• J Burn Care Res · Oct 2018

    Incidence of Unplanned 30-Day Readmissions in Adult Burn Patients in the United States.

    • Zachary Hodosevich, Krista K Wheeler, Junxin Shi, Rebecca Coffey, J Kevin Bailey, Larry M Jones, Rajan K Thakkar, Renata B Fabia, Jonathan I Groner, and Henry Xiang.
    • The Ohio State University College of Medicine, Columbus, Ohio.
    • J Burn Care Res. 2018 Oct 23; 39 (6): 923-931.

    AbstractThis study characterizes adult burn readmissions in the United States using a nationally representative hospital inpatient sample. Readmission rates, diagnoses, and risk factors are discussed. We analyzed the 2013 and 2014 Nationwide Readmission Database for adult burn patients. The data were weighted to estimate national 30-day readmission rates. Principal readmission diagnoses were sorted into burn-specific or other readmission categories. We used multivariable logistic regression to assess the effects of patient and hospital stay risk factors on readmissions. An estimated 42,957 U.S. adult burn patients were discharged between January and November of 2013 and 2014. Of these patients, an estimated 3203 had unscheduled readmissions within 30 days (all-cause readmission rate: 7.5%, 95% CI: 6.7-8.2). An estimated 55.4 per cent of unplanned readmissions were for burn-specific principal readmission diagnoses. Burn-specific readmission was associated with burn severity and increased with both patient age and the number of comorbidities. Patients whose length of stay was less than 1 day per % total body surface area (%TBSA) burned had higher readmission risk (Adjusted odds ratio = 2.10, 95% CI = 1.48-2.99). The results of logistic regression models were similar for burn-specific readmissions and all-cause readmissions. In a nationally representative sample of adult burn patients, 4.1 per cent had unplanned 30-day readmissions for burn-specific reasons; 7.5 per cent were readmitted for any reason. Patient comorbidities and discharge before 1 day per %TBSA from the hospital impact readmission risk. Healthcare providers can use this information to identify at-risk patients, modify their treatment plans, and prevent readmissions.

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