Evidence map›Paper›PMID 41032887›Full record

ArticleJournal of medical Internet research2025

Stakeholder Perspectives on Early Feasibility Studies for Digital Health Technologies in the European Union: Qualitative Interview Study.

Marlen Peseke, Ilja Michaelis, Ornella Tangila Kayembe, Majella Geraghty, Ali McDonnell, Franco Luigi Zurlo, Zoe Sophie Oftring, Nicolas Martelli, Tom Melvin, Sebastian Kuhn

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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

10 authors.

Marlen PesekeInstitute for Digital Medicine, University Hospital Giessen-Marburg, Philipps University Marburg, Baldingerstrasse, Marburg, 35042, Germany, 49 642158625.ORCID http://orcid.org/0000-0002-3876-1740
Ilja MichaelisInstitute for Digital Medicine, University Hospital Giessen-Marburg, Philipps University Marburg, Baldingerstrasse, Marburg, 35042, Germany, 49 642158625.ORCID http://orcid.org/0009-0000-2116-9807
Ornella Tangila KayembePharmacy Department, Hôpital Européen Georges-Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France.ORCID http://orcid.org/0009-0009-3743-6178
Majella GeraghtySchool of Medicine, Trinity College Dublin, Dublin, Ireland.ORCID http://orcid.org/0009-0007-9596-410X
Ali McDonnellSchool of Medicine, Trinity College Dublin, Dublin, Ireland.ORCID http://orcid.org/0009-0003-4436-4631
Franco Luigi ZurloSDA Bocconi School of Management, Università Bocconi, Milan, Italy.ORCID http://orcid.org/0009-0001-8810-0211
Zoe Sophie OftringInstitute for Digital Medicine, University Hospital Giessen-Marburg, Philipps University Marburg, Baldingerstrasse, Marburg, 35042, Germany, 49 642158625.ORCID http://orcid.org/0000-0001-5473-2141
Nicolas MartelliPharmacy Department, Hôpital Européen Georges-Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France.ORCID http://orcid.org/0000-0001-5959-231X
Tom MelvinSchool of Medicine, Trinity College Dublin, Dublin, Ireland.ORCID http://orcid.org/0000-0001-6370-4177
Sebastian KuhnInstitute for Digital Medicine, University Hospital Giessen-Marburg, Philipps University Marburg, Baldingerstrasse, Marburg, 35042, Germany, 49 642158625.ORCID http://orcid.org/0000-0002-8031-2973

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Early feasibility studies (EFSs) are small-scale clinical investigations conducted during the early development of medical devices to assess initial safety and performance, especially when bench or in-silico testing is insufficient. While EFSs are well established for hardware devices, their application to digital health technologies (DHTs) including artificial intelligence (AI)-enabled medical devices remains limited. The rapidly evolving regulatory landscape, including the European Union Medical Device Regulation (EU MDR 2017/745) and the phased introduction of the European Union Artificial Intelligence (EU AI) Act, creates additional complexity for DHT developers. Despite the recognized potential of EFSs to support iterative, user-centered innovation, little is known about how European DHT companies and contract research organizations (CROs) perceive and implement EFSs, or what barriers and opportunities exist for broader adoption. Objective: This study aimed to explore stakeholder perspectives on the use, barriers, and opportunities of EFSs for DHTs in the European Union, and to generate stakeholder-driven recommendations for a harmonized EU-wide EFS framework. Methods: A qualitative descriptive study was conducted using semistructured interviews with representatives from 12 DHT companies and 3 CROs across a range of company sizes, MDR device risk classes, and clinical domains. Participants were recruited through purposive maximum-variation sampling until saturation was reached to capture diverse experiences in regulatory and clinical evidence generation. Interviews, conducted in November 2024 and January 2025, were transcribed and analyzed using thematic analysis, combining deductive and inductive coding. Results: Interviews revealed that while EFSs are valued for providing early human-factor feedback and facilitating iterative design improvements, their current use in DHT development is limited. Key barriers include unclear and hardware-centric regulatory requirements under MDR, fragmented and inconsistent interpretations across EU member states, resource and expertise constraints, and limited dialog with regulatory authorities. The anticipated introduction of the EU AI Act is expected to further increase regulatory complexity, with stakeholders expressing uncertainty about overlapping obligations and the risk of slowed innovation. Some companies, particularly larger or AI-focused ones, have proactively prepared for these changes, while others, especially small and medium-sized enterprises, face significant resource challenges. Several companies reported prioritizing the US Food and Drug Administration pathway due to clearer guidance for DHTs and structured timelines. Stakeholders advocated for a harmonized EU EFS program with DHT-specific guidelines, standardized documentation, predictable timelines, and improved communication channels. Several international models were highlighted as best practices. Conclusions: EFSs remain underused in the EU DHT sector, primarily due to regulatory complexity, fragmentation, and a lack of tailored guidance. A harmonized, DHT-specific EFS framework featuring clearer definitions, standardized processes, and structured dialog between innovators and regulators could accelerate safe, effective, and user-centric digital health innovation. As the MDR and AI Act converge, coordinated regulatory approaches will be critical to balancing innovation, safety, and patient benefit in Europe.

Indexed as

Biomedical TechnologyDigital TechnologyStakeholder ParticipationArtificial IntelligenceDigital HealthEuropean UnionFeasibility StudiesHumansInterviews as TopicQualitative ResearchAI-enabled medical devicesdigital health technologiesearly feasibility studiesMDRmedical device regulationqualitative researchregulatory framework

Identifiers

PMID41032887
PMCPMC12500223

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.