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  • Evidence Syntheses and Value Assessment of Digital Health Interventions

    Evidence Syntheses and Value Assessment of Digital Health Interventions

    Digital health interventions (DHIs) are changing the care delivery and experience. However, the speed of innovation often overtakes the ability to assess what truly works. Therefore, evidence syntheses and value assessments are crucial in helping researchers, clinicians, and policymakers identify solutions that deliver meaningful impact.(1, 2)

    Evidence from systematic reviews has frequently shown DHIs to exhibit strong usability, safety, acceptability, and favourable clinical advantages, especially when rooted in user-centred design and supplemented by human interaction. However, evidence for long-term efficacy, cost-effectiveness, and scalable real-world application continues to be varied. This inconsistency highlights the need for context-aware assessments, which also focus on user experience, equity, and workflow integration as much as measured outcomes.(1, 3, 4)

    For clarity, researchers are increasingly turning to umbrella reviews, rapid assessments, and scoping reviews, and evidence gap maps (EGMs) to synthesize what is known and identify where major gaps persist.(5) These syntheses also underscore persisting challenges, including heterogeneous study designs, variable outcome measures, and diverse intervention components, which restrict comparability across studies. Consequently, modern assessments emphasize systematized reporting, transparent risk-of-bias evaluations, and alignment with the complete patient journey.(4, 6)

    Value assessment is central to digital health decision-making. Beyond clinical outcomes, value includes user-friendliness, cost-effectiveness, equity, and system-level advantages. Although frameworks categorize these components, they are not uniformly applied in empirical research, which warrants practical measures and economic models that depict real-world conditions.(4, 6)

    The success of DHIs also depends on engagement and adherence; however, engagement doesn’t always guarantee better outcomes.(6, 7) Effective solutions must alleviate burden, fit seamlessly into daily routines, and sustain user motivation, elements that are increasingly being captured in contemporary evidence syntheses.(4-6)

    Furthermore, economic evaluation of DHIs adds another layer of complexity. Digital tools are associated with unique costs, including development, maintenance, interoperability, cybersecurity; while also including benefits that grow over time. Standardized methods, scenario analyses, and sensitivity testing are crucial for generating credible, policy-relevant insights.(8, 9)

    Implementing DHIs is a crucial bridge between evidence and practice. EGMs and implementation frameworks help pinpoint where robust research exists and where more work is needed to strengthen adoption, reliability, and sustainability.(4, 5) Quality, safety, and equity are equally non-negotiable components. Systematic reviews increasingly highlight privacy and security risks and explore differential effects across sociodemographic groups to ensure digital tools do not increase disparities. Transparent reporting and robust appraisal improve trust that guide responsible decision-making.(1, 2)

    Finally, consistent, meaningful assessments will help stakeholders recognize high-value digital health solutions while facilitating safe, equitable, and impactful innovation. With evolving methods, evidence will continue to shape, not just validate, the future of digital health.

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    References

    1. Merino M, Del Barrio J, Nuño R, Errea M. Value-based digital health: A systematic literature review of the value elements of digital health care. Digit Health. 2024; 10:20552076241277438.
    2. Liu S, Ma J, Sun M, et al. Mapping the Landscape of Digital Health Intervention Strategies: 25-Year Synthesis. J Med Internet Res. 2025; 27:e59027.
    3. Rauschenberg C, Schick A, Hirjak D, et al. Evidence Synthesis of Digital Interventions to Mitigate the Negative Impact of the COVID-19 Pandemic on Public Mental Health: Rapid Meta-review. J Med Internet Res. 2021; 23(3):e23365.
    4. Milne-Ives M, Homer SR, Andrade J, Meinert E. Mapping the Process of Engagement With Digital Health Interventions: A Cross-Case Synthesis. Mayo Clin Proc Innov Qual Outcomes. 2025; 9(3):100625.
    5. Campbell, F., Tricco, A.C., Munn, Z. et al. Mapping reviews, scoping reviews, and evidence and gap maps (EGMs): the same but different – the “Big Picture” review family. Syst Rev. 2023; 12:45.
    6. Iwakura M, Ozeki C, Jung S, et al. An umbrella review of efficacy of digital health interventions for workers. npj Digit. Med. 2025; 8:207.
    7. Sun S, Simonsson O, McGarvey S, et al. Mobile phone interventions to improve health outcomes among patients with chronic diseases: an umbrella review and evidence synthesis from 34 meta-analyses. The Lancet Digital Health. 2024; 6(11):e857-e870.
    8. Gomes M, Murray E, Raftery J. Economic Evaluation of Digital Health Interventions: Methodological Issues and Recommendations for Practice. Pharmacoeconomics. 2022; 40(4):367-378.
    9. Wilkinson T, Wang M, Friedman J, Görgens M. A Framework for the Economic Evaluation. Policy Research Working Paper; World Bank Group. 2023. Accessed online at: https://documents1.worldbank.org/curated/en/099446504122313917/pdf/IDU0f639726d0f11404a3509af8054677649dcd6.pdf

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  • Selecting Appropriate Review Approach for HTA Submissions

    Selecting Appropriate Review Approach for HTA Submissions

    Formulating Fit-for-Purpose Evidence Packages to Demonstrate the Value of Interventions for Rare Diseases

    Health Technology Assessments (HTAs) heavily rely on vigorous evidence synthesis. As a result, the selection of review methodology for evidence generation is an essential early step in the HTA process. This selection usually depends on the research question, nature and extent of existing evidence, and assessment timelines.(1) Three distinct approaches for reviewing existing evidence include de novo systematic review, an update of an existing review, and an overview of systematic reviews.(1, 2)

