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Redesigning Primary Care: The Emergence of Artificial-Intelligence-Driven Symptom Diagnostic Tools

Modern healthcare is facing a juxtaposition of increasing patient demands owing to an aging population and a decreasing general practitioner workforce, leading to strained access to primary care. The coronavirus disease 2019 pandemic has emphasized the potential for alternative consultation methods,...

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Autores principales: Wiedermann, Christian J., Mahlknecht, Angelika, Piccoliori, Giuliano, Engl, Adolf
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10532810/
https://www.ncbi.nlm.nih.gov/pubmed/37763147
http://dx.doi.org/10.3390/jpm13091379
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author Wiedermann, Christian J.
Mahlknecht, Angelika
Piccoliori, Giuliano
Engl, Adolf
author_facet Wiedermann, Christian J.
Mahlknecht, Angelika
Piccoliori, Giuliano
Engl, Adolf
author_sort Wiedermann, Christian J.
collection PubMed
description Modern healthcare is facing a juxtaposition of increasing patient demands owing to an aging population and a decreasing general practitioner workforce, leading to strained access to primary care. The coronavirus disease 2019 pandemic has emphasized the potential for alternative consultation methods, highlighting opportunities to minimize unnecessary care. This article discusses the role of artificial-intelligence-driven symptom checkers, particularly their efficiency, utility, and challenges in primary care. Based on a study conducted in Italian general practices, insights from both physicians and patients were gathered regarding this emergent technology, highlighting differences in perceived utility, user satisfaction, and potential challenges. While symptom checkers are seen as potential tools for addressing healthcare challenges, concerns regarding their accuracy and the potential for misdiagnosis persist. Patients generally viewed them positively, valuing their ease of use and the empowerment they provide in managing health. However, some general practitioners perceive these tools as challenges to their expertise. This article proposes that artificial-intelligence-based symptom checkers can optimize medical-history taking for the benefit of both general practitioners and patients, with potential enhancements in complex diagnostic tasks rather than routine diagnoses. It underscores the importance of carefully integrating digital innovations while preserving the essential human touch in healthcare. Symptom checkers offer promising solutions; ensuring their accuracy, reliability, and effective integration into primary care requires rigorous research, clinical guidance, and an understanding of varied user perceptions. Collaboration among technologists, clinicians, and patients is paramount for the successful evolution of digital tools in healthcare.
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spelling pubmed-105328102023-09-28 Redesigning Primary Care: The Emergence of Artificial-Intelligence-Driven Symptom Diagnostic Tools Wiedermann, Christian J. Mahlknecht, Angelika Piccoliori, Giuliano Engl, Adolf J Pers Med Opinion Modern healthcare is facing a juxtaposition of increasing patient demands owing to an aging population and a decreasing general practitioner workforce, leading to strained access to primary care. The coronavirus disease 2019 pandemic has emphasized the potential for alternative consultation methods, highlighting opportunities to minimize unnecessary care. This article discusses the role of artificial-intelligence-driven symptom checkers, particularly their efficiency, utility, and challenges in primary care. Based on a study conducted in Italian general practices, insights from both physicians and patients were gathered regarding this emergent technology, highlighting differences in perceived utility, user satisfaction, and potential challenges. While symptom checkers are seen as potential tools for addressing healthcare challenges, concerns regarding their accuracy and the potential for misdiagnosis persist. Patients generally viewed them positively, valuing their ease of use and the empowerment they provide in managing health. However, some general practitioners perceive these tools as challenges to their expertise. This article proposes that artificial-intelligence-based symptom checkers can optimize medical-history taking for the benefit of both general practitioners and patients, with potential enhancements in complex diagnostic tasks rather than routine diagnoses. It underscores the importance of carefully integrating digital innovations while preserving the essential human touch in healthcare. Symptom checkers offer promising solutions; ensuring their accuracy, reliability, and effective integration into primary care requires rigorous research, clinical guidance, and an understanding of varied user perceptions. Collaboration among technologists, clinicians, and patients is paramount for the successful evolution of digital tools in healthcare. MDPI 2023-09-15 /pmc/articles/PMC10532810/ /pubmed/37763147 http://dx.doi.org/10.3390/jpm13091379 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Opinion
Wiedermann, Christian J.
Mahlknecht, Angelika
Piccoliori, Giuliano
Engl, Adolf
Redesigning Primary Care: The Emergence of Artificial-Intelligence-Driven Symptom Diagnostic Tools
title Redesigning Primary Care: The Emergence of Artificial-Intelligence-Driven Symptom Diagnostic Tools
title_full Redesigning Primary Care: The Emergence of Artificial-Intelligence-Driven Symptom Diagnostic Tools
title_fullStr Redesigning Primary Care: The Emergence of Artificial-Intelligence-Driven Symptom Diagnostic Tools
title_full_unstemmed Redesigning Primary Care: The Emergence of Artificial-Intelligence-Driven Symptom Diagnostic Tools
title_short Redesigning Primary Care: The Emergence of Artificial-Intelligence-Driven Symptom Diagnostic Tools
title_sort redesigning primary care: the emergence of artificial-intelligence-driven symptom diagnostic tools
topic Opinion
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10532810/
https://www.ncbi.nlm.nih.gov/pubmed/37763147
http://dx.doi.org/10.3390/jpm13091379
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