Evidence map›Paper›PMID 40835414›Full record

ArticleJournal of medical Internet research2025

Integrating Patient Perspectives Into the Digital Health Technology Readiness Framework: Delphi Study.

Elisenda de la Torre, Cristina Montane, Olga Rubio, Laura Sampietro-Colom, Araceli Camacho-Mahamud, Inmaculada Grau-Corral

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Management of Chronic Health Situations.Healthcare (Basel, Switzerland) · 2026
    Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Elisenda de la TorrePatient Advocate, Barcelona, Spain.ORCID http://orcid.org/0009-0007-5006-9558
Cristina MontanePatient Advocate, Barcelona, Spain.ORCID http://orcid.org/0009-0006-6890-9490
Olga RubioHospital Clínic de Barcelona, Villarroel 170, Barcelona, 08036, Spain.ORCID http://orcid.org/0000-0001-5159-1793
Laura Sampietro-ColomHospital Clínic de Barcelona, Villarroel 170, Barcelona, 08036, Spain.ORCID http://orcid.org/0000-0001-7182-0231
Araceli Camacho-MahamudHospital Clínic de Barcelona, Villarroel 170, Barcelona, 08036, Spain.ORCID http://orcid.org/0009-0008-1205-3288
Inmaculada Grau-CorralHospital Clínic de Barcelona, Villarroel 170, Barcelona, 08036, Spain.ORCID http://orcid.org/0000-0003-1014-051X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Digital health technologies-including mobile applications, telemedicine platforms, artificial intelligence, and eHealth tools-are transforming health care delivery by enhancing access, personalization, and efficiency. However, traditional technology readiness levels (TRLs), while widely used to assess technological maturity, do not explicitly account for patient involvement-an essential factor in usability, acceptability, and real-world effectiveness. Objective: This study aimed to integrate patient perspectives into the TRLs framework, specifically tailoring it for applications in digital health innovations. By developing a patient-centered dimension using a Delphi methodology, this study provides actionable insights to enhance usability, acceptance, and real-world effectiveness of digital health technologies such as mHealth apps, telemedicine platforms, and eHealth solutions. Methods: A Delphi methodology was applied, involving 24 Spanish-speaking experts from diverse disciplines, including patient advocacy, clinical care, public health, ethics, and digital health engineering. Experts evaluated patient involvement statements across 10 TRL stages using a 6-point Likert scale. Consensus was defined a priori as ≥75% agreement and a mean score of ≥4.5. The Delphi process included 2 iterative rounds, allowing for refinement of the content despite initial consensus. Results: The Delphi process finally included 2 rounds, achieving a final 83.3% participation rate (20 of 24 experts). In round 1, all 10 TRL statements reached the predefined consensus threshold, with median scores ranging from 5.0 to 6.0 (83.3% to 100%) and mean scores from 4.70 (TRL2, 78.3%) to 5.25 (TRL5, 87.5%). While consensus was achieved, the presence of variability and qualitative feedback-particularly in early-stage TRLs such as TRL2 (Idea)-motivated a second round for refinement. In round 2, revised statements incorporating expert feedback were re-evaluated. Agreement increased across all TRLs, with mean scores ranging from 5.00 (TRL2, 83.3%) to 5.65 (TRL5, 94.2%). In total, 4 TRLs (TRL3, TRL4, TRL5, and TRL10) received a median of 6.0, indicating a unanimous strong agreement. Key refinements included more precise patient roles in usability testing, co-creation, clinical protocol design, and implementation monitoring. The framework also integrates patient-reported experience measures and patient-reported outcome measures in TRLs 5, 7, and 8. Conclusions: The PULSO-Tech-Clinic (Patient Participation, User/Usability, Literacy, System, and Observatory) Model is the first framework to systematically embed patient perspectives within the TRLs. Although consensus was achieved in the first round, a second round allowed for methodological rigor and optimization of clarity and inclusivity. This validated model enhances alignment with real-world patient needs and supports the design, evaluation, and adoption of patient-centered digital health technologies. Further research should evaluate its adaptability in diverse health care systems.

Indexed as

Delphi TechniquePatient ParticipationTelemedicineDigital HealthHumansconsensus buildingDelphi methoddigital health innovationhealth care innovationhealth care technology adoptionhealth technology assessmentmultidisciplinary collaborationpatient advocacypatient-centered designpatient engagementpatient participationtechnology acceptance modeltechnology readiness levelsunified theory of acceptance and use of technologyuser-centered frameworks

Identifiers

PMID40835414
PMCPMC12367350

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.