医学
医疗补助
置信区间
优势比
过渡期护理
冲程(发动机)
逻辑回归
康复
回顾性队列研究
急症护理
可能性
急诊医学
儿科
医疗保健
物理疗法
内科学
机械工程
工程类
经济
经济增长
作者
Amy Kind,Maureen A. Smith,Jennifer R. Frytak,Michael Finch
标识
DOI:10.1111/j.1532-5415.2007.01091.x
摘要
OBJECTIVES: To identify predictors of complicated transitions within 30 days after discharge from hospitalization for acute stroke. DESIGN: Retrospective analysis of administrative data. SETTING: Four hundred twenty‐two hospitals in the southern and eastern United States. PARTICIPANTS: Thirty‐nine thousand three hundred eighty‐four Medicare beneficiaries aged 65 and older discharged after acute ischemic stroke from 1998 to 2000. MEASUREMENTS: Complicated transition, defined as movement from less‐ to more‐intensive care setting after hospital discharge, with hospital being most intensive and home without home health care being least intensive. RESULTS: Twenty percent of patients experienced at least one complicated transition; 16% of those experienced more than one complicated transition. After adjustment using logistic regression, factors predicting any complicated transition included older age, African‐American race, Medicaid enrollment, prior hospitalization, gastrostomy tube, chronic disease, length of stay, and discharge site. Patients with multiple complicated transitions were more likely to be African American (odds ratio (OR)=1.38, 95% confidence interval (CI)=1.13–1.68), be male (OR=1.21, 95% CI=1.04–1.40), have a prior diagnosis of fluid and electrolyte disorder (e.g., dehydration) (OR=1.23, 95% CI=1.07–1.43), have a prior hospitalization (OR=1.18, 95% CI=1.01–1.36), and be initially discharged to a skilled‐nursing facility or long‐term care (OR=1.22, 95% CI=1.04–1.44) than patients with only one complicated transition. They were less likely to be initially discharged to a rehabilitation center (OR=0.71, 95% CI=0.57–0.89). CONCLUSION: Significant numbers of stroke patients experience complicated transitions soon after hospital discharge. Sociodemographic factors and initial discharge site distinguish patients with multiple complicated transitions. These factors may enable prospective identification and targeting of stroke patients at risk for “bouncing back.”
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