Estimates and Temporal Trend for US Nationwide 30-Day Hospital Readmission Among Patients With Ischemic and Hemorrhagic Stroke
Estimates and Temporal Trend for US Nationwide 30-Day Hospital Readmission Among Patients With Ischemic and Hemorrhagic Stroke
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DOI：
10.1001/jamanetworkopen.2018.1190
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发表时间：
2018-08-01
影响因子：
13.8
通讯作者：
Vahidy, Farhaan S.
中科院分区：
文献类型：
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作者：
Bambhroliya, Arvind B.;Donnelly, John P.;Vahidy, Farhaan S.
降低再入院的重要性与改善护理质量、节省成本有关，并且是以患者为中心的理想结果。到目前为止，还没有具有全国代表性的中风患者再入院指标。目的提供美国全国范围内缺血性和出血性中风患者30天再住院的总体、计划和潜在可预防的住院时间趋势的估计和时间趋势；调查医院卒中出血量、教学状况和30天再入院之间的关联；强调30天再入院的原因，并从死亡率、住院时间和中风患者的护理成本方面探索30天再入院的相关性。设计、设置和参与者对2010年1月1日至2015年9月30日期间全国范围内的阅读数据库进行年度分析。研究背景是一项以人群为基础的队列研究，提供了国家对30天重新入院的估计。该数据库代表了美国22个地理上分散的州所有住院患者的50%。受试者为成人(<18岁)，首次出院诊断为脑内出血、急性缺血性中风或蛛网膜下腔出血。医院根据其年中风出院量进行分类，如果医院有美国医学会批准的住院医生计划，或者全职相当于实习生和住院医生与床位的比率为0.25或更高，则被归类为教学医院。MAIN结果和衡量标准再入院定义为指数住院出院后30天内的任何入院。使用医疗保险和医疗补助服务中心定义的算法，事件被归类为计划内或计划外以及潜在的可预防。结果根据研究标准，纳入2 078 854名符合条件的患者(平均[SE]年龄，70.02[0.07]岁；51.9%女性)。再入院30d以脑出血患者最高(13.70%；95%CI，13.40%~13.99%)，其次为急性缺血性卒中患者(12.44%；95%CI，12.33%~12.55%)和蛛网膜下腔出血患者(11.48%；95%CI，11.01%~11.96%)。2010至2014年间，再入院率平均每年下降3.3%，这在调查期间具有统计学意义(优势比为0.96；95%可信区间为0.95-0.97)。卒中出院量大的非教学医院出院的患者30天再入院的风险明显更高，再入院的前两位原因是急性脑血管疾病和败血症。结论和相关性本研究表明，全国有代表性的再入院指标可以用来衡量医院的绩效，3.3%的时间趋势可以用来评估再入院减少策略的有效性。
IMPORTANCE Readmission reduction is linked to improved quality of care, saves cost, and is a desirable patient-centered outcome. Nationally representative readmission metrics for patients with stroke are unavailable to date. Such estimates are necessary for benchmarking performance.OBJECTIVES To provide US nationwide estimates and a temporal trend for overall, planned, and potentially preventable 30-day hospital readmission among patients with ischemic and hemorrhagic stroke; to investigate the association between hospitals' stroke discharge volume, teaching status, and 30-day readmission; and to highlight reasons for 30-day readmission and explore the association of 30-day readmission in terms of mortality, length of stay, and cost of care among patients with stroke.DESIGN, SETTING, AND PARTICIPANTS Cohort, year-wise analysis of the Nationwide Readmissions Database between January 1, 2010, and September 30, 2015. The setting was a population-based cohort study providing national estimates of 30-day readmission. The database represents 50% of all US hospitalizations from 22 geographically dispersed states. Participants were adult (>= 18 years) patients with a primary discharge diagnosis of intracerebral hemorrhage, acute ischemic stroke, or subarachnoid hemorrhage. Hospitals were categorized by their annual stroke discharge volume and were classified as teaching hospitals if they had an American Medical Association-approved residency program or had a ratio of full-time equivalent interns and residents to beds of 0.25 or higher.MAIN OUTCOMES AND MEASURES Readmission was defined as any admission within 30 days of index hospitalization discharge. Using Centers for Medicare & Medicaid Services-defined algorithms, events were classified as planned or unplanned and as potentially preventable.RESULTS Based on study criteria, 2 078 854 eligible patients were included (mean [SE] age, 70.02 [0.07] years; 51.9% female). Thirty-day readmission was highest for patients with intracerebral hemorrhage (13.70%; 95% CI, 13.40%-13.99%), followed by patients with acute ischemic stroke (12.44%; 95% CI, 12.33%-12.55%) and patients with subarachnoid hemorrhage (11.48%; 95% CI, 11.01%-11.96%). On average, there was a 3.3% annual decline in readmission between 2010 and 2014, which was statistically significant for the period of investigation (odds ratio, 0.96; 95% CI, 0.95-0.97). Patients discharged from nonteaching hospitals with high stroke discharge volume were at a significantly higher risk of 30-day readmission, and the top 2 reasons for readmission were acute cerebrovascular disease and septicemia.CONCLUSIONS AND RELEVANCE This study suggests that nationally representative readmission metrics can be used to benchmark hospitals' performance, and a temporal trend of 3.3% may be used to evaluate the effectiveness of readmission reduction strategies.