BACKGROUND: Hospital occupancy, nurse staffing levels, weekend admission, and seasonal influenza have all been shown to be associated with in-hospital mortality. Yet, no study has simultaneously compared the strength of associations of these 4 factors with in-hospital mortality. OBJECTIVE: To compare the risk of in-hospital mortality conferred by high hospital occupancy on admission, increased nurse staffing levels, weekend admission, and seasonal influenza. STUDY DESIGN: Retrospective cohort study of 166,920 patients admitted to 39 Michigan hospitals between 2003 and 2006. Participants were adults, age > or = 65 years, admitted through the emergency department with 6 common discharge diagnoses (acute myocardial infarction, congestive heart failure, stroke, pneumonia, hip fracture, gastrointestinal bleeding). We used logistic regression to compare the differences in the predicted probability of death conferred by each of the 4 factors, controlling for patient age, gender, discharge diagnosis, and comorbid conditions. RESULTS: Each of the 4 factors had a statistically significant, independent association with in-hospital mortality. Seasonal influenza conferred the greatest increase in absolute risk of in-hospital mortality (0.5 percentage points; 95% CI, 0.23-0.76), followed by weekend admission (0.32, 0.11-0.54), and high hospital occupancy on admission (0.24, 0.06-0.43). Increased nurse staffing levels decreased the absolute risk of mortality by 0.25 percentage points (0.04-0.48) for each additional full-time equivalent nurse per patient-day. CONCLUSION: Hospital occupancy, nurse staffing levels, weekend admission, and seasonal influenza all appear to be independently associated with in-hospital mortality, but to varying degrees in the current sample. These findings may guide hospital administrators as they consider factors that influence weekly and seasonal patient flow and capacity, as well as staffing.
BACKGROUND: Hospital occupancy, nurse staffing levels, weekend admission, and seasonal influenza have all been shown to be associated with in-hospital mortality. Yet, no study has simultaneously compared the strength of associations of these 4 factors with in-hospital mortality. OBJECTIVE: To compare the risk of in-hospital mortality conferred by high hospital occupancy on admission, increased nurse staffing levels, weekend admission, and seasonal influenza. STUDY DESIGN: Retrospective cohort study of 166,920 patients admitted to 39 Michigan hospitals between 2003 and 2006. Participants were adults, age > or = 65 years, admitted through the emergency department with 6 common discharge diagnoses (acute myocardial infarction, congestive heart failure, stroke, pneumonia, hip fracture, gastrointestinal bleeding). We used logistic regression to compare the differences in the predicted probability of death conferred by each of the 4 factors, controlling for patient age, gender, discharge diagnosis, and comorbid conditions. RESULTS: Each of the 4 factors had a statistically significant, independent association with in-hospital mortality. Seasonal influenza conferred the greatest increase in absolute risk of in-hospital mortality (0.5 percentage points; 95% CI, 0.23-0.76), followed by weekend admission (0.32, 0.11-0.54), and high hospital occupancy on admission (0.24, 0.06-0.43). Increased nurse staffing levels decreased the absolute risk of mortality by 0.25 percentage points (0.04-0.48) for each additional full-time equivalent nurse per patient-day. CONCLUSION: Hospital occupancy, nurse staffing levels, weekend admission, and seasonal influenza all appear to be independently associated with in-hospital mortality, but to varying degrees in the current sample. These findings may guide hospital administrators as they consider factors that influence weekly and seasonal patient flow and capacity, as well as staffing.
Authors: Katie J Sheehan; Boris Sobolev; Pierre Guy; Lisa Kuramoto; Suzanne N Morin; Jason M Sutherland; Lauren Beaupre; Donald Griesdale; Michael Dunbar; Eric Bohm; Edward Harvey Journal: CMAJ Date: 2016-10-17 Impact factor: 8.262
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Authors: Mahdi Khoshchehreh; Elliott M Groves; David Tehrani; Alpesh Amin; Pranav M Patel; Shaista Malik Journal: Int J Cardiol Date: 2016-02-17 Impact factor: 4.164