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Attitudes Toward the Adoption of Remote Patient Monitoring and Artificial Intelligence in Parkinson's Disease Management: Perspectives of Patients and Neurologists.
Godoy Junior, Carlos Antonio; Miele, Francesco; Mäkitie, Laura; Fiorenzato, Eleonora; Koivu, Maija; Bakker, Lytske Jantien; Groot, Carin Uyl-de; Redekop, William Ken; van Deen, Welmoed Kirsten.
Afiliación
  • Godoy Junior CA; Erasmus School of Health Policy and Management, Erasmus University Rotterdam, Burgemeester Oudlaan 50, 3062 PA, Rotterdam, Netherlands. godoyjunior@eshpm.eur.nl.
  • Miele F; Department of Political and Social Sciences, University of Trieste, Trieste, Italy.
  • Mäkitie L; Department of Neurology, Brain Center, Helsinki University Hospital, Helsinki, Finland.
  • Fiorenzato E; Department of Clinical Neurosciences, University of Helsinki, Helsinki, Finland.
  • Koivu M; Department of Neuroscience (DNS), University of Padova, Padua, Italy.
  • Bakker LJ; Department of Neurology, Brain Center, Helsinki University Hospital, Helsinki, Finland.
  • Groot CU; Department of Clinical Neurosciences, University of Helsinki, Helsinki, Finland.
  • Redekop WK; Erasmus School of Health Policy and Management, Erasmus University Rotterdam, Burgemeester Oudlaan 50, 3062 PA, Rotterdam, Netherlands.
  • van Deen WK; Erasmus School of Health Policy and Management, Erasmus University Rotterdam, Burgemeester Oudlaan 50, 3062 PA, Rotterdam, Netherlands.
Patient ; 17(3): 275-285, 2024 May.
Article en En | MEDLINE | ID: mdl-38182935
ABSTRACT

OBJECTIVE:

Early detection of Parkinson's Disease (PD) progression remains a challenge. As remote patient monitoring solutions (RMS) and artificial intelligence (AI) technologies emerge as potential aids for PD management, there's a gap in understanding how end users view these technologies. This research explores patient and neurologist perspectives on AI-assisted RMS.

METHODS:

Qualitative interviews and focus-groups were conducted with 27 persons with PD (PwPD) and six neurologists from Finland and Italy. The discussions covered traditional disease progression detection and the prospects of integrating AI and RMS. Sessions were recorded, transcribed, and underwent thematic analysis.

RESULTS:

The study involved five individual interviews (four Italian participants and one Finnish) and six focus-groups (four Finnish and two Italian) with PwPD. Additionally, six neurologists (three from each country) were interviewed. Both cohorts voiced frustration with current monitoring methods due to their limited real-time detection capabilities. However, there was enthusiasm for AI-assisted RMS, contingent upon its value addition, user-friendliness, and preservation of the doctor-patient bond. While some PwPD had privacy and trust concerns, the anticipated advantages in symptom regulation seemed to outweigh these apprehensions.

DISCUSSION:

The study reveals a willingness among PwPD and neurologists to integrate RMS and AI into PD management. Widespread adoption requires these technologies to provide tangible clinical benefits, remain user-friendly, and uphold trust within the physician-patient relationship.

CONCLUSION:

This study offers insights into the potential drivers and barriers for adopting AI-assisted RMS in PD care. Recognizing these factors is pivotal for the successful integration of these digital health tools in PD management.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedad de Parkinson / Inteligencia Artificial / Neurólogos Tipo de estudio: Qualitative_research / Screening_studies Límite: Adult / Aged / Female / Humans / Male / Middle aged País/Región como asunto: Europa Idioma: En Revista: Patient Año: 2024 Tipo del documento: Article País de afiliación: Países Bajos Pais de publicación: Nueva Zelanda

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedad de Parkinson / Inteligencia Artificial / Neurólogos Tipo de estudio: Qualitative_research / Screening_studies Límite: Adult / Aged / Female / Humans / Male / Middle aged País/Región como asunto: Europa Idioma: En Revista: Patient Año: 2024 Tipo del documento: Article País de afiliación: Países Bajos Pais de publicación: Nueva Zelanda