ECONOMIC IMPACT OF DIGITAL HEALTH SOLUTIONS: INSIGHTS FROM PETERSON HEALTH TECHNOLOGY INSTITUTE ASSESSMENTS
Author(s)
Nikolina Boskovic, MPH1, Victoria Loo, BA, MPH2, Josh Carlson, MPH, PhD3, Adam Kasle, BA1;
1Curta, Washington, DC, USA, 2Peterson Health Technology Institute, New York, NY, USA, 3University of Washington, Seattle, WA, USA
1Curta, Washington, DC, USA, 2Peterson Health Technology Institute, New York, NY, USA, 3University of Washington, Seattle, WA, USA
OBJECTIVES: Digital health solutions have the potential to improve health and lower costs, but purchasers must consider how these solutions may impact healthcare spending. The Peterson Health Technology Institute (PHTI) addresses this gap by providing independent, evidence-based assessments evaluating the clinical and economic impact of digital health solutions. We aimed to provide an overview of methods and a synthesis of findings from the economic analyses in published PHTI assessments.
METHODS: The analysis set included five PHTI assessments: diabetes, musculoskeletal disorders (MSK), hypertension (HTN), depression/anxiety, and opioid use disorder (OUD). For each assessment, we characterized the structure of the economic analyses, the use of findings from the clinical assessments, the estimates on pricing for the digital health solutions, and key economic impact results.
RESULTS: Economic analyses were conducted for a total of 14 digital solution categories representing groups of similar solution interventions across five assessments (diabetes, n=3; MSK, n=3; HTN, n=3; anxiety/depression, n=3; OUD, n=2). The majority (11/14) of the analyses used clinical outcomes combined with data from external studies to model the relationship between clinical outcomes and healthcare costs, whereas three directly compared digital health solution resource utilization costs to in-person care costs. Pricing for the digital health solutions varied widely. All economic analyses estimated the change in spending over one year, except for the HTN analyses which projected long-term events and spending beyond three years. Seven digital health solution categories were found to increase net spending, four were cost-saving, two increased net spending initially with potential for long-term savings, and one had insufficient pricing data to generate spending estimates.
CONCLUSIONS: The economic analyses supporting PHTI assessments provide informative evidence on the economic impact of digital health solutions that can help guide purchaser decision-making.
METHODS: The analysis set included five PHTI assessments: diabetes, musculoskeletal disorders (MSK), hypertension (HTN), depression/anxiety, and opioid use disorder (OUD). For each assessment, we characterized the structure of the economic analyses, the use of findings from the clinical assessments, the estimates on pricing for the digital health solutions, and key economic impact results.
RESULTS: Economic analyses were conducted for a total of 14 digital solution categories representing groups of similar solution interventions across five assessments (diabetes, n=3; MSK, n=3; HTN, n=3; anxiety/depression, n=3; OUD, n=2). The majority (11/14) of the analyses used clinical outcomes combined with data from external studies to model the relationship between clinical outcomes and healthcare costs, whereas three directly compared digital health solution resource utilization costs to in-person care costs. Pricing for the digital health solutions varied widely. All economic analyses estimated the change in spending over one year, except for the HTN analyses which projected long-term events and spending beyond three years. Seven digital health solution categories were found to increase net spending, four were cost-saving, two increased net spending initially with potential for long-term savings, and one had insufficient pricing data to generate spending estimates.
CONCLUSIONS: The economic analyses supporting PHTI assessments provide informative evidence on the economic impact of digital health solutions that can help guide purchaser decision-making.
Conference/Value in Health Info
2026-05, ISPOR 2026, Philadelphia, PA, USA
Value in Health, Volume 29, Issue S6
Code
EE417
Topic
Economic Evaluation
Topic Subcategory
Budget Impact Analysis
Disease
No Additional Disease & Conditions/Specialized Treatment Areas