Schwartz, Jessica

Measurement of clinical documentation burden among physicians and nurses using electronic health records: a scoping review

Moy, A. J., Schwartz, J. M., Chen, R., Sadri, S., Lucas, E., Cato, K. D., & Rossetti, S. C. (2021) · Journal of the American Medical Informatics Association

Electronic Health Records SystemsNursing Diagnosis and Documentation

Cited by 284

Development and validation of early warning score system: A systematic literature review

Fu, L.-H., Schwartz, J., Moy, A., Knaplund, C., Kang, M.-J., Schnock, K. O., Garcia, J. P., Jia, H., Dykes, P. C., Cato, K., et al. (2020) · Journal of Biomedical Informatics

Healthcare Technology and Patient MonitoringSepsis Diagnosis and Treatment

Cited by 102

Factors influencing clinician trust in predictive clinical decision support systems for in-hospital deterioration: qualitative descriptive study

Schwartz, J. M., George, M., Rossetti, S. C., Dykes, P. C., Minshall, S. R., Lucas, E., & Cato, K. D. (2022) · JMIR Human Factors

Artificial Intelligence in Healthcare and EducationElectronic Health Records Systems

Cited by 88

Healthcare Process Modeling to Phenotype Clinician Behaviors for Exploiting the Signal Gain of Clinical Expertise (HPM-ExpertSignals): Development and evaluation of a conceptual framework

Rossetti, S. C., Knaplund, C., Albers, D., Dykes, P. C., Kang, M. J., Korach, T. Z., Zhou, L., Schnock, K., Garcia, J., Schwartz, J., et al. (2021) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 42

Mining clinical phrases from nursing notes to discover risk factors of patient deterioration

Korach, Z. T., Yang, J., Rossetti, S. C., Cato, K. D., Kang, M.-J., Knaplund, C., Schnock, K. O., Garcia, J. P., Jia, H., Schwartz, J. M., et al. (2020) · International Journal of Medical Informatics

Machine Learning in HealthcareBiomedical Text Mining and Ontologies

Cited by 40

Unsupervised Machine Learning of Topics Documented by Nurses about Hospitalized Patients Prior to a Rapid-Response Event

Korach, Z. T., Cato, K. D., Collins, S. A., Kang, M. J., Knaplund, C., Dykes, P. C., Wang, L., Schnock, K. O., Garcia, J. P., Jia, H., et al. (2019) · Applied Clinical Informatics

Machine Learning in HealthcareNursing Diagnosis and Documentation

Cited by 32

Identifying nurses’ concern concepts about patient deterioration using a standard nursing terminology

Kang, M.-J., Dykes, P. C., Korach, T. Z., Zhou, L., Schnock, K. O., Thate, J., Whalen, K., Jia, H., Schwartz, J., Garcia, J. P., et al. (2020) · International Journal of Medical Informatics

Nursing Diagnosis and DocumentationMachine Learning in Healthcare

Cited by 24