Decoding Digital Therapeutics: A Qualitative Analysis of Software Features in German Digital Health Applications.

Area of Science:

• Digital health
• Medical informatics
• Software engineering

Background:

• Digital therapeutics (DTx) show promise for patient care.
• The specific functional components and their interactions within DTx are not well understood.
• A systematic analysis of DTx features is needed to clarify their building blocks.

Purpose of the Study:

• To systematically analyze and categorize the functional features of digital therapeutics.
• To develop a framework for understanding the components and interactions within DTx.
• To differentiate between core therapeutic components (active ingredients) and supporting elements (excipients) in DTx.

Main Methods:

• Systematic analysis of 197 distinct features across 35 different DTx.
• Clustering of features into 19 themes.
• Organization of themes into six overarching dimensions.
• Classification of features as digital active ingredients or excipients.

Main Results:

• Identification and clustering of 197 unique features within 35 DTx.
• Organization of features into 19 distinct themes and six broader dimensions.
• Distinction established between digital active ingredients and excipients within DTx.
• A comprehensive framework detailing the interactions of DTx components was developed.

Conclusions:

• The study provides a structured understanding of the functional elements comprising digital therapeutics.
• The framework differentiates core therapeutic components from supporting features, aiding in DTx design and evaluation.
• These insights advance the foundational knowledge of DTx, supporting further development and stakeholder understanding.