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Clinical Decision Support System Used in Spinal Disorders: Scoping Review.
Toh, Zheng An; Berg, Bjørnar; Han, Qin Yun Claudia; Hey, Hwee Weng Dennis; Pikkarainen, Minna; Grotle, Margreth; He, Hong-Gu.
Afiliación
  • Toh ZA; National University Hospital, National University Health System, Singapore, Singapore.
  • Berg B; Centre for Intelligent Musculoskeletal Health, Faculty of Health Sciences, Oslo Metropolitan University, Oslo, Norway.
  • Han QYC; Department of Nursing, Tan Tock Seng Hospital, Singapore, Singapore.
  • Hey HWD; Division of Orthopaedic Surgery, National University Hospital, National University Health System, Singapore, Singapore.
  • Pikkarainen M; Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
  • Grotle M; Department of Rehabilitation and Health Technology, Oslo Metropolitan University, Oslo, Norway.
  • He HG; Martti Ahtisaari Institute, Oulu Business School, Oulu University, Oulu, Finland.
J Med Internet Res ; 26: e53951, 2024 Mar 19.
Article en En | MEDLINE | ID: mdl-38502157
ABSTRACT

BACKGROUND:

Spinal disorders are highly prevalent worldwide with high socioeconomic costs. This cost is associated with the demand for treatment and productivity loss, prompting the exploration of technologies to improve patient outcomes. Clinical decision support systems (CDSSs) are computerized systems that are increasingly used to facilitate safe and efficient health care. Their applications range in depth and can be found across health care specialties.

OBJECTIVE:

This scoping review aims to explore the use of CDSSs in patients with spinal disorders.

METHODS:

We used the Joanna Briggs Institute methodological guidance for this scoping review and reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) statement. Databases, including PubMed, Embase, Cochrane, CINAHL, Web of Science, Scopus, ProQuest, and PsycINFO, were searched from inception until October 11, 2022. The included studies examined the use of digitalized CDSSs in patients with spinal disorders.

RESULTS:

A total of 4 major CDSS functions were identified from 31 studies preventing unnecessary imaging (n=8, 26%), aiding diagnosis (n=6, 19%), aiding prognosis (n=11, 35%), and recommending treatment options (n=6, 20%). Most studies used the knowledge-based system. Logistic regression was the most commonly used method, followed by decision tree algorithms. The use of CDSSs to aid in the management of spinal disorders was generally accepted over the threat to physicians' clinical decision-making autonomy.

CONCLUSIONS:

Although the effectiveness was frequently evaluated by examining the agreement between the decisions made by the CDSSs and the health care providers, comparing the CDSS recommendations with actual clinical outcomes would be preferable. In addition, future studies on CDSS development should focus on system integration, considering end user's needs and preferences, and external validation and impact studies to assess effectiveness and generalizability. TRIAL REGISTRATION OSF Registries osf.io/dyz3f; https//osf.io/dyz3f.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Sistemas de Apoyo a Decisiones Clínicas Límite: Humans Idioma: En Revista: J Med Internet Res Asunto de la revista: INFORMATICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Singapur

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Sistemas de Apoyo a Decisiones Clínicas Límite: Humans Idioma: En Revista: J Med Internet Res Asunto de la revista: INFORMATICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Singapur