Details

Autor(en) / Beteiligte

• Peacock, Sarah H
• Grek, Ami A
• Rogers, Emily R
• Freeman, William D
• White, Launia J
• Li, Zhuo
• Hartjes, Tonja
• Naessens, James M

Titel

Neuro R 2 score: Predicting high-risk neurologic readmissions within 30 days

Ist Teil von

• Neurology, 2020-04, Vol.94 (15), p.e1614

Ort / Verlag

United States

Erscheinungsjahr

2020

Quelle

MEDLINE

Beschreibungen/Notizen

• To evaluate clinical and demographic factors of patients with neurologic disorders to determine which patient characteristics are significant for predicting 30-day hospital readmissions to develop a readmission risk predictor specific to patients with neurologic disorders. We performed a retrospective single-center chart review for all patients admitted to the Department of Neurology or neurologic intensive care unit from January 1, 2013, to December 31, 2017. Clinical and demographic factors were analyzed to determine the association with readmission. Multivariable logistic regression analysis was performed and validated to develop a simple tool (Neuro R score) for predicting patients with neurologic disorders at high risk for hospital readmission. After removal of planned readmissions and patients who died in the hospital, the records of 4,876 patients with 314 (6.4%) readmission events were analyzed. The strongest predictors for readmission were Charlson disease count (odds ratio [OR] 1.20, 95% confidence interval [CI] 1.06-1.35, = 0.005), urgent or emergent admission (OR 1.50, 95% CI 1.04-2.17, = 0.031), discharge to rehabilitation (OR 1.66, 95% CI 1.16-2.35, = 0.005), cancer (OR 1.70, 95% CI 1.15-2.50, = 0.007), brain tumor (OR 1.82, 95% CI 1.08-3.09, < 0.03), cerebrovascular disease (OR 2.18, 95% CI 1.53-3.11, < 0.001), and discharge to skilled nursing facility (OR 2.43, 95% CI 1.65-3.57, < 0.001). The Neuro R score was developed to predict readmission risk, specifically in patients with neurologic disorders. Future research could include further validation of this readmission risk tool and strategies to reduce readmission in patients with the highest risk.