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1.
JMIR Hum Factors ; 11: e50939, 2024 Jun 13.
Artigo em Inglês | MEDLINE | ID: mdl-38869934

RESUMO

BACKGROUND: The clinical management of type 2 diabetes mellitus (T2DM) presents a significant challenge due to the constantly evolving clinical practice guidelines and growing array of drug classes available. Evidence suggests that artificial intelligence (AI)-enabled clinical decision support systems (CDSSs) have proven to be effective in assisting clinicians with informed decision-making. Despite the merits of AI-driven CDSSs, a significant research gap exists concerning the early-stage implementation and adoption of AI-enabled CDSSs in T2DM management. OBJECTIVE: This study aimed to explore the perspectives of clinicians on the use and impact of the AI-enabled Prescription Advisory (APA) tool, developed using a multi-institution diabetes registry and implemented in specialist endocrinology clinics, and the challenges to its adoption and application. METHODS: We conducted focus group discussions using a semistructured interview guide with purposively selected endocrinologists from a tertiary hospital. The focus group discussions were audio-recorded and transcribed verbatim. Data were thematically analyzed. RESULTS: A total of 13 clinicians participated in 4 focus group discussions. Our findings suggest that the APA tool offered several useful features to assist clinicians in effectively managing T2DM. Specifically, clinicians viewed the AI-generated medication alterations as a good knowledge resource in supporting the clinician's decision-making on drug modifications at the point of care, particularly for patients with comorbidities. The complication risk prediction was seen as positively impacting patient care by facilitating early doctor-patient communication and initiating prompt clinical responses. However, the interpretability of the risk scores, concerns about overreliance and automation bias, and issues surrounding accountability and liability hindered the adoption of the APA tool in clinical practice. CONCLUSIONS: Although the APA tool holds great potential as a valuable resource for improving patient care, further efforts are required to address clinicians' concerns and improve the tool's acceptance and applicability in relevant contexts.


Assuntos
Inteligência Artificial , Diabetes Mellitus Tipo 2 , Grupos Focais , Pesquisa Qualitativa , Diabetes Mellitus Tipo 2/tratamento farmacológico , Diabetes Mellitus Tipo 2/terapia , Humanos , Sistemas de Apoio a Decisões Clínicas , Masculino , Feminino , Hipoglicemiantes/uso terapêutico , Hipoglicemiantes/administração & dosagem , Pessoa de Meia-Idade , Adulto
2.
Headache ; 60(9): 2083-2084, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-32757392

RESUMO

We present the case of 24-year-old woman who presented with chronic headaches with features of raised intracranial pressure and bilateral papilledema. Brain magnetic resonance imaging revealed the characteristic features of idiopathic intracranial hypertension. A diagnosis supported by clinical features and other ancillary tests. These features are important for physicians to recognize early, so that timely treatment may prevent permanent complications from this rare but potentially sight-threatening headache.


Assuntos
Hipertensão Intracraniana/diagnóstico , Adulto , Feminino , Cefaleia/diagnóstico , Cefaleia/etiologia , Humanos , Hipertensão Intracraniana/complicações , Imageamento por Ressonância Magnética , Papiledema/diagnóstico , Papiledema/etiologia , Adulto Jovem
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