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Abstract Details

Neuroscience Patient Readmissions: Are Medical Prediction Models Accurate for Neurology and Neuro Intensive Care Unit Patients?
Practice, Policy, and Ethics
S50 - Practice, Policy, and Ethics (3:52 PM-4:03 PM)
003
Hospital readmissions have been shown to be a measure of quality and result in higher mortality and increased cost. 
The purpose of this study was to review demographic characteristics to determine what factors contribute to 30 day readmissions in neuroscience patients.  

After IRB approval, we conducted a retrospective analysis analyzing all neurology and neuro intensive care unit (ICU) patients admitted and readmitted to Mayo Clinic  within 30 days. We reviewed the following demographic characteristics: age, sex, length of stay, Charleston comorbidity index, ICU admission and discharge disposition and other covariates associated with readmission. We defined statistical significance as a P value <0.001.

Over a 4 year period, from January 2013 to December 2017, we studied a total of 4561 patients with 314 of these patients (6.9%) who were readmitted within 30 days.  Statistically significant factors associated with readmission included older age (median 68 years of age versus 60 years of age, P< 0.0001), longer initial length of stay (mean 4.9 days (SD 4.3) versus 4.0 days (SD 5.0), comorbid conditions of congestive heart failure, peripheral vascular disease, stroke, dementia, pulmonary disease, ulcers, diabetes,  moderate to severe renal disease, cancer and metastatic tumors, brain tumors, hemiplegia and discharge to location other than home (e.g., skilled nursing facility or rehabilitation  P <0.0001). Factors not statistically significant associated with readmission include sex (male or female), mild liver disease, AIDS, rheumatic disease, and discharging service (neurocritical care or neurology).

This is one of the largest neuroscience patient population readmission studies to date looking at patient risk factors for associated with readmission.  Risk factors for readmission included medically complex comorbid medical history, and debilitated patients with hemiplegia, and moderate to severe end-organ dysfunction.  We are designing a prospective multivariate regression model for better prediction and strategies for these higher neuroscience risk patients.
Authors/Disclosures
Sarah Peacock, NP (Mayo Clinic)
PRESENTER
No disclosure on file
No disclosure on file
No disclosure on file
William D. Freeman, MD, FAAN (Mayo Clinic) Dr. Freeman has nothing to disclose.
No disclosure on file
No disclosure on file
No disclosure on file