Progress and innovation in artificial intelligence (AI)-based healthcare interventions continue to develop rapidly. However, there are limitations in the published health economic evaluations (HEEs) of AI interventions, including limited reporting on characteristics and development of algorithms. We developed an extension to the existing Consolidated Health Economic Evaluation Reporting Standards (CHEERS) to improve consistency, transparency, and reliability of the reporting of HEEs of AI interventions.

The Delphi method was used, following a prespecified study protocol. A steering group with expert oversight was formed to guide the development process. A long list of potential items was defined based on two recent systematic reviews of HEEs of AI-based interventions. The steering group identified and invited 119 experts to the three-stage survey. Participants were asked to score each item on a nine-point Likert scale, and they were also able to provide free-text comments. The final checklist was piloted on a random sample of nine HEEs of AI-based interventions.

Three stages of the Delphi survey were completed by 58, 42, and 31 multidisciplinary respondents, respectively, including HTA specialists, health economists, AI experts, and patient representatives. The CHEERS-AI extension includes 18 AI-specific reporting items. Ten are entirely new items, including considerations about user autonomy, validation of the AI component, and AI-specific uncertainty. In addition, elaborations on eight existing CHEERS items were added to emphasize important AI-specific nuances. Some participants highlighted that CHEERS-AI can provide key benefits; for example, it could clarify the misconception that the predictive algorithms supporting AI-driven healthcare interventions are available for use without cost.

CHEERS-AI can aid in improved reporting quality for researchers, editors, and reviewers conducting or assessing HEEs of AI interventions.

The National Health Service (NHS) in England aims to be carbon neutral by 2045, acknowledging the link between planetary and human health. By 2028, NHS suppliers will need to report carbon footprint data for their products, including the medicines and technologies that the National Institute for Health and Care Excellence (NICE) appraises. Additionally, company level data are already being reported. This type of data may provide NICE with an opportunity to support system environmental sustainability goals.

The NICE Science Policy and Research team conducted an options appraisal to consider the feasibility and acceptability of different ways NICE might engage with environmental impact data (EID). We held discussions with NICE teams that could be affected by the collection and use of EID. Discussions examined the array of potential options for NICE—from being a simple conduit for EID to incorporating EID into its decision-making—and sought to identify those that were practical for further consideration. We then discussed these options with key external stakeholders (NHS England, industry, and commissioners) to understand their expected usefulness and practicality.

Several options for NICE to use EID were identified as suitable for further consideration. Using company level data, NICE could encourage companies to engage with NHS sustainability goals by citing their carbon reduction plans alongside guidance or using them to prioritize its activities. Using product level data, NICE could pilot an evaluation comparing the environmental outcomes of competing health technologies that have no differential direct health outcomes. NICE could also publish environmental impact assessment tools to help commissioners consider EID in procurement decisions. Better data and methodological standards are needed before NICE might consider embedding product-level EID in its usual decision-making frameworks.

Our options appraisal has identified several ways that NICE might start to engage with EID to have a positive impact on NHS sustainability goals and wider planetary health. Future work will scope out how these activities should proceed. The identified options are not necessarily mutually exclusive and may evolve as the data and methods around sustainable health care continue to advance.

The COVID-19 pandemic put substantial strain on healthcare systems globally. Early decision-making about diagnostic tests and treatments was driven by the need for rapid responses with a focus on reducing clinical burden. As COVID-19 continues its transition into an endemic state, health technology assessment (HTA) agencies will need to consider the clinical- and cost-effectiveness of tests and treatments, as with other conditions.

We first conducted a systematic literature review in July 2021 and updated the search in July 2023. The review aimed to identify economic evaluations of diagnostics for SARS-CoV-2 and treatments for COVID-19 using predefined search strategy across journal databases and sources of grey literature. In the update, an additional targeted search was completed with terms relating to novel treatments. Search results were screened by title and abstract, and full texts of potentially relevant studies were reviewed against selection criteria. Studies with very serious methodological limitations were excluded. Findings from studies were synthesized narratively due to high levels of heterogeneity.

The database search identified 8,287 unique records, of which 54 full texts were reviewed, 28 were quality assessed, and 15 were included. Three further studies were included through HTA sources and citation checking. Of the 18 studies ultimately included, 16 evaluated pharmacological treatments including corticosteroids, antivirals, and immunotherapies. Two studies in lower-income settings evaluated the cost-effectiveness of rapid antigen tests and critical care provision. In most studies, a healthcare or payer perspective was used, and the comparator was standard care. There were 17 modeling analyses and one trial-based evaluation. Cost–utility analyses using QALYs were the most common analysis type.

