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INTRODUCTION: Technical and trade off issues to incorporating environmental data in HTA decision processes are known. Multi criteria decision analysis has been successfully used across disciplines, supporting multifaceted technology decision making. Challenges in prioritising environmental criteria, resource constraints, and other criteria to assess technologies can be overcome through the application of MCDA, also used in conjunction with other techniques in HTA.
METHODS: A systematic review of methods to evaluate environmental sustainability in HTA; conducted following the PRISMA guidelines. Using a comprehensive search strategy Ovid EMBASE; Web of Science (all databases); PubMed; EBSCO Host Greenfile; IEEE Xplore; International HTA database; Cochrane Library and grey literature were searched. The review analyzed the following broad themes; methods to overcome barriers including how methods can handle "trade off" issues between financial and environmental considerations , resource and expertise constraints and data quality issues. This review determined how comprehensive the methods are for assessing sustainability in HTA. Frameworks were also ranked based on their overall transparency and feasibility.
RESULTS:
This review identified ten key studies. Half of these studies outline MCDA models within their frameworks. All MCDA studies have been combined with other techniques to support sustainable technology decision making HTA. Analytical MCDA models with roots in mathematics are highlighted as reproducible techniques to support multifaceted decision making, particularly where there are conflicting criteria. Analytical hierarchy process (AHP) used in conjunction with a circular economy framework for health technology supports global health system net zero and wider sustainability goals. A performance matrix model elicits outcome trade off by assigning weights to costs, technical performance, and environmental outcomes.
CONCLUSIONS
The multidisciplinary findings of this research provide valuable insight in an area where there is currently limited research, confirming and expand on previous scoping reviews. The results highlight several comprehensive MCDA models supporting HTA sustainability framework development. Further research is warranted into the feasibility of the frameworks. Study selection and data extraction were undertaken independently due to project time constraints.
INTRODUCTION: Single-arm studies, particularly single-arm trials (SATs), are increasingly being used in submissions for marketing authorization and health technology assessment. As reviewers of evidence, we sought to better understand the validity of SATs, compared with observational single-arm studies (case series), and how to assess them in our reviews.
METHODS: We conducted a highly pragmatic literature review to create a convenience sample of recent systematic reviews published from January to July 2023 to establish the following: (i) what single-arm study designs are included; (ii) what quality assessment tools are used; and (iii) whether there is a difference in effect size and variability among different study designs. A single reviewer identified reviews of interventions that included single-arm studies and extracted information on the numbers of included SATs and case series, and the quality assessment tools used. Any misclassifications by review authors were identified. For meta-analyses, outcome data were extracted and a subgroup analysis comparing SATs and case series was conducted.
RESULTS: Work is still underway to complete this investigation. So far, it appears that a large proportion of systematic reviews misclassify SATs and case series studies and few use appropriate quality assessment tools. There is not yet any evidence of a systematic difference between SATs and case series in terms of effect size.
CONCLUSIONS: Findings suggest that there is poor understanding of SATs in the review community. There are limited specific quality assessment tools for SATs and review authors frequently use inappropriate tools to assess them. More research is likely to be needed to investigate the relative validity of SATs and single-arm observational studies.
INTRODUCTION: As health technology assessment (HTA) bodies introduce more rigorous requirements, the submission process is becoming increasingly diverse between countries. This study assesses the HTA submission processes and requirements in Australia, Canada, England, France and Germany. This allows the identification of where efficiencies can be made in the global market access strategy, such as when to submit HTA dossiers.
METHODS: A pragmatic review and desk-based research were conducted in November 2023. Published articles, HTA guidelines, process documents, conference abstracts, and white papers were reviewed to identify country-specific processes with implications for market access strategy. Where available, information was extracted about the general submission process and stakeholders involved (including regulatory, HTA and pricing authorities), clinical evidence requirements, and pharmacoeconomic evidence requirements for HTA submission. Comparisons of the median time from marketing authorization to HTA decision within each country allowed the identification of efficiencies in individual HTA submission processes. A narrative summary of the key findings and between-country differences will be presented.
