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Modeling Nursing Home Harms From COVID-19 Staff Furlough Policies.
Bartsch, Sarah M; Weatherwax, Colleen; Leff, Bruce; Wasserman, Michael R; Singh, Raveena D; Velmurugan, Kavya; John, Danielle C; Chin, Kevin L; O'Shea, Kelly J; Gussin, Gabrielle M; Martinez, Marie F; Heneghan, Jessie L; Scannell, Sheryl A; Shah, Tej D; Huang, Susan S; Lee, Bruce Y.
Afiliação
  • Bartsch SM; Center for Advanced Technology and Communication in Health, City University of New York Graduate School of Public Health and Health Policy, New York.
  • Weatherwax C; Public Health Informatics, Computational, and Operations Research, City University of New York Graduate School of Public Health and Health Policy, New York.
  • Leff B; Artificial Intelligence, Modeling, and Informatics for Nutrition Guidance and Systems Center, City University of New York Graduate School of Public Health and Health Policy, New York.
  • Wasserman MR; Center for Advanced Technology and Communication in Health, City University of New York Graduate School of Public Health and Health Policy, New York.
  • Singh RD; Public Health Informatics, Computational, and Operations Research, City University of New York Graduate School of Public Health and Health Policy, New York.
  • Velmurugan K; Artificial Intelligence, Modeling, and Informatics for Nutrition Guidance and Systems Center, City University of New York Graduate School of Public Health and Health Policy, New York.
  • John DC; Division of Geriatric Medicine and Gerontology, The Center for Transformative Geriatric Research, Johns Hopkins School of Medicine, Baltimore, Maryland.
  • Chin KL; California Association of Long Term Care Medicine, Santa Clarita.
  • O'Shea KJ; Division of Infectious Diseases, Department of Medicine, University of California Irvine School of Medicine, Irvine.
  • Gussin GM; Center for Advanced Technology and Communication in Health, City University of New York Graduate School of Public Health and Health Policy, New York.
  • Martinez MF; Public Health Informatics, Computational, and Operations Research, City University of New York Graduate School of Public Health and Health Policy, New York.
  • Heneghan JL; Artificial Intelligence, Modeling, and Informatics for Nutrition Guidance and Systems Center, City University of New York Graduate School of Public Health and Health Policy, New York.
  • Scannell SA; Center for Advanced Technology and Communication in Health, City University of New York Graduate School of Public Health and Health Policy, New York.
  • Shah TD; Public Health Informatics, Computational, and Operations Research, City University of New York Graduate School of Public Health and Health Policy, New York.
  • Huang SS; New York City Pandemic Response Institute, New York.
  • Lee BY; Center for Advanced Technology and Communication in Health, City University of New York Graduate School of Public Health and Health Policy, New York.
JAMA Netw Open ; 7(8): e2429613, 2024 Aug 01.
Article em En | MEDLINE | ID: mdl-39158906
ABSTRACT
Importance Current guidance to furlough health care staff with mild COVID-19 illness may prevent the spread of COVID-19 but may worsen nursing home staffing shortages as well as health outcomes that are unrelated to COVID-19.

Objective:

To compare COVID-19-related with non-COVID-19-related harms associated with allowing staff who are mildly ill with COVID-19 to work while masked. Design, Setting, and

Participants:

This modeling study, conducted from November 2023 to June 2024, used an agent-based model representing a 100-bed nursing home and its residents, staff, and their interactions; care tasks; and resident and staff health outcomes to simulate the impact of different COVID-19 furlough policies over 1 postpandemic year. Exposures Simulating increasing proportions of staff who are mildly ill and are allowed to work while wearing N95 respirators under various vaccination coverage, SARS-CoV-2 transmissibility and severity, and masking adherence. Main Outcomes and

Measures:

The main outcomes were staff and resident COVID-19 cases, staff furlough days, missed care tasks, nursing home resident hospitalizations (related and unrelated to COVID-19), deaths, and costs.

Results:

In the absence of SARS-CoV-2 infection in the study's 100-bed agent-based model, nursing home understaffing resulted in an annual mean (SD) 93.7 (0.7) missed care tasks daily (22.1%), 38.0 (7.6) resident hospitalizations (5.2%), 4.6 (2.2) deaths (0.6%), and 39.7 (19.8) quality-adjusted life years lost from non-COVID-19-related harms, costing $1 071 950 ($217 200) from the Centers for Medicare & Medicaid Services (CMS) perspective and $1 112 800 ($225 450) from the societal perspective. Under the SARS-CoV-2 Omicron variant conditions from 2023 to 2024, furloughing all staff who tested positive for SARS-CoV-2 was associated with a mean (SD) 326.5 (69.1) annual furlough days and 649.5 (95% CI, 593.4-705.6) additional missed care tasks, resulting in 4.3 (95% CI, 2.9-5.9) non-COVID-19-related resident hospitalizations and 0.7 (95% CI, 0.2-1.1) deaths, costing an additional $247 090 (95% CI, $203 160-$291 020) from the CMS perspective and $405 250 (95% CI, $358 550-$451 950) from the societal perspective. Allowing 75% of staff who were mildly ill to work while masked was associated with 5 additional staff and 5 additional resident COVID-19 cases without added COVID-19-related hospitalizations but mitigated staffing shortages, with 475.9 additional care tasks being performed annually, 3.5 fewer non-COVID-19-related hospitalizations, and 0.4 fewer non-COVID-19-related deaths. Allowing staff who were mildly ill to work ultimately saved an annual mean $85 470 (95% CI, $41 210-$129 730) from the CMS perspective and $134 450 (95% CI, $86 370-$182 540) from the societal perspective. These results were robust to increased vaccination coverage, increased nursing home transmission, increased importation of COVID-19 from the community, and failure to mask while working ill. Conclusion and Relevance In this modeling study of staff COVID-19 furlough policies, allowing nursing home staff to work with mild COVID-19 illness was associated with fewer resident harms from staffing shortages and missed care tasks than harms from increased COVID-19 transmission, ultimately saving substantial direct medical and societal costs.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: SARS-CoV-2 / COVID-19 / Casas de Saúde Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: JAMA Netw Open Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: SARS-CoV-2 / COVID-19 / Casas de Saúde Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: JAMA Netw Open Ano de publicação: 2024 Tipo de documento: Article