| Autor: |
Benjamin D. Pollock, Rickey E. Carter, Sean C. Dowdy, Shannon M. Dunlay, Elizabeth B. Habermann, Daryl J. Kor, Andrew H. Limper, Hongfang Liu, Pablo Moreno Franco, Matthew R. Neville, Katherine H. Noe, John D. Poe, Priya Sampathkumar, Curtis B. Storlie, Henry H. Ting, Nilay D. Shah, Kimberly Amrami, Robert Domnick, Ethan Heinzen, Karen Helfinstine, Ajay Jayakumar, Patrick Johnson, Camille Knepper, David Marcelletti, Mindy Mickelson, Ricardo Rojas, Mark St. George, Aaron Tande, Kelli Walvatne, Phichet Wutthisirisart |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Mayo Clinic Proceedings |
| ISSN: |
0025-6196 |
| DOI: |
10.1016/j.mayocp.2020.12.019 |
| Popis: |
In March 2020, our institution developed an interdisciplinary predictive analytics task force to provide coronavirus disease 2019 (COVID-19) hospital census forecasting to help clinical leaders understand the potential impacts on hospital operations. As the situation unfolded into a pandemic, our task force provided predictive insights through a structured set of visualizations and key messages that have helped the practice to anticipate and react to changing operational needs and opportunities. The framework shared here for the deployment of a COVID-19 predictive analytics task force could be adapted for effective implementation at other institutions to provide evidence-based messaging for operational decision-making. For hospitals without such a structure, immediate consideration may be warranted in light of the devastating COVID-19 third-wave which has arrived for winter 2020-2021. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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