Kannampallil, Thomas

Exposure to COVID-19 patients increases physician trainee stress and burnout

Kannampallil, T. G., Goss, C. W., Evanoff, B. A., Strickland, J. R., McAlister, R. P., & Duncan, J. (2020) · PLOS ONE

COVID-19 and Mental HealthHealthcare professionals’ stress and burnout

Cited by 389

Temporal Associations Between EHR-Derived Workload, Burnout, and Errors: a Prospective Cohort Study

Lou, S. S., Lew, D., Harford, D. R., Lu, C., Evanoff, B. A., Duncan, J. G., & Kannampallil, T. (2022) · Journal of General Internal Medicine

Healthcare professionals’ stress and burnoutElectronic Health Records Systems

Cited by 46

Precision clinical trials: a framework for getting to precision medicine for neurobehavioural disorders

Lenze, E. J., Nicol, G. E., Barbour, D. L., Kannampallil, T., Wong, A. W. K., Piccirillo, J., Drysdale, A. T., Sylvester, C. M., Haddad, R., Miller, J. P., et al. (2021) · Journal of Psychiatry and Neuroscience

Statistical Methods in Clinical TrialsMental Health Research Topics

Cited by 43

Efficiency of emergency physicians: insights from an observational study using EHR log files

Kannampallil, T., Denton, C., Shapiro, J., & Patel, V. (2018) · Applied Clinical Informatics

Electronic Health Records SystemsEmergency and Acute Care Studies

Cited by 27

Predicting self-intercepted medication ordering errors using machine learning

King, C. R., Abraham, J., Fritz, B. A., Cui, Z., Galanter, W., Chen, Y., & Kannampallil, T. (2021) · PLOS ONE

Patient Safety and Medication ErrorsElectronic Health Records Systems

Cited by 22

Reasons for computerised provider order entry (CPOE)-based inpatient medication ordering errors: an observational study of voided orders

Abraham, J., Kannampallil, T. G., Jarman, A., Sharma, S., Rash, C., Schiff, G., & Galanter, W. (2018) · BMJ Quality & Safety

Electronic Health Records SystemsPatient Safety and Medication Errors

Cited by 22

Unlocking Inpatient Workload Insights with Electronic Health Record Event Logs

Burden, M., Keniston, A., Pell, J., Yu, A., Dyrbye, L., & Kannampallil, T. (2025) · Journal of Hospital Medicine

Electronic Health Records SystemsHealthcare professionals’ stress and burnout

Cited by 19

Learning from errors: analysis of medication order voiding in CPOE systems

Kannampallil, T. G., Abraham, J., Solotskaya, A., Philip, S. G., Lambert, B. L., Schiff, G. D., Wright, A., & Galanter, W. L. (2017) · Journal of the American Medical Informatics Association

Electronic Health Records SystemsPatient Safety and Medication Errors

Cited by 18

Characterizing the macrostructure of electronic health record work using raw audit logs: an unsupervised action embeddings approach

Lou, S. S., Liu, H., Harford, D., Lu, C., & Kannampallil, T. (2023) · Journal of the American Medical Informatics Association

Electronic Health Records SystemsMachine Learning in Healthcare

Cited by 13

Identifying and addressing barriers to implementing core electronic health record use metrics for ambulatory care: virtual consensus conference proceedings

Levy, D. R., Moy, A. J., Apathy, N., Adler-Milstein, J., Rotenstein, L., Nath, B., Rosenbloom, S. T., Kannampallil, T., Mishuris, R. G., Alexanian, A., et al. (2023) · Applied Clinical Informatics

Electronic Health Records SystemsMedical Coding and Health Information

Cited by 6

‘This is our liver patient…’: use of narratives during resident and nurse handoff conversations

Kannampallil, T., Jones, S., & Abraham, J. (2020) · BMJ Quality & Safety

Hospital Admissions and OutcomesPatient Safety and Medication Errors

Cited by 2

A language model framework for sequence modeling of EHR audit logs to characterize clinician-EHR interactions

Kim, S., Lou, S., Cobb, A., Jha, S., & Kannampallil, T. (2026) · medRxiv

Machine Learning in HealthcareElectronic Health Records Systems

Cited by 0