Étude et rapport

Artificial intelligence-assisted clinical decision support for childhood asthma management: A randomized clinical trial

GRATUIT

Auteur(s) :

Hee Yun Seol , Pragya Shrestha , Joy Fladager Muth, Chung-Il Wi, Sunghwan Sohn, Euijung Ryu, Miguel Park, Kathy Ihrke, Sungrim Moon, Katherine King, Philip Wheeler, Bijan Borah, James Moriarty, Jordan Rosedahl, Hongfang Liu, Deborah B. McWilliams, Young J. Juhn

Éditeur(s) :

PLOS ONE

Date de publication :02/08/2021

16 pages

EN BREF ...

"Growing deployments of Electronic Health Records (EHRs) systems have established large practice-based longitudinal patient records causing an increase in the volume of unstructured data (80%) in the currently available health care records. Inefficient and ineffective use of EHRs due to overwhelming volume has led to physician burnout (70% of clinicians reported health information technology [HIT]-related stress) due to increased workload during their limited (e.g.,15–20 min) clinic visit. The application of Artificial Intelligence (AI) to health care may potentially address these challenges through AI-assisted clinical decision support (CDS) tools. The National Academy of Medicine suggested delivering high-value care in the personal and social context through science and technology as one of the key directions for the US health care system" En bref issu de l'étude.

Rédacteur(s) de la fiche : Beesens TEAM


Introductio

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Conclusio

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