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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
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1 to 1 of 1 Research Studies DisplayedCohen B, Sanabria E, Liu J
Predicting healthcare-associated infections, length of stay, and mortality with the nursing intensity of care index.
The purpose of this study was to develop, validate, and utilize a simulation model to predict healthcare-associated infections (HAIs), length of stay (LOS), and patient mortality, as well as evaluate whether the variation in incidence of HAIs was dependent upon the adequacy of unit staffing levels. The researchers analyzed data from all patients discharged from four different types of New York City hospitals within a single healthcare network between 2012-2016 (N=562,435). The researchers developed a simulation model to estimate the daily probability rates of 5 different HAIs, length of stay, and mortality, and modeled staffing adequacy based on nursing care supply (as indicated by total nurse staffing) and nursing care demand (indicated using the Nursing Intensity of Care Index.) The study results indicated that the model predictions were within 95% confidence intervals of the actual outcomes. The authors reported that the incidence of HAI was the highest when total nurse staffing (supply) was lowest and nursing care intensity (demand) was highest.
AHRQ-funded; HS024915.
Citation: Cohen B, Sanabria E, Liu J .
Predicting healthcare-associated infections, length of stay, and mortality with the nursing intensity of care index.
Infect Control Hosp Epidemiol 2022 Mar;43(3):298-305. doi: 10.1017/ice.2021.114..
Keywords: Healthcare-Associated Infections (HAIs), Provider: Nurse, Inpatient Care, Mortality