Evidence DEFINED
Evidence DEFINED is a framework designed to help organizations quickly and rigorously assess the evidence for digital health interventions. It focuses on what matters most in real-world decision-making, offering a streamlined process that balances thoroughness with speed. It includes a checklist and guidance on how strong the evidence should be before adopting a digital health tool.
At a glance
Use when
Assessing evidence for digital health interventions in payer, health system, or policy settings where timely, rigorous decisions are needed; supporting evidence generation by developers aiming for real-world adoption.
Avoid when
Conducting comprehensive health technology assessments requiring full economic evaluation or deep organizational impact analysis; when detailed safety or long-term outcomes are the primary concern and rapid assessment is not a priority.
Inputs
Evidence from studies on digital health interventions, including study design, quality, outcomes, and context; regulatory information; implementation data.
Outputs
Structured assessment of evidence quality, checklist-based evaluation, evidence-to-recommendation guidance, and suggested adoption level based on evidence strength.
How it works
The Evidence DEFINED (Evidence in Digital health for EFfectiveness of INterventions with Evaluative Depth) framework addresses gaps in existing digital health evidence assessment methods by incorporating digital-specific considerations, heightened evidence quality criteria aligned with current regulatory expectations, and adaptation of robust methodologies from non-digital interventions. It enhances rigor while enabling rapid assessment through optimized screening and deprioritization of low-value steps. The framework includes a Quick Start Guide, a high-priority evidence checklist, and evidence-to-recommendation guidelines that map evidence quality to appropriate levels of adoption. It supports standardized evaluation of digital health interventions for stakeholder organizations and informs evidence generation strategies for developers.
- HTA domains
- Clinical Effectiveness, Organisational aspects, Patient and Social Aspects
- Assumptions
- That digital health interventions require tailored evidence assessment approaches due to their unique characteristics; that decision-makers need both speed and rigor; and that existing frameworks do not adequately address regulatory and methodological challenges in digital health.
- Strengths
- Balances rigor and speed; addresses digital-specific evidence considerations; incorporates robust methodologies from non-digital fields; provides actionable guidance for adoption; includes tools like a checklist and Quick Start Guide for real-world use.
- Limitations
- May deprioritize certain evaluation steps to achieve speed, potentially overlooking nuanced aspects of evidence; focused primarily on effectiveness and adoption, with less emphasis on cost or organizational integration.
- Also known as
- Evidence DEFINED Framework, Evidence in Digital health for EFfectiveness of INterventions with Evaluative Depth
Questions this answers
- › How strong is the evidence supporting a digital health intervention's effectiveness?
- › What are the key evidence considerations unique to digital health that should be evaluated?
- › What level of evidence is sufficient to support adoption of a digital health intervention?
- › How can organizations streamline evidence assessment without sacrificing rigor?
- › Are there regulatory and methodological gaps in current digital health evidence reviews?
- › How can digital health developers generate evidence that supports real-world adoption?
References & sources
Similar by meaning
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