RESULTS: The review identified several areas with implications for market access strategy. The median HTA review time was shortest in Australia (125 days) and longest in England (266 days). Australia and Canada have both sequential and parallel regulatory/HTA processes. The median time taken from regulatory approval to HTA recommendation was faster than the sequential process in both countries. All countries require comparative clinical evidence within the indication. The weight placed on pharmacoeconomic evidence varies between countries. In Germany, economic evaluation is yet to play a real role. Requirements for additional information after HTA submission occurred within all HTA bodies.
CONCLUSIONS: HTA processes in Canada, Australia, England, France, and Germany differ from one another. This will likely affect the market access strategy for health technology developers. Similar requirements allow efficiencies in the preparation of submission documentation. Future research should investigate the impact of the EU HTA Regulation on market access and how this could affect strategic decision making.
INTRODUCTION: Early health technology assessment (eHTA) can help to explore the potential value of a technology in the early stages of development. Care pathway analysis (CPA) is a method to identify and map clinical decisions in the current and new care pathways (including the new intervention). This work provides examples of applying CPA within the context of eHTA for medical interventions.
METHODS: CPA usually involves a pragmatic review to identify and synthesize national/international guidelines that describe the care pathway for the condition of interest. This is typically followed by a qualitative evaluation that can include semi-structured interviews with thematic analysis. Interviews with experts are undertaken to understand where (and why) real-world practices differ from published guidance and to validate the care pathway. They also help to evaluate the strengths/weaknesses of the new technology, potential population and role in the pathway, and barriers/facilitators to adoption. The CPA forms the basis of economic modelling that helps assess the monetary value of the new technology.
RESULTS: The application of CPA from two recent projects will be presented: an innovative diagnostic test for respiratory tract infections and a medical device for treating cataracts. Additionally, the value of CPA in eHTA will be described from the technology developers' perspective. In both projects, CPA was used to inform the potential value propositions of the new technology and its positioning in the care pathway. It also helped to optimize the structure of the early economic model and to identify evidence generation needs. The early model identified the pathway that was more likely to be cost effective in the future.
CONCLUSIONS: CPA is a valuable method within the context of eHTA. Alongside identifying the potential role and positioning of the new technology, test developers found the assessment useful for informing internal strategy decisions and discussions with potential external investors. The developers were able to demonstrate the clinical perspective around the value of the test, elicited through an independent and rigorous methodology.
INTRODUCTION: Conducting a systematic review (SR) of clinical trials is labor-intensive and expensive. However, existing open-source content can be used to develop custom machine learning tools suited to the workflow of individual organizations. This case study details the potential of a bespoke tool developed by York Health Economics Consortium (YHEC) for reducing the time and cost involved in producing an SR.
METHODS: RESbot is a flexible, stand-alone machine learning tool created using an extensively tested open-source dataset developed by Cochrane. The tool identifies randomized controlled trials (RCTs) from a large corpus of records. It has a user interface and inputs/outputs to fit into the company's existing workflow at any stage. RESbot has two settings. The "sensitive" setting identifies a higher number of possible RCTs with a lower risk of missing eligible studies, while the "precise" setting is more focused. For both settings, we estimated the reduction in resources required for record screening in two examples of RCT-only reviews.
RESULTS: Scoping searches in MEDLINE were conducted for SRs of RCTs in femoropopliteal artery diseases (FAD) and postpartum depression (PD). The results were run through RESbot. For the FAD SR, 1,444 references were retrieved, with the sensitive and precise RESbot settings reducing the record set by 38 percent and 64 percent, respectively. For the PD SR, a record set of 2,153 records was reduced by 25 percent and 41 percent, respectively. Resource savings offered by RESbot vary depending on subject but may reduce the time taken to screen records by up to 64 percent, with a subsequent reduction in cost to the organization commissioning the SR.
CONCLUSIONS: The use of bespoke machine learning tools in SR production has the potential to reduce the time and staff costs involved in producing a review. This case study tested the effect on a small number of records, but for larger reviews retrieving tens of thousands of records, reductions in time and costs can be very significant.
