| Autor: |
Gustavson, Allison M., Purnell, Amanda, Adly, Marian, Awan, Omar, Bräu, Norbert, Braus, Nicholas A., Bryant, Mon S., Chang, Lynn, Cyborski, Cherina, Darvish, Babak, Del Piero, Larissa B., Eaton, Tammy L., Kiliveros, Amelia, Kloth, Heather, McNiel, Eric R., Miller, Megan A., Patrick, Alana, Powers, Patrick, Pyne, Morgan, Rodriguez, Idelka G., Romesser, Jennifer, Rud, Brittany, Seidel, Ilana, Tepper, Alexandria, Trinh, Hanh, Tonkin, Brionn, Vachachira, Johnson, Yang, Hlee, Shak, Joshua R. |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Fed Pract |
| ISSN: |
1078-4497 |
| Popis: |
BACKGROUND: Global initiatives to mitigate COVID-19 transmission have shifted health system priorities to management of patients with prolonged long COVID symptoms. To better meet the needs of patients, clinicians, and systems, a learning health system approach can use rapid-cycle methods to integrate data and real-world experience to iteratively evaluate and adapt models of long COVID care. OBSERVATIONS: Employees in the Veterans Health Administration formed a multidisciplinary workgroup. We sought to develop processes to learn more about this novel long COVID syndrome and innovative long COVID care models that can be applied within and outside of our health care system. We describe our workgroup processes and goals to create a mechanism for cross-facility communication, identify gaps in care and research, and cocreate knowledge on best practices for long COVID care delivery. CONCLUSIONS: The learning health system approach will be critical in reimagining health care service delivery after the COVID-19 pandemic. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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