How to design digital health interventions with artificial intelligence: A scoping review - Scorecard - MDSpire
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Developing AI-Driven Digital Health Solutions: A Comprehensive Scoping Review

  • By

  • Shuimei Liu

  • L. Raymond Guo

  • September 12, 2026

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Clinical Scorecard: Developing AI-Driven Digital Health Solutions: A Comprehensive Scoping Review

At a Glance

CategoryDetail
ConditionAI-Driven Digital Health Solutions
Key MechanismsIntegration of Generative AI and Large Language Models in health tool design and development.
Target PopulationDiverse patient populations with heterogeneous needs.
Care SettingDigital health interventions and health informatics.

Key Highlights

  • AI is transitioning from a product to a collaborative design agent in digital health.
  • Generative AI tools are reshaping prototyping workflows and patient engagement.
  • A systematic scoping review was conducted to explore AI's roles in health design methodologies.
  • Existing literature lacks comprehensive insights into AI's operational workflows in health tool design.
  • A practical framework for incorporating AI agents in health informatics is proposed.

Guideline-Based Recommendations

Diagnosis

    Management

      Monitoring & Follow-up

        Risks

          Patient & Prescribing Data

          Not specified; focuses on diverse patient populations.

          Emphasizes the need for culturally adaptive health content co-created with marginalized communities.

          Clinical Best Practices

          • Incorporate human-in-the-loop validation stages in AI-driven design workflows.
          • Utilize established frameworks like CONSORT-AI and SPIRIT-AI for assessing AI models.

          Related Resources & Content

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