Digital health technology companies are searching for the best route to assess and prove the total value of their products. Economic evaluation is a critical part of any strategy to break into US, European, and other world markets. This is particularly salient when pursuing financial reimbursement from government and commercial health plans or looking to use real-world evidence as part of contract negotiations.
However, the task of evaluating digital health interventions (DHI) is notoriously challenging compared to evaluating pharmaceuticals. Demonstrating the appropriate type of value to each stakeholder requires understanding the unique needs of health economics and outcomes research in the value assessment of digital health technologies.
With that understanding, digital health leaders can choose one or more economic evaluation methodologies to reflect their product and value objectives best. Here, we recommend using a combination of approaches that could include a budget impact assessment (BIA), a cost-effectiveness analysis (CEA), and a cost-consequence analysis (CCA).
These are the primary questions that health plan executives in the US and Europe want to answer regarding vetting and reimbursing for digital health technologies.
They want to ensure they make sound investment decisions, which they do through gathering comparative analysis data on one or more interventions in terms of costs, consequences, and impact.
The generation of economic evidence for the emerging digital health space is still in its infancy. Despite industry experts pointing to 95 frameworks for evaluating digital health, there are no evaluative standards, and the results can be disparate, inconsistent, and vary in quality.
While the economic evaluation of digital health products tends to rely heavily on the budget impact assessment, is conducting a BIA enough? In the US, CMS places a high priority on cost-effectiveness analysis. In Europe, authorities will not approve a digital health device without a cost-effectiveness analysis.
According to The International Society for Pharmacoeconomics and Outcomes Research (ISPOR), digital technologies have unique features that require a differentiated and tailored approach to economic evaluation compared with standard technologies like medicines and medical devices.
Some aspects of digital health technologies that require special consideration when evaluating include:
Medicines are typically evaluated for their clinical effectiveness, cost, toxicity, or side effects. In contrast, the evaluation of digital health interventions should account for efficacy and clinical safety as well as the provider and patient user experience, technical stability, interoperability, and data privacy.
The complexity of DHI necessitates considering these unique aspects when choosing evaluative methodologies that study items like the choice of comparator, study perspective, cost measurement, benefits, and type of economic analysis.
According to a 2022 article in Pharmacoeconomics, “The implications of the distinctive nature of DHIs for the methodological choices underpinning their economic evaluation is not well understood." Gomes et al. suggest that rather than taking the typical approach—including a health service perspective, focusing on health-related benefits, and adopting cost-utility analyses—digital health producers and their prospective customers look to complementary and novel approaches to evaluate value.
Table 1 highlights the key differences when comparing pharmaceuticals, medical devices, and DHIs, along with the implications of each variable to consider in economic evaluation.
Gomes, M., Murray, E., & Raftery, J. (2022). Economic Evaluation of Digital Health Interventions: Methodological Issues and Recommendations for Practice. PharmacoEconomics, 40(4), 367–378. https://doi.org/10.1007/s40273-022-01130-0
The CDC's 2021 report, Applied Economic Evaluation of Digital Health Interventions, distinguishes various types of analyses. The report looks at how technology benefits accrue from implementing a digital health intervention. It notes that it is “common for studies to use multiple methods and that there is often a lack of methodological purity or clarity about studies as reported in the literature."
This is backed by research by the World Bank's Framework for the Economic Evaluation of Digital Health Interventions published in 2023. Their framework consists of 5 steps: assessing a DHI's context, intervention type, level of complexity, analytic principles, and value proposition.
Other approaches, mainly those Gomes et al. referenced earlier, focus on the following:
Ultimately, any economic evaluation should account for its place in a relevant healthcare pathway—impacting individual health as well as operational benefits—along with digital health product's general lifecycle.
Here are 3 economic evaluation models that may best assess different types of digital health value and also account for the unique aspects of digital health tools.
Budget impact analysis estimates the expected change in expenditures once the new technology is adopted and implemented. Used for budget and resource planning, it compares the costs of healthcare post-intervention against those in the pre-intervention environment. The difference reflects the budget impact.
Commonly used as a go-to model for digital health tools, BIA is typically performed after an intervention is deemed cost-effective. Therefore, the BIA determines an intervention's fiscal feasibility or affordability.
Cost-effectiveness analysis highlights the costs and effects of a DHI compared to a minimum of 1 alternative intervention. The comparison is reflected as a ratio of incremental cost to incremental benefits. These outcomes are shown as natural units, such as disease cases avoided, years of life gained, quality-adjusted life-years (QALYs), or disability-adjusted life-years (DALYs).
Cost-effectiveness analysis estimates benefits using natural units, such as life years gained or cases of illness averted, or units that integrate effects on health and longevity, such as QALYs or DALYs.
Essentially, CEA is a measure of value, demonstrating how much benefit is achieved for each unit of DHI cost. Cost-effectiveness complements BIA because the first looks at benefit and cost, and the latter looks at affordability based on budget constraints.
Combined, these two approaches determine whether a digital health technology is a good value for money and whether the budget is available.
The third methodology is cost-consequences analysis, which is recommended by The National Institute for Health and Care Excellence (NCIE).
Cost-consequences analysis (CCA) considers a broad range of DHI costs and effects being compared and reports them individually. This approach presents disaggregated measures across all health and non-health impacts aligned with their impact inventory.
Decision makers and those reviewing evaluation data can choose which costs and consequences are most relevant to their patient-members, populations, markets, and priorities. This enables digital health companies to focus their assessment on specific aspects that align with their desired market, emphasizing what is most valuable to prospective payers.
CCA offers a multidimensional list of outcomes and asks the assessor to decide which benefits are most desirable. This approach is particularly suited for evaluating complex interventions or when novel variables are essential to the customer.
Combined with the first two approaches, CCA rounds out the analysis, providing the most significant customization based on the stakeholder's specific objectives.
When vetting and selecting an economic evaluation model to assess a digital health technology, the message is clear: one approach won't highlight all aspects of value. Here, we've presented three models that offer distinct elements of value and complement each other. When combined, these approaches ensure that a DHI's value is demonstrated from each stakeholder's perspective.
If you are a digital health company looking to create compelling evidence for reimbursement, market assessment, and contract negotiations, we can help. Our team includes HEOR experts, digital health technologists, data scientists, and healthcare industry consultants who work together to map a straightforward approach for evidence generation, including data collection and study design. Contact us.
