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Frontiers in digital health · 2026

Health economic evaluations of digital health technologies-a rapid review of applied methods.

СтатьяОбзорНазвание и аннотация: Перевод в очереди
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Campione Alessandro, Zetzsche Milan, Rombey Tanja, Rödiger Hendrikje, Henschke Cornelia

Аннотация

INTRODUCTION: Digital health technologies (DHTs) offer significant potential to improve healthcare delivery, efficiency and outcomes. Despite increasing uptake, their full potential remains underused, partly because existing approaches and regulatory frameworks for generating economic evidence are not yet adequately adapted to the specific characteristics of DHTs.

METHODS: This rapid review examined methods applied in economic evaluations (EEs) of DHTs of studies published between 2020 and 2024. Following Cochrane guidelines, searches were performed in PubMed and Scopus, yielding 1254 unique records, of which 51 primary studies met inclusion criteria. Methodological characteristics, including general and EE-specific aspects, were stratified by EE type and underlying study design, distinguishing between EEs as a primary or secondary objective and model-based EEs. The included studies were assessed using RoB2, ROBINS-I, CHEQUE, and CHEERS-(AI).

RESULTS: Most EEs were based on randomized controlled trials, and employed conventional methods developed for non-DHT interventions. The included EEs showed considerable heterogeneity in perspectives, cost categories, and handling of uncertainty. Reporting and methodological quality were inconsistent, including incomplete descriptions of the DHTs. Key limitations included limited study registration and transparency, and bias from underlying studies, particularly when multiple data sources were used. Important DHT-specific aspects, such as technology life cycles and real-world transferability across user groups, were rarely addressed.

DISCUSSION: The findings highlight a fragmented landscape of methodological and reporting practices and underscore the need for adequately adapted, DHT-specific economic evaluation methods that better reflect the unique characteristics of DHTs and generate robust, decision-relevant evidence.

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

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