A photo of Judith Dexheimer.

Associate Professor, UC Department of Pediatrics


Biography & Affiliation


Dr. Dexheimer has a background in developing, implementing and evaluating clinical information systems including clinical decision systems, organizational and workflow aspects of informatics applications, computerized applications for emergency medicine and implementation of artificial intelligence techniques, computerized guideline applications and evidence-based medicine, public health informatics, and preventive care measures. Her research focuses on the design, implementation and evaluation of clinical decision support systems in pediatric emergency medicine to improve clinical care.

Dr. Dexheimer co-leads the Decision Support Analytics Workgroup (DSAW), which investigates the links between the effectiveness of clinical decision support (CDS), patient safety, and user efficiency. This research has demonstrated ties between decreasing alert burden on clinicians, increasing CDS alert salience, and improving patient outcomes.

Research Interests

Learn more about the Decision Support Analytics Workgroup.

Academic Affiliation

Associate Professor, UC Department of Pediatrics


Biomedical Informatics, Emergency Medicine

Science Blog


PhD: Biomedical Informatics, Vanderbilt University, Nashville, TN, 2011.

MS: Biomedical Informatics, Vanderbilt University, Nashville, TN, 2006.


Prospective validation of a machine learning model that uses provider notes to identify candidates for resective epilepsy surgery. Wissel, BD; Greiner, HM; Glauser, TA; Holland-Bouley, KD; Mangano, FT; Santel, D; Faist, R; Zhang, N; Pestian, JP; Szczesniak, RD; et al. Epilepsia. 2020; 61:39-48.

A Time-and-Motion Study of Clinical Trial Eligibility Screening in a Pediatric Emergency Department. Dexheimer, JW; Tang, H; Kachelmeyer, A; Hounchell, M; Kennebeck, S; Solti, I; Ni, Y. Pediatric Emergency Care. 2019; 35:868-873.

Automated patient linking for electronic health record and child welfare databases. Dexheimer, JW; Beal, SJ; Divekar, P; Hall, ES; Patel, V; Greiner, MV. Journal of Technology in Human Services. 2019; 37:286-292.

Investigation of bias in an epilepsy machine learning algorithm trained on physician notes. Wissel, BD; Greiner, HM; Glauser, TA; Mangano, FT; Santel, D; Pestian, JP; Szczesniak, RD; Dexheimer, JW. Epilepsia. 2019; 60:e93-e98.

Improving Information Sharing for Youth in Foster Care. Greiner, MV; Beal, SJ; Dexheimer, JW; Divekar, P; Patel, V; Hall, ES. Pediatrics. 2019; 144:e20190580-e20190580.

Sharing personal health record data elements in protective custody: Youth and stakeholder perspectives. Dexheimer, JW; Greiner, MV; Beal, SJ; Johnson, D; Kachelmeyer, A; Vaughn, LM. Journal of the American Medical Informatics Association. 2019; 26:714-721.

Designing and evaluating a real-time automated patient screening system in an emergency department. Ni, Y; Bermudez, M; Kennebeck, S; Liddy-Hicks, S; Dexheimer, J. Journal of Medical Internet Research. 2019; 7:e14185-e14185.

Mathematical Model for Computer-Assisted Modification of Medication Dosing Rules. Grabel, MZ; Vaughan, BL; Dexheimer, JW; Kirkendall, ES. Biomedical Informatics Insights. 2019; 11:1178222619829079-117822261982907.

The Parkinson's disease e-diary: Developing a clinical and research tool for the digital age. Vizcarra, JA; Sanchez-Ferro, A; Maetzler, W; Marsili, L; Zavala, L; Lang, AE; Martinez-Martin, P; Mestre, TA; Reilmann, R; Hausdorff, JM; et al. Movement Disorders. 2019; 34:676-681.

The Reliability of Computerized Physician Order Entry Data for Research Studies. Dexheimer, JW; Taylor, RG; Kachelmeyer, AM; Reed, JL. Pediatric Emergency Care. 2019; 35:e61-e64.