This update indicates that there are cost-effective treatments for COVID-19, with repurposed pharmacological treatments like dexamethasone presenting best value. There also appear to be promising options for people with severe disease alongside standard care. Future economic evaluations would benefit from reflecting the changing context around COVID-19 with parameters that reflect current circumstances, and fully incremental analyses comparing different treatment options.

The sandbox approach, developed in the financial technologies sector, creates an environment to collaboratively develop and test innovative new products, methods and regulatory approaches, separated from business as usual. It has been used in health care to encourage innovation in response to emerging challenges, but, until recently, has not been used in health technology assessment (HTA). This article summarizes our learnings from using the sandbox approach to address three challenges facing HTA organizations and to identify implications for the use of this approach in HTA.

We identified three challenging contemporary HTA-related topics to explore in a sandbox environment, away from the pressures and interests of “live” assessments. We convened a pool of 120 stakeholders and experts to participate in various sandbox activities and ultimately co-develop solutions to help HTA organizations respond to the identified challenges.

Important general learnings about the potential benefits and implementation of a sandbox approach in HTA were identified. Consequently, we developed recommendations to guide its use, including how to implement an HTA sandbox in an effective way and the types of challenges for which it may be best suited.

For many HTA organizations, it is difficult to carefully consider emerging challenges and innovate their processes due to risks associated with decision errors and resource limitations. The sandbox approach could reduce these barriers. The potential benefits of addressing HTA challenges in a collaborative “safe space” are considerable.

To develop best-practice guidance for health technology assessment (HTA) agencies when appraising diagnostic tests for SARS-CoV-2 and treatments for COVID-19.

We used a policy sandbox approach to develop best-practice guidance for HTA agencies to approach known challenges associated with assessing tests and treatments for COVID-19. The guidance was developed by a multi-stakeholder workshop of twenty-one participants representing HTA agencies, clinical and patient experts, academia, industry, and a payer, from across Europe and North America. The workshop was supported by extensive background work to identify the key challenges, including: targeted reviews of existing COVID-related methods guidance for assessing interventions and clinical guidelines, engagement with clinical experts, a survey and workshop of HTA agencies, a systematic review of published economic evaluations, and a workshop of health economic modelers.

We suggest HTA agencies should consider using other types of evidence (e.g., real world) where high-quality randomized controlled trials may be lacking and healthcare systems would value timely HTA outputs. A “living” HTA approach may be useful, given the context of an evolving disease, scientific understanding and evidence base, allowing for decisions to be efficiently revisited in response to new information; particularly, if supported by a common “disease model” for COVID-19. Innovative ways of engaging with the public and clinicians, and early engagement with regulators and payers, are recommended.

HTA agencies should consider the elements of this guidance that are most suited to their existing processes to enable them to assess the effectiveness and value of interventions for COVID-19.

This review aims to assess the cost-effectiveness of psychological interventions for schizophrenia/bipolar disorder (BD), to determine the robustness of current evidence and identify gaps in the available evidence.

Electronic searches (PsycINFO, MEDLINE, Embase) identified economic evaluations relating incremental cost to outcomes in the form of an incremental cost-effectiveness ratio published in English since 2000. Searches were concluded in November 2018. Inclusion criteria were: adults with schizophrenia/BD; any psychological/psychosocial intervention (e.g., psychological therapy and integrated/collaborative care); probability of cost-effectiveness at explicitly defined thresholds reported. Comparators could be routine practice, no intervention, or alternative psychological therapies. Screening, data extraction, and critical appraisal were performed using pre-specified criteria and forms. Results were summarized qualitatively. The protocol was registered on the PROSPERO database (CRD42017056579).

Of 3,864 studies identified, 12 met the criteria for data extraction. All were integrated clinical and economic randomized controlled trials. The most common intervention was cognitive behavioral therapy (CBT, 6/12 studies). The most common measure of health benefit was the quality-adjusted life-year (6/12). Follow-up ranged from 6 months to 5 years. Interventions were found to be cost-effective in most studies (9/12): the probability of cost-effectiveness ranged from 35-99.5 percent. All studies had limitations and demonstrated uncertainty (particularly related to incremental costs).

Most studies concluded psychological interventions for schizophrenia/BD are cost-effective, including CBT, although there was notable uncertainty. Heterogeneity across studies makes it difficult to reach strong conclusions. There is a particular need for more evidence in the population with BD and for longer-term evidence across both populations.