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Analysis of institutional authors

Garcia-Gomez, Juan MCorresponding AuthorBlanes-Selva, VicentAuthor

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July 31, 2025
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Mitigating patient harm risks: A proposal of requirements for AI in healthcare

Publicated to: ARTIFICIAL INTELLIGENCE IN MEDICINE. 167 103168- - 2025-09-01 167(), DOI: 10.1016/j.artmed.2025.103168

Authors:

Garcia-Gomez, Juan M; Blanes-Selva, Vicent; Romero, Celia Alvarez; Cenzano, Jose Carlos de Bartolome; Mesquita, Felipe Pereira; Pazos, Alejandro; Donate-Martinez, Ascension
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Affiliations

Com Tecn Inteligencia Artificial, Soc Espanola Informat Salud SEIS, Madrid, Spain - Author
Ctr Invest Tecnol Informac & Comunicac CITIC, La Coruna, Spain - Author
Inst Invest Biomed A Coruna INIB, La Coruna, Spain - Author
Soc Iber Telemed & Telesalud SITT, Madrid, Spain - Author
Univ A Coruna, Comp Sci & Informat Technol Dept, RNASA IMEDIR Grp, La Coruna, Spain - Author
Univ Fed Juiz de Fora, Hematol Hemoterapia & Transplante Medula Ossea, Hosp Univ, Juiz de Fora, Brazil - Author
Univ Politecn Valencia, Area Derecho Constituc UPV, Valencia, Spain - Author
Univ Politecn Valencia, Biomed Data Sci Lab, ITACA Inst Informacio & Tecnol Comunicac, Valencia, Spain - Author
Univ Seville, IBiS Virgen Rocio Univ Hosp, Inst Biomed Seville, Computat Hlth Informat Grp,CSIC, Seville, Spain - Author
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Abstract

With the rise Artificial Intelligence (AI), mitigation strategies may be needed to integrate AI-enabled medical software responsibly, ensuring ethical alignment and patient safety. This study examines how to mitigate the key risks identified by the European Parliamentary Research Service (EPRS). For that, we discuss how complementary risk-mitigation requirements may ensure the main aspects of AI in Healthcare: Reliability - Continuous performance evaluation, Continuous usability test, Encryption and use of field-tested libraries, Semantic interoperability -, Transparency - AI passport, eXplainable AI, Data quality assessment, Bias Check -, Traceability - User management, Audit trail, Review of cases-, and Responsibility - Regulation check, Academic use only disclaimer, Clinicians double check -. A survey conducted among 216 Medical ICT professionals (medical doctors, ICT staff and complementary profiles) between March and June 2024 revealed these requirements were perceived positive by all profiles. Responders deemed explainable AI and data quality assessment essential for transparency; audit trail for traceability; and regulatory compliance and clinician double check for responsibility. Clinicians rated the following requirements more relevant (p < 0.05) than technicians: continuous performance assessment, usability testing, encryption, AI passport, retrospective case review, and academic use check. Additionally, users found the AI passport more relevant for transparency than decision-makers (p < 0.05). We trust that this proposal can serve as a starting point to endow the future AI systems in medical practice with requirements to ensure their ethical deployment.
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Keywords

Ai actArtificial intelligenceArtificial-intelligenceMedical softwareMitigating strategiesModelPatient harmReliabilityResponsibilityRisk for patientsSoftware design requirementsSurveTraceabilityTransparency

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal ARTIFICIAL INTELLIGENCE IN MEDICINE due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2025, it was in position 7/48, thus managing to position itself as a Q1 (Primer Cuartil), in the category Medical Informatics.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-04:

  • WoS: 3
  • Scopus: 4
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-04:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 63.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 63 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 2.
  • The number of mentions on the social network X (formerly Twitter): 2 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
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Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Brazil.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (García Gómez, Juan Miguel) .

the author responsible for correspondence tasks has been García Gómez, Juan Miguel.

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