Meeker, Daniella

A harmonized data quality assessment terminology and framework for the secondary use of electronic health record data

Kahn, M. G., Callahan, T. J., Barnard, J., Bauck, A. E., Brown, J., Davidson, B. N., Estiri, H., Goerg, C., Holve, E., Johnson, S. G., et al. (2016) · eGEMs (Generating Evidence & Methods to improve patient outcomes)

Medical Coding and Health InformationElectronic Health Records Systems

Cited by 697

Characterizing treatment pathways at scale using the OHDSI network

Hripcsak, G., Ryan, P. B., Duke, J. D., Shah, N. H., Park, R. W., Huser, V., Suchard, M. A., Schuemie, M. J., DeFalco, F. J., Perotte, A., et al. (2016) · Proceedings of the National Academy of Sciences

Medical Coding and Health InformationMachine Learning in Healthcare

Cited by 326

Use of ambient AI scribes to reduce administrative burden and professional burnout

Olson, K. D., Meeker, D., Troup, M., Barker, T. D., Nguyen, V. H., Manders, J. B., Stults, C. D., Jones, V. G., Shah, S. D., Shah, T., et al. (2025) · JAMA Network Open

Electronic Health Records SystemsHealthcare professionals’ stress and burnout

Cited by 243

Development of a social and environmental determinants of health informatics maturity model

Espinoza, J. C., Sehgal, S., Phuong, J., Bahroos, N., Starren, J., Wilcox, A., & Meeker, D. (2023) · Journal of Clinical and Translational Science

Electronic Health Records SystemsArtificial Intelligence in Healthcare and Education

Cited by 9

Generative Medical Event Models Improve with Scale

Waxler, S., Blazek, P., White, D., Sneider, D., Chung, K., Nagarathnam, M., Williams, P., Voeller, H., Wong, K., Swanhorst, M., et al. (2025) · arXiv

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 4