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Hospital nurse staffing variation and Covid-19 deaths: A cross-sectional study.
Lasater, Karen B; McHugh, Matthew D; Aiken, Linda H.
Afiliação
  • Lasater KB; Center for Health Outcomes and Policy Research, School of Nursing, University of Pennsylvania, Philadelphia, PA, United States of America; The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, United States of America. Electronic address: karenbl@nursing.upenn.edu.
  • McHugh MD; Center for Health Outcomes and Policy Research, School of Nursing, University of Pennsylvania, Philadelphia, PA, United States of America; The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, United States of America.
  • Aiken LH; Center for Health Outcomes and Policy Research, School of Nursing, University of Pennsylvania, Philadelphia, PA, United States of America; The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, United States of America.
Int J Nurs Stud ; 158: 104830, 2024 Jun 07.
Article em En | MEDLINE | ID: mdl-38917747
ABSTRACT

BACKGROUND:

During the Covid-19 pandemic, Covid-19 mortality varied depending on the hospital where patients were admitted, but it is unknown what aspects of hospitals were important for mitigating preventable deaths.

OBJECTIVE:

To determine whether hospital differences in pre-pandemic and during pandemic nursing resources-average patient-to-registered nurse (RN) staffing ratios, proportion of bachelor-qualified RNs, nurse work environments, Magnet recognition-explain differences in risk-adjusted Covid-19 mortality; and to estimate how many deaths may have been prevented if nurses were better resourced prior to and during the pandemic.

METHODS:

This is a cross-sectional study of 87,936 Medicare beneficiaries (65-99 years old) hospitalized with Covid-19 and discharged (or died) between April 1 and December 31, 2020, in 237 general acute care hospitals in New York and Illinois. Measures of hospital nursing resources (i.e. patient-to-RN staffing ratios, proportion of bachelor-qualified RNs, nurse work environments, Magnet recognition) in the pre-pandemic period (December 2019 to February 2020) and during (April to June 2021) were used to predict in-hospital and 30-day mortality using adjusted logistic regression models.

RESULTS:

The mean age of patients was 78 years (8.6 SD); 51 % were male (n = 44,998). 23 % of patients admitted to the hospital with Covid-19 died during the hospitalization (n = 20,243); 31.5 % died within 30-days of admission (n = 27,719). Patients admitted with Covid-19 to hospitals with better nursing resources pre-pandemic and during the pandemic were statistically significantly less likely to die. For example, each additional patient in the average nurses' workload pre-pandemic was associated with 20 % higher odds of in-hospital mortality (OR 1.20, 95 % CI [1.12-1.28], p < 0.001) and 15 % higher odds of 30-day mortality (OR 1.15, 95 % CI [1.09-1.21], p < 0.001). Hospitals with greater proportions of BSN-qualified RNs, better quality nurse work environments, and Magnet recognition offered similar protective benefits to patients during the pandemic. If all hospitals in the study had superior nursing resources prior to or during the pandemic, models estimate many thousands of deaths among patients hospitalized with Covid-19 could have been avoided.

CONCLUSIONS:

Patients with Covid-19 admitted to hospitals with adequate numbers of RNs caring for patients, a workforce rich in BSN-qualified RNs, and high-quality nurse work environments (both prior to and during the Covid-19 pandemic) were more likely to survive the hospitalization. Bolstering these hospital nursing resources during ordinary times is necessary to ensure better patient outcomes and emergency-preparedness of hospitals for future public health emergencies.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Int J Nurs Stud Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Int J Nurs Stud Ano de publicação: 2024 Tipo de documento: Article