Rao Ahsan, Jones Alice, Bottle Alex, Darzi Ara, Aylin Paul
Faculty of Medicine, Dr Foster Unit, Imperial College London, Dorset Rise, UK.
Faculty of Medicine, Global Health, Imperial College London, London, UK.
BMJ Open. 2017 Jun 24;7(6):e014618. doi: 10.1136/bmjopen-2016-014618.
To apply group-based trajectory modelling (GBTM) to the hospital administrative data to evaluate, model and visualise trends and changes in the frequency of long-term hospital care use of the subgroups of patients with cerebrovascular conditions.
A retrospective cohort study of patients with cerebrovascular conditions.
Secondary care of all patients with cerebrovascular conditions admitted to English National Hospital Service hospitals.
All patients with cerebrovascular conditions identified through national administrative data (Hospital Episode Statistics) and subsequent emergency hospital admissions followed up for 4 years.
Annual number of emergency hospital readmissions.
GBTM model classified patients with intracranial haemorrhage (n=2605) into five subgroups, whereas ischaemic stroke (n=34 208) and transient ischaemic attack (TIA) (n=20 549) patients were shown to have two conventional groups, low and high impact. The covariates with significant association with high-impact users (17.1%) among ischaemic stroke were epilepsy (OR 2.29), previous stroke (OR 2.18), anxiety/depression (OR 1.63), procedural complication (OR 1.43), admission to intensive therapy unit (ITU) or high dependency unit (HDU) (OR 1.42), comorbidity score (OR 1.36), urinary tract infections (OR 1.32), vision loss (OR 1.32), chest infections (OR 1.25), living alone (OR 1.25), diabetes (OR 1.23), socioeconomic index (OR 1.20), older age (OR 1.03) and prolonged length of stay (OR 1.00). The covariates associated with high-impact users among TIA (20.0%) were thromboembolic event (OR 3.67), previous stroke (OR 2.51), epilepsy (OR 2.25), hypotension (OR 1.86), anxiety/depression (OR 1.63), amnesia (OR 1.62), diabetes (OR 1.58), anaemia (OR 1.55), comorbidity score (OR 1.39), atrial fibrillation (OR 1.27), living alone (OR 1.25), socioeconomic index (OR 1.13), older age (OR 1.04) and prolonged length of stay (OR 1.02). The high-impact users (0.5%) among intracranial haemorrhage were strongly associated with thromboembolic event (OR 20.3) and inversely related to older age (OR 0.58).
GBTM effectively assessed trends in the use of hospital care by the subgroups of patients with cerebrovascular conditions. High-impact users persistently had higher annual readmission during the follow-up period.
应用基于群体的轨迹建模（GBTM）对医院管理数据进行分析，以评估、建模并可视化脑血管疾病患者亚组长期住院护理使用频率的趋势和变化。
对脑血管疾病患者进行回顾性队列研究。
对所有入住英国国家医疗服务体系医院的脑血管疾病患者进行二级护理。
通过国家管理数据（医院事件统计）识别出的所有脑血管疾病患者，以及随后的急诊住院患者，并进行了4年的随访。
急诊住院再入院的年度次数。
GBTM模型将颅内出血患者（n = 2605）分为五个亚组，而缺血性中风患者（n = 34208）和短暂性脑缺血发作（TIA）患者（n = 20549）显示有两个传统组，即低影响组和高影响组。在缺血性中风患者中，与高影响使用者（17.1%）有显著关联的协变量包括癫痫（OR 2.29）、既往中风（OR 2.18）、焦虑/抑郁（OR 1.63）、手术并发症（OR 1.43）、入住重症监护病房（ITU）或高依赖病房（HDU）（OR 1.42）、合并症评分（OR 1.36）、尿路感染（OR 1.32）、视力丧失（OR 1.32）、肺部感染（OR 1.25）、独居（OR 1.25）、糖尿病（OR 1.23）、社会经济指数（OR 1.20）、高龄（OR 1.03）和住院时间延长（OR 1.00）。在TIA患者中（20.0%），与高影响使用者相关的协变量包括血栓栓塞事件（OR 3.67）、既往中风（OR 2.51）、癫痫（OR 2.25）、低血压（OR 1.86）、焦虑/抑郁（OR 1.63）、失忆（OR 1.62）、糖尿病（OR 1.58）、贫血（OR 1.55）、合并症评分（OR 1.39）、心房颤动（OR 1.27）、独居（OR 1.25）、社会经济指数（OR 1.13）、高龄（OR 1.04）和住院时间延长（OR 1.02）。颅内出血患者中的高影响使用者（0.5%）与血栓栓塞事件密切相关（OR 20.3），与高龄呈负相关（OR 0.58）。
GBTM有效地评估了脑血管疾病患者