Predictive Analytics and Workflow Automation to Reduce Administrative Burden and Clinician Burnout in United States Clinical Settings: A Systematic Review.
- DOI
- 10.63116/ah.000000010
- Published
- 2026
- Container
- Advances in health information science and practice
- Publisher
- Not recorded
- Open access
- yes
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limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.63116/ah.000000010,
title = {Predictive Analytics and Workflow Automation to Reduce Administrative Burden and Clinician Burnout in United States Clinical Settings: A Systematic Review.},
author = {Akosah A and Hunt TJ},
year = {2026},
journal = {Advances in health information science and practice},
doi = {10.63116/ah.000000010},
url = {https://doi.org/10.63116/ah.000000010}
}RIS
TY - JOUR TI - Predictive Analytics and Workflow Automation to Reduce Administrative Burden and Clinician Burnout in United States Clinical Settings: A Systematic Review. AU - Akosah A AU - Hunt TJ PY - 2026 JO - Advances in health information science and practice DO - 10.63116/ah.000000010 UR - https://doi.org/10.63116/ah.000000010 ER -
APA
A, A., & TJ, H. (2026). Predictive Analytics and Workflow Automation to Reduce Administrative Burden and Clinician Burnout in United States Clinical Settings: A Systematic Review.. Advances in health information science and practice. https://doi.org/10.63116/ah.000000010
Source records
- pubmed · retrieved 2026-11-09T13:41:24.828Z
- europe-pmc · retrieved 2026-11-09T13:41:24.857Z