T2DM Clinical Decision Support System: Comprehensive Patient Care

Presenter Information

Dong-Gil Ko, University of CincinnatiFollow
Judith W. Dexheimer, Cincinnati Children’s Hospital Medical CenterFollow
Mark H Eckman, University of CincinnatiFollow
Robert M. Cohen, University of CincinnatiFollow
Daniel Schauer, University of CincinnatiFollow
Brett Harnett, University of CincinnatiFollow

Paper Type

ERF

Paper Number

1248

Description

We report on the current state of type 2 diabetes clinical decision support systems (CDSS), identify gaps that contribute to the lack of CDSS success, and apply lessons learned from practice for developing and implementing a localized diabetes CDSS. A survey of the literature reveals mixed findings regarding the efficacy of the CDSS; they do not include patient-rich information – the patient experience data in the electronic health records. We believe that diabetes care can improve by guiding clinical decisions using published evidence, patient preferences, and clinical data augmented by the local patient experience and social determinants of health using natural language processing and machine learning techniques.

Comments

SIG Health

Recommended Citation

Ko, Dong-Gil; Dexheimer, Judith W.; Eckman, Mark H; Cohen, Robert M.; Schauer, Daniel; and Harnett, Brett, "T2DM Clinical Decision Support System: Comprehensive Patient Care" (2022). AMCIS 2022 Proceedings. 4.
https://aisel.aisnet.org/amcis2022/sig_health/sig_health/4