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Realising the broader value of vaccines in the UK.

ABSTRACT: Many health technology assessment (HTA) agencies limit their assessments of vaccines to the health benefits for the vaccinated individual, the costs associated with vaccine administration and the disease avoided. However, because the value of vaccines tends to accrue to a large extent beyond the vaccinated individual, they are systematically undervalued in many current HTA processes. This is also the case in the UK, where the Joint Committee on Vaccination and Immunisation (JCVI) is in charge of assessing preventative vaccines, while therapeutic vaccines fall in the realm of the National Institute for Clinical Excellence (NICE). To contribute to a forward-looking perspective, we designed a framework to capture the broader value of vaccination. We reviewed the current state of the global vaccines pipeline and selected seven preventative and three therapeutic vaccines that are likely to enter the UK market within five years. We assessed on which value elements the selected vaccines would potentially generate value, and compared those against the novel broader value framework. A review of the current value elements considered by the JCVI and NICE allowed identifying the critical gaps between potential value generation and value recognition. To our knowledge, this is the first time that the broader value of vaccination has been pro-actively assessed for pipeline vaccinations. Our findings show that the existing narrow evaluation frameworks are likely to systematically undervalue the value of potential future vaccines coming to the UK market. This is particularly relevant, where their impact on AMR and other health interventions, and on the productivity of the workforce is of concern. Recommendations to overcome this include an explicit and more consistent inclusion of, and data collection on, the impact of vaccines on AMR and other health interventions by JCVI and NICE; the consideration of a societal perspective and the fiscal impact of vaccines to societies.

SUBMITTER: Brassel S

PROVIDER: S-EPMC8099625 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe COVID-19 pandemic shows that the impact of effective vaccines can extend well beyond vaccinated individuals and healthcare systems. Yet, these broader value elements are not typically considered in Health Technology Assessment (HTA) which may underestimate vaccines' broader value.ObjectivesThis study aimed to (1) describe the gap between broader value elements identified in value frameworks for vaccines and those recognised in HTA of vaccines in nine developed markets, and (2) develop expert-informed, consensus-based recommendations on how hurdles for broader value recognition could be overcome.MethodsWe used a four-step modified Delphi method consisting of literature research (phase I, pearl-growing approach using PubMed Web of Science and Google covering the years 2000-2019), two consecutive phases of expert elicitation (phase II and III, including two email surveys and one virtual round table with 10 experts from 9 countries) and synthesis of recommendations (phase IV).ResultsResults show that about half of the broader value elements relevant to vaccines are not (consistently) considered in HTA processes of multiple higher-income countries. Experts identified five priority areas for broader value recognition, including considering (1) more comprehensive cost offsets within the health care system, (2) carer quality of life, (3) transmission value, (4) prevention of antimicrobial resistance and (5) macroeconomic effects.ConclusionTo achieve a broader recognition of the value of vaccines, a three-pronged approach was recommended, focusing on (1) Evidence: proactively steering generation of high-quality evidence to quantify the broader value of vaccines to society; (2) Ability: leveraging and further developing existing methodological and analytic expertise to appropriately recognise the broad value of vaccines within HTA processes; (3) Willingness: Stimulating stakeholder engagement to change the status quo and move towards more transparent and comprehensive value assessment processes for vaccines globally.

Project description:RationaleClinical trials are the gold standard for testing interventions. COVID-19 has further raised their public profile and emphasised the need to deliver better, faster, more efficient trials for patient benefit. Considerable overlap exists between data required for trials and data already collected routinely in electronic healthcare records (EHRs). Opportunities exist to use these in innovative ways to decrease duplication of effort and speed trial recruitment, conduct and follow-up.ApproachThe National Institute of Health Research (NIHR), Health Data Research UK and Clinical Practice Research Datalink co-organised a national workshop to accelerate the agenda for 'data-enabled clinical trials'. Showcasing successful examples and imagining future possibilities, the plenary talks, panel discussions, group discussions and case studies covered: design/feasibility; recruitment; conduct/follow-up; collecting benefits/harms; and analysis/interpretation.ReflectionSome notable studies have successfully accessed and used EHR to identify potential recruits, support randomised trials, deliver interventions and supplement/replace trial-specific follow-up. Some outcome measures are already reliably collected; others, like safety, need detailed work to meet regulatory reporting requirements. There is a clear need for system interoperability and a 'route map' to identify and access the necessary datasets. Researchers running regulatory-facing trials must carefully consider how data quality and integrity would be assessed. An experience-sharing forum could stimulate wider adoption of EHR-based methods in trial design and execution.DiscussionEHR offer opportunities to better plan clinical trials, assess patients and capture data more efficiently, reducing research waste and increasing focus on each trial's specific challenges. The short-term emphasis should be on facilitating patient recruitment and for postmarketing authorisation trials where research-relevant outcome measures are readily collectable. Sharing of case studies is encouraged. The workshop directly informed NIHR's funding call for ambitious data-enabled trials at scale. There is the opportunity for the UK to build upon existing data science capabilities to identify, recruit and monitor patients in trials at scale.

Project description:BackgroundStratified or personalised medicine targets treatments for groups of individuals with a disorder based on individual heterogeneity and shared factors that influence the likelihood of response. Psychiatry has traditionally defined diagnoses by constellations of co-occurring signs and symptoms that are assigned a categorical label (e.g. schizophrenia). Trial methodology in psychiatry has evaluated interventions targeted at these categorical entities, with diagnoses being equated to disorders. Recent insights into both the nosology and neurobiology of psychiatric disorder reveal that traditional categorical diagnoses cannot be equated with disorders. We argue that current quantitative methodology (1) inherits these categorical assumptions, (2) allows only for the discovery of average treatment response, (3) relies on composite outcome measures and (4) sacrifices valuable predictive information for stratified and personalised treatment in psychiatry.Methods and findingsTo achieve a truly 'stratified psychiatry' we propose and then operationalise two necessary steps: first, a formal multi-dimensional representation of disorder definition and clinical state, and second, the similar redefinition of outcomes as multidimensional constructs that can expose within- and between-patient differences in response. We use the categorical diagnosis of schizophrenia-conceptualised as a label for heterogeneous disorders-as a means of introducing operational definitions of stratified psychiatry using principles from multivariate analysis. We demonstrate this framework by application to the Clinical Antipsychotic Trials of Intervention Effectiveness dataset, showing heterogeneity in both patient clinical states and their trajectories after treatment that are lost in the traditional categorical approach with composite outcomes. We then systematically review a decade of registered clinical trials for cognitive deficits in schizophrenia highlighting existing assumptions of categorical diagnoses and aggregate outcomes while identifying a small number of trials that could be reanalysed using our proposal.ConclusionWe describe quantitative methods for the development of a multi-dimensional model of clinical state, disorders and trajectories which practically realises stratified psychiatry. We highlight the potential for recovering existing trial data, the implications for stratified psychiatry in trial design and clinical treatment and finally, describe different kinds of probabilistic reasoning tools necessary to implement stratification.

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Realising the broader value of vaccines in the UK.

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