    A de novo systematic review is performed when no reliable review is available on the topic, or when the available ones are outdated, incomplete, or methodologically weak. This method enables an exhaustive and unbiased evaluation of the evidence from scratch, allowing for the customization of inclusion criteria, quality appraisal, and data synthesis as per the specific HTA’s objectives. This is also the most resource-consuming option, demanding substantial time and effort to select and analyse the relevant literature.(2-4)

    An update of an existing systematic review may be performed if a high-quality review is already present in public domain; here the objective would be to update the evidence using publications reported after the publication of the review. In rapidly evolving therapeutic areas with frequently emerging trials and interventions, updating an existing review provides efficiency while preserving the integrity of the evidence. This approach facilitates HTA bodies to expand on prior work, integrate new data, and improve inferences without repeating the entire review process.(2, 4, 5) In this context, the use of living systematic reviews (living SLRs), which are constantly updated with new and upcoming evidence, can also be explored. By integrating real-time updates, living SLRs minimize the delay between research publication and evidence generation, making them especially important in dynamic therapeutic areas where well-timed decisions are crucial.(6, 7)

    An overview of systematic reviews, often referred to as an umbrella review, is apt when multiple high-quality reviews have already been performed on closely related interventions or outcomes. This methodology incorporates findings across reviews, focusing on not just consistencies but also differences and evidence gaps. It is especially important when HTAs are required to assess wide-ranging policy questions or making decisions encompassing multiple treatment options, therapeutic areas, or patient subgroups. By incorporating insights across systematic reviews, their overviews offer an enhanced understanding of the evidence setting that guides strategic decision-making.(2, 3, 8)

    In some cases, selection of other types of reviews may also be applicable. For instance, scoping reviews can be especially beneficial during the exploratory phase, where the aim is to determine the scope of available evidence, elucidate concepts, or characterize knowledge gaps before providing final answers. Such scoping reviews help refine research questions and assess if a full systematic review is needed.(1) On the other hand, rapid reviews are used when HTA-relevant decisions must be made under strict timelines (e.g., during public health emergencies or early advice procedures), in which conventional systematic review steps are streamlined while preserving transparency. In contrast, targeted literature reviews are applied in narrower contexts, such as epidemiology assessments or comparator identification, where a structured but not fully systematic evidence synthesis is sufficient. However, both rapid and targeted reviews are generally less favoured in HTA because their methodological shortcuts increase the risk of bias and limit reproducibility compared with full systematic reviews.(9, 10) Agencies like Canadian Agency for Drugs and Technologies in Health (CADTH) are leading the development of practical guidance on when each review approach is most suitable, facilitating global HTA agencies to approve fit-for-purpose methods.(2)

    Finally, the selection of any of these review types should be based on the scope of the HTA, available timelines, and the state of the evidence landscape. A rationalized decision not only facilitates methodological strength but also improves the integrity and relevance of the HTA’s recommendations. With the expanding evidence network, careful selection of the review approaches will continue to be essential for accomplishing timely, efficient, and impactful HTAs.

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    References

    1. Nemzoff C, Shah HA,  Heupink LE, et al. Adaptive Health Technology Assessment: A Scoping Review of Methods. Value Health. 2023; 26(10):P1549-1557.
    2. Kim JSM, Pollock M, Kaunelis D, Weeks L. Guidance on review type selection for health technology assessments: key factors and considerations for deciding when to conduct a de novo systematic review, an update of a systematic review, or an overview of systematic reviews. Syst Rev. 2022; 11(1):206.
    3. Pollock M, Fernandes RM, Becker LA, et al. What guidance is available for researchers conducting overviews of reviews of healthcare interventions? A scoping review and qualitative metasummary. Syst Rev. 2016;5(1):190.
    4. Cumpston M, Chandler J, et al. Chapter IV: Updating a review. In: Higgins J, Thomas J, Chandler J, et al., editors. Cochrane Handbook for Systematic Reviews of Interventions. Version 6.2 (updated February 2021) London: Cochrane; 2021.
    5. Garner P, Hopewell S, Chandler J, et al. When and how to update systematic reviews: consensus and checklist. BMJ. 2016; 354:i3507.
    6. Simmonds M, Elliott JH, Synnot A, Turner T. Living Systematic Reviews. Methods Mol Biol. 2022; 2345:121-134.
    7. Sauca M, Tarchand R, Kallmes K. Living SLRs for HTA. ISPOR Europe 2023. [Accessed online on 1st Sept 2025]. Available at: https://www.ispor.org/docs/default-source/euro2023/isporeurope23saucahta361poster-129656-pdf.pdf?sfvrsn=ca7a753b_0
    8. Pollock M, Fernandes RM, Becker LA, Pieper D, Hartling L. Chapter V: Overviews of reviews. In: Higgins JPT, Thomas J, Chandler J, et al., Cochrane Handbook for Systematic Reviews of Interventions. Version 6.2 (updated February 2021). London: Cochrane; 2021.
    9. Kaltenthaler E, Cooper K, Pandor A, et al. The use of rapid review methods in health technology assessments: 3 case studies. BMC Med Res Methodol. 2016; 16(1):108.
    10. Watt A, Cameron A, Sturm L, et al. Rapid reviews versus full systematic reviews: an inventory of current methods and practice in health technology assessment. Int J Technol Assess Health Care. 2008; 24(2):133-9.

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