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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Yeste AdvLabMed2021 2-3.jpg|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Čartolovni DigitalHealth2023 9.jpeg|240px]]</div>
'''"[[Journal:Management of post-analytical processes in the clinical laboratory according to ISO 15189:2012: Considerations about the management of clinical samples, ensuring quality of post-analytical processes and laboratory information management|Management of post-analytical processes in the clinical laboratory according to ISO 15189:2012: Considerations about the management of clinical samples, ensuring quality of post-analytical processes and laboratory information management]]"'''
'''"[[Journal:Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study|Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study]]"'''


[[ISO 15189|ISO 15189:2012 ''Medical laboratories — Requirements for quality and competence'']] establishes the requirements for clinical specimen management, ensuring the [[Quality (business)|quality]] of processes and [[laboratory]] [[information management]]. ENAC (Entidad Nacional de Acreditación), the sole accreditation authority in Spain, established the requirements for the authorized use of the ISO 15189 accreditation label in reports issued by accredited laboratories. These recommendations are applicable to the lab's post-analytical processes and the professionals involved. The standard requires laboratories to define and document the duration and conditions of specimen [[Retention period|retention]]. Laboratories are also required to design an internal [[quality control]] scheme to verify whether post-analytical activities attain the expected standards. Information management requirements are also established, and laboratories are required to design a contingency plan to ensure the communication of laboratory results  ... ('''[[Journal:Management of post-analytical processes in the clinical laboratory according to ISO 15189:2012: Considerations about the management of clinical samples, ensuring quality of post-analytical processes and laboratory information management|Full article...]]''')<br />
This qualitative study aims to present the aspirations, expectations, and critical analysis of the potential for [[artificial intelligence]] (AI) to transform the patient–physician relationship, according to multi-stakeholder insight. This study was conducted from June to December 2021, using an anticipatory ethics approach and sociology of expectations as the theoretical frameworks. It focused mainly on three groups of stakeholders, namely physicians (''n'' = 12), patients (''n'' = 15), and healthcare managers (''n'' = 11), all of whom are directly related to the adoption of AI in medicine (''n'' = 38). In this study, interviews were conducted with 40% of the patients in the sample (15/38), as well as 31% of the physicians (12/38) and 29% of health managers in the sample (11/38) ... ('''[[Journal:Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study|Full article...]]''')<br />
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Latest revision as of 15:48, 26 May 2024

Fig1 Čartolovni DigitalHealth2023 9.jpeg

"Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study"

This qualitative study aims to present the aspirations, expectations, and critical analysis of the potential for artificial intelligence (AI) to transform the patient–physician relationship, according to multi-stakeholder insight. This study was conducted from June to December 2021, using an anticipatory ethics approach and sociology of expectations as the theoretical frameworks. It focused mainly on three groups of stakeholders, namely physicians (n = 12), patients (n = 15), and healthcare managers (n = 11), all of whom are directly related to the adoption of AI in medicine (n = 38). In this study, interviews were conducted with 40% of the patients in the sample (15/38), as well as 31% of the physicians (12/38) and 29% of health managers in the sample (11/38) ... (Full article...)
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