Background: Outpatient parenteral antimicrobial therapy (OPAT) allows administration of IV antibiotics in ambulatory settings to facilitate hospital discharge. To realize the benefits of OPAT, careful selection of patients who can successfully complete therapy without readmission or complication is critical. We sought to identify predictors of unplanned 30-day readmission from our local VA OPAT database.
Methods: Patients treated between June 2009 and November 2012 in the OPAT program at the VA North Texas Healthcare System had data collected on demographics, comorbidities, indication for OPAT, antimicrobials used, number and reason for readmissions. Univariate analysis was performed using Student's t, Chi-squared, or Fisher's exact tests with multivariate analysis by logistic regression.
Results: Of 395 patients reviewed, 350 patients met inclusion criteria. Seventy three (21%) had unplanned readmission within 30 days. Most common infection types were bone/joint infections (32%), skin and soft tissue infections (31%), and prosthetic joint infections (18%). Most common reasons for readmission were causes unrelated to treatment (43%), adverse drug reaction (21%), and worsening infection (16%). Figure 1 shows predictors of unplanned readmission included in the final regression model including prior inpatient admissions in the previous 12 months (odds ratio [OR], 1.27 per admission; 95% confidence interval [CI], 1.11–1.45), infective endocarditis (OR, 3.14; 95% CI, 1.12–8.82), cardiac device (CIED) infection (OR, 3.16; 95% CI, 0.77–12.96), primary bacteremia (OR, 2.44; 95% CI, 1.16–5.11), use of antistaphylococcal β-lactams (OR, 2.74; 95% CI, 1.37–5.51), and use of antipseudomonal β-lactams (OR, 3.45; 95% CI, 1.64–7.23). After internal validation, the corrected model c-statistic was 0.66, and calibration curves showed good fit of the model with the data (Hosmer–Lemeshow P = 0.18, Figure 2). Significant predictors of adverse events are shown in Figure 3.
Conclusion: We identified several factors significantly associated with unplanned 30-day readmission in a veteran OPAT population. The predictive model, if externally validated, may improve patient selection for OPAT prior to discharge.
S. Duquaine, None
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