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Artificial intelligence for secondary prevention of myocardial infarction: A qualitative study of patient and health professional perspectives.
Pelly, Melissa; Fatehi, Farhad; Liew, Danny; Verdejo-Garcia, Antonio.
Afiliação
  • Pelly M; School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC 3800, Australia. Electronic address: melissa.pelly1@monash.edu.
  • Fatehi F; School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC 3800, Australia. Electronic address: f.fatehi@uq.edu.au.
  • Liew D; School of Public Health and Preventive Medicine, Monash University, Clayton, VIC 3800, Australia; The Alfred Hospital, 55 Commercial Rd, Melbourne, VIC 3800, Australia. Electronic address: amsdean@adelaide.edu.au.
  • Verdejo-Garcia A; School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC 3800, Australia. Electronic address: antonio.verdejo@monash.edu.
Int J Med Inform ; 173: 105041, 2023 05.
Article em En | MEDLINE | ID: mdl-36934609
ABSTRACT

BACKGROUND:

Artificial intelligence (AI) has potential to improve self-management of several chronic conditions. However, the perspective of patients and healthcare professionals regarding AI-enabled health management programs, which are key to successful implementation, remains poorly understood.

PURPOSE:

To explore the opinions of people with a history of myocardial infarction (PHMI) and health professionals on the use of AI for secondary prevention of MI. PROCEDURE Three rounds of focus groups were conducted via videoconferencing with 38

participants:

22 PHMI and 16 health professionals.

FINDINGS:

We identified 21 concepts stemming from participants' views, which we classified into five categories Trust; Expected Functions; Adoption; Concerns; and Perceived Benefits. Trust covered the credibility of information and safety to believe health advice. Expected Functions covered tailored feedback and personalised advice. Adoption included usability features and overall interest in AI. Concerns originated from previous negative experience with AI. Perceived Benefits included the usefulness of AI to provide advice when regular contact with healthcare services is not feasible. Health professionals were more optimistic than PHMI about the usefulness of AI for improving health behaviour.

CONCLUSIONS:

Altogether, our findings provide key insights from end-users to improve the likelihood of successful implementation and adoption of AI-enabled systems in the context of MI, as an exemplar of broader applications in chronic disease management.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Infarto do Miocárdio Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Infarto do Miocárdio Idioma: En Ano de publicação: 2023 Tipo de documento: Article