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Applications of Clinical Decision Support Systems in Diabetes Care: Scoping Review.
Huang, Shan; Liang, Yuzhen; Li, Jiarui; Li, Xuejun.
Afiliação
  • Huang S; Endocrinology Department, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Liang Y; Department of Endocrinology, The Second Affiliated Hospital, Guangxi Medical University, Nanning, China.
  • Li J; Department of Endocrinology, Cangzhou Central Hospital, Cangzhou, China.
  • Li X; Department of Endocrinology and Diabetes, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
J Med Internet Res ; 25: e51024, 2023 12 08.
Article em En | MEDLINE | ID: mdl-38064249
BACKGROUND: Providing comprehensive and individualized diabetes care remains a significant challenge in the face of the increasing complexity of diabetes management and a lack of specialized endocrinologists to support diabetes care. Clinical decision support systems (CDSSs) are progressively being used to improve diabetes care, while many health care providers lack awareness and knowledge about CDSSs in diabetes care. A comprehensive analysis of the applications of CDSSs in diabetes care is still lacking. OBJECTIVE: This review aimed to summarize the research landscape, clinical applications, and impact on both patients and physicians of CDSSs in diabetes care. METHODS: We conducted a scoping review following the Arksey and O'Malley framework. A search was conducted in 7 electronic databases to identify the clinical applications of CDSSs in diabetes care up to June 30, 2022. Additional searches were conducted for conference abstracts from the period of 2021-2022. Two researchers independently performed the screening and data charting processes. RESULTS: Of 11,569 retrieved studies, 85 (0.7%) were included for analysis. Research interest is growing in this field, with 45 (53%) of the 85 studies published in the past 5 years. Among the 58 (68%) out of 85 studies disclosing the underlying decision-making mechanism, most CDSSs (44/58, 76%) were knowledge based, while the number of non-knowledge-based systems has been increasing in recent years. Among the 81 (95%) out of 85 studies disclosing application scenarios, the majority of CDSSs were used for treatment recommendation (63/81, 78%). Among the 39 (46%) out of 85 studies disclosing physician user types, primary care physicians (20/39, 51%) were the most common, followed by endocrinologists (15/39, 39%) and nonendocrinology specialists (8/39, 21%). CDSSs significantly improved patients' blood glucose, blood pressure, and lipid profiles in 71% (45/63), 67% (12/18), and 38% (8/21) of the studies, respectively, with no increase in the risk of hypoglycemia. CONCLUSIONS: CDSSs are both effective and safe in improving diabetes care, implying that they could be a potentially reliable assistant in diabetes care, especially for physicians with limited experience and patients with limited access to medical resources. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.37766/inplasy2022.9.0061.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Médicos / Sistemas de Apoio a Decisões Clínicas / Diabetes Mellitus Tipo de estudo: Systematic_reviews Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Médicos / Sistemas de Apoio a Decisões Clínicas / Diabetes Mellitus Tipo de estudo: Systematic_reviews Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article