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Pandemic influenza and excess intensive-care workload.

ABSTRACT: In The Netherlands a major part of preparedness planning for an epidemic or pandemic consists of maintaining essential public services, e.g., by the police, fire departments, army personnel, and healthcare workers. We provide estimates for peak demand for healthcare workers, factoring in healthcare worker absenteeism and using estimates from published epidemiologic models on the expected evolution of pandemic influenza in relation to the impact on peak surge capacity of healthcare facilities and intensive care units (ICUs). Using various published scenarios, we estimate their effect in increasing the availability of healthcare workers for duty during a pandemic. We show that even during the peak of the pandemic, all patients requiring hospital and ICU admission can be served, including those who have non-influenza-related conditions. For this rigorous task differentiation, clear hierarchical management, unambiguous communication, and discipline are essential and we recommend informing and training non-ICU healthcare workers for duties in the ICU.

SUBMITTER: Nap RE

PROVIDER: S-EPMC2609860 | biostudies-literature | 2008 Oct

REPOSITORIES: biostudies-literature

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Pandemic influenza and excess intensive-care workload.

Nap Raoul E RE Andriessen Maarten P H M MP Meessen Nico E L NE Miranda Dinis dos Reis Ddos R van der Werf Tjip S TS

Emerging infectious diseases 20081001 10

In The Netherlands a major part of preparedness planning for an epidemic or pandemic consists of maintaining essential public services, e.g., by the police, fire departments, army personnel, and healthcare workers. We provide estimates for peak demand for healthcare workers, factoring in healthcare worker absenteeism and using estimates from published epidemiologic models on the expected evolution of pandemic influenza in relation to the impact on peak surge capacity of healthcare facilities and ...[more]

PMID: 18826813

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Project description:ImportanceQuality improvement initiatives demonstrate the contribution of reliable nursing care to gains in clinical and safety outcomes in neonatal intensive care units (NICUs); when core care is missed, outcomes can worsen.ObjectiveTo evaluate the association of NICU nurse workload with missed nursing care.Design, setting, and participantsA prospective design was used to evaluate associations between shift-level workload of individual nurses and missed care for assigned infants from March 1, 2013, through January 31, 2014, at a 52-bed level IV NICU in a Midwestern academic medical center. A convenience sample of registered nurses who provided direct patient care and completed unit orientation were enrolled. Nurses reported care during each shift for individual infants whose clinical data were extracted from the electronic health record. Data were analyzed from January 1, 2015, through August 13, 2018.ExposuresWorkload was assessed each shift with objective measures (infant-to-nurse staffing ratio and infant acuity scores) and a subjective measure (the National Aeronautics and Space Administration Task Load Index [NASA-TLX]).Main outcomes and measuresMissed nursing care was measured by self-report of omission of 11 essential care practices. Cross-classified, multilevel logistic regression models were used to estimate associations of workload with missed care.ResultsA total of 136 nurses provided reports of shift-level workload and missed nursing care for 418 infants during 332 shifts of 12 hours each. When workload variables were modeled independently, 7 of 12 models demonstrated a significant worsening association of increased infant-to-nurse ratio with odds of missed care (eg, nurses caring for ≥3 infants were 2.51 times more likely to report missing any care during the shift [95% credible interval, 1.81-3.47]), and all 12 models demonstrated a significant worsening association of increased NASA-TLX subjective workload ratings with odds of missed care (eg, each 5-point increase in a nurse's NASA-TLX rating during a shift was associated with a 34% increase in the likelihood of missing a nursing assessment for his or her assigned infant[s] during the same shift [95% credible interval, 1.30-1.39]). When modeling all workload variables jointly, only 4 of 12 models demonstrated significant association of staffing ratios with odds of missed care, whereas the association with NASA-TLX ratings remained significant in all models. Few associations of acuity scores were observed across modeling strategies.Conclusions and relevanceThe workload of NICU nurses is significantly associated with missed nursing care, and subjective workload ratings are particularly important. Subjective workload represents an important aspect of nurse workload that remains largely unmeasured despite high potential for intervention.

Project description:PURPOSE: The rate of severe outcomes of patients with 2009 pandemic (A/H1N1) influenza (2009pI) hospitalized in non-intensive care units (ICUs) has not been defined thus far. This study aims to assess the efficacy of the management of patients with influenza-like illness (ILI) of moderate intermediate severity in an infectious diseases unit (IDU) during the first wave of 2009pI and its influence on the burden of ICUs. METHODS: All patients hospitalized from October 27, 2009, to February 5, 2010, with ILI were included in this prospective observational study. The IDU was organized and the staff was trained to provide intermediate care; patients were transferred to the ICU only if they required invasive ventilation, extracorporeal membrane oxygenation, or advanced cardiovascular support. Demographic data, clinical presentation, coexisting medical conditions, and laboratory and radiological findings were recorded and analyzed, as well as treatment and outcome data. RESULTS: Overall, 108 patients (median age 36 years [IQR 27-54], 57.4% males) including 66.7% with ≥ 1 risk factor for severe influenza, 47.2% with confirmed 2009pI by RT-PCR and 63.9% with pneumonia, were enrolled in the study. All subjects received intravenous fluids and 83.3% were administered oseltamivir, 96.3% antibacterials, 19.4% oxygen therapy without ventilatory support, and 10.2% non-invasive ventilation. A total of 106 (98.1%) subjects were discharged after a 6-day median hospital stay [IQR 4-9]. Two patients (1.9%) were transferred to the ICU. There were no deaths. CONCLUSIONS: These results suggest that the aggressive treatment of patients with moderate intermediate severity 2009 pandemic ILI in non-ICU wards may result in a low rate of severe outcomes and brief hospitalization. IDUs, if properly organized for intermediate care, may efficiently provide correct disease management, in addition to complying with infection control requirements, thus reducing the burden of the pandemic on ICUs. Further studies are warranted to evaluate the outcome of patients with moderate intermediate 2009pI in different non-ICU settings.

Project description:BackgroundThe impact of socio-demographic factors and baseline health on the mortality burden of seasonal and pandemic influenza remains debated. Here we analyzed the spatial-temporal mortality patterns of the 1918 influenza pandemic in Spain, one of the countries of Europe that experienced the highest mortality burden.MethodsWe analyzed monthly death rates from respiratory diseases and all-causes across 49 provinces of Spain, including the Canary and Balearic Islands, during the period January-1915 to June-1919. We estimated the influenza-related excess death rates and risk of death relative to baseline mortality by pandemic wave and province. We then explored the association between pandemic excess mortality rates and health and socio-demographic factors, which included population size and age structure, population density, infant mortality rates, baseline death rates, and urbanization.ResultsOur analysis revealed high geographic heterogeneity in pandemic mortality impact. We identified 3 pandemic waves of varying timing and intensity covering the period from Jan-1918 to Jun-1919, with the highest pandemic-related excess mortality rates occurring during the months of October-November 1918 across all Spanish provinces. Cumulative excess mortality rates followed a south-north gradient after controlling for demographic factors, with the North experiencing highest excess mortality rates. A model that included latitude, population density, and the proportion of children living in provinces explained about 40% of the geographic variability in cumulative excess death rates during 1918-19, but different factors explained mortality variation in each wave.ConclusionsA substantial fraction of the variability in excess mortality rates across Spanish provinces remained unexplained, which suggests that other unidentified factors such as comorbidities, climate and background immunity may have affected the 1918-19 pandemic mortality rates. Further archeo-epidemiological research should concentrate on identifying settings with combined availability of local historical mortality records and information on the prevalence of underlying risk factors, or patient-level clinical data, to further clarify the drivers of 1918 pandemic influenza mortality.

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Pandemic influenza and excess intensive-care workload.

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Pandemic influenza and excess intensive-care workload.

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