reviewing activity associated with model development should be transparent and reproducible but can result in a tension between being both timely and systematic. Little procedural guidance exists in this area. The purpose of this article was to provide guidance, informed by focus groups, on what might constitute a systematic and transparent approach to reviewing information to populate model parameters. METHODS: A focus group series was held with HTA experts in the United Kingdom including systematic reviewers, information specialists, and health economic modelers to explore these issues. Framework analysis was used to analyze the qualitative data elicited during focus groups. RESULTS: Suggestions included the use of rapid reviewing methods and the need to consider the trade-off between relevance and quality. The need for transparency in the reporting of review methods was emphasized. It was suggested that additional attention should be given to the reporting of parameters deemed to be more important to the model or where the preferred decision regarding the choice of evidence is equivocal. DISCUSSION: These recommendations form part of a Technical Support Document produced for the National Institute for Health and Clinical Excellence Decision Support Unit in the United Kingdom. It is intended that these recommendations will help to ensure a more systematic, transparent, and reproducible process for the review of model parameters within HTA.