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Published on: September 30, 2020
Understanding predictors of prolonged hospitalizations among general medicine patients: A guide and preliminary
Mary E Anderson1, Jeffrey J Glasheen1, Debra Anoff1
1Hospital Medicine Section, Division of General Internal Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora, Colorado.
Abstract:
Targeting patients with prolonged hospitalizations may represent an effective strategy for reducing average hospital length of stay (LOS). We sought to characterize predictors of prolonged hospitalizations among general medicine patients to guide future improvement efforts. We conducted a retrospective cohort study using administrative data of general medicine patients discharged from inpatient status from our academic medical center between 2012 and 2014. Multivariable logistic regression was performed to assess the association between sociodemographic and clinical variables with prolonged LOS, defined as >21 days. Of 18,363 discharges, 416 (2.3%) demonstrated prolonged LOS. Prolonged hospitalizations accounted for 18.6% of total inpatient days and contributed 0.8 days to an average LOS of 4.8 days during the study period. Prolonged hospitalizations were associated with younger age (odds ratio [OR]: 0.80 per 10-year increase in age, 95% confidence interval [CI]: 0.73-0.87) and Medicaid insurance (OR: 1.99, 95% CI: 1.29-3.05, REF = Medicare). Compared to patients without prolonged LOS, prolonged LOS patients were more likely to have methicillin-resistant Staphylococcus aureus septicemia (OR: 8.83, 95% CI: 1.72-45.36); require a palliative care consult (OR: 4.63, 95% CI: 2.86-7.49), ICU stay (OR: 6.66, 95% CI: 5.22-8.50), or surgery (OR: 5.04, 95% CI: 3.90-6.52); and be discharged to a post-acute-care facility (OR: 10.37, 95% CI: 6.92-15.56). Prolonged hospitalizations in a small proportion of patients were an important contributor to overall LOS and particularly affected Medicaid enrollees with complex hospital stays who were not discharged home. Further studies are needed to determine the reasons for discharge delays in this population.
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