STUDY OBJECTIVE

Hospitalizations that occur shortly after emergency department (ED) discharge may reveal opportunities to improve ED or follow-up care. There currently is limited, population-level information about such events. We identify hospital- and visit-level predictors of bounce-back admissions, defined as 7-day unscheduled hospital admissions after ED discharge.

METHODS

Using the California Office of Statewide Health Planning and Development files, we conducted a retrospective cohort analysis of adult (aged >18 years) ED visits resulting in discharge in 2007. Candidate predictors included index hospital structural characteristics such as ownership, teaching affiliation, trauma status, and index ED size, along with index visit patient characteristics of demographic information, day of service, against medical advice or eloped disposition, insurance, and ED primary discharge diagnosis. We fit a multivariable, hierarchic logistic regression to account for clustering of ED visits by hospitals.

RESULTS

The study cohort contained a total of 5,035,833 visits to 288 facilities in 2007. Bounce-back admission within 7 days occurred in 130,526 (2.6%) visits and was associated with Medicaid (odds ratio [OR] 1.42; 95% confidence interval [CI] 1.40 to 1.45) or Medicare insurance (OR 1.53; 95% CI 1.50 to 1.55) and a disposition of leaving against medical advice or before the evaluation was complete (OR 1.90; 95% CI 1.89 to 2.0). The 3 most common age-adjusted index ED discharge diagnoses associated with a bounce-back admission were chronic renal disease, not end stage (OR 3.3; 95% CI 2.8 to 3.8), end-stage renal disease (OR 2.9; 95% CI 2.4 to 3.6), and congestive heart failure (OR 2.5; 95% CI 2.3 to 2.6). Hospital characteristics associated with a higher bounce-back admission rate were for-profit status (OR 1.2; 95% CI 1.1 to 1.3) and teaching affiliation (OR 1.2; 95% CI 1.0 to 1.3).

CONCLUSION

We found 2.6% of discharged patients from California EDs to have a bounce-back admission within 7 days. We identified vulnerable populations, such as the very old and the use of Medicaid insurance, and chronic or end-stage renal disease as being especially at risk. Our findings suggest that quality improvement efforts focus on high-risk individuals and that the disposition plan of patients consider vulnerable populations.