Machine Learning Model for Predicting High Administrative Burden Encounters Using Documentation Complexity, Billing Requirements, Insurance Rules, Care Coordination Needs, and Provider Workload Indicators

cirpublications.com-yLm3-1790883433-n429666118 1790883433 Clinical Intelligence Research Press info@cirpublications.com Clinical Intelligence Research Press Journal of Health Informatics and Digital Systems J. Health Inform. Digit. Syst. 3149-8973 2026 6 2 Machine Learning Model for Predicting High Administrative Burden Encounters Using Documentation Complexity, Billing Requirements, Insurance Rules, Care Coordination Needs, and Provider Workload Indicators Mohamed Salah Youssef Karim Ahmed Nabil Mahmoud Adel Karim Hassan 2026 10.68159/n429666118 https://cirpublications.com/pub/journal/2/article/n429666118 Arndt BG, Beasley JW, Watkinson MD, Temte JL, Tuan WJ, Sinsky CA, et al. Tethered to the EHR: primary care physician workload assessment using EHR event log data and time-motion observations. Ann Fam Med. 2017;15(5):419-26. Tai-Seale M, Olson CW, Li J, Chan AS, Morikawa C, Durbin M, et al. 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