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Integrating Patient Perspectives Into the Digital Health Technology Readiness Framework: Delphi Study
Elisenda de la Torre1, Cristina Montane1, Olga Rubio2
1Patient Advocate, Barcelona, Spain.
This study developed the PULSO-Tech-Clinic Model, integrating patient perspectives into technology readiness levels (TRLs) for digital health innovations. This patient-centered framework enhances usability, acceptance, and effectiveness of digital health tools.
Area of Science:
- Digital Health
- Health Technology Assessment
- Patient-Centered Care
Background:
- Digital health technologies are transforming healthcare delivery, improving access, personalization, and efficiency.
- Traditional technology readiness levels (TRLs) lack explicit consideration of patient involvement, crucial for real-world effectiveness.
- Patient engagement is essential for the usability and acceptance of digital health innovations.
Purpose of the Study:
- To integrate patient perspectives into the TRLs framework for digital health innovations.
- To develop a patient-centered dimension for assessing digital health technologies.
- To enhance the usability, acceptance, and real-world effectiveness of digital health solutions.
Main Methods:
- A Delphi methodology involving 24 Spanish-speaking experts from diverse fields was employed.
- Experts evaluated patient involvement across 10 TRL stages using a 6-point Likert scale.
- Two iterative rounds were conducted to refine statements and achieve consensus (≥75% agreement, mean score ≥4.5).
Main Results:
- Consensus was achieved in round 1 for all 10 TRL statements, with mean scores ranging from 4.70 to 5.25.
- A second round refined statements, increasing agreement and incorporating precise patient roles in development and evaluation.
- The framework integrates patient-reported measures into TRLs 5, 7, and 8, with high agreement on key refinements.
Conclusions:
- The PULSO-Tech-Clinic Model is the first framework to systematically embed patient perspectives within TRLs.
- This validated, patient-centered model enhances the design, evaluation, and adoption of digital health technologies.
- Further research is needed to evaluate the model's adaptability across diverse healthcare systems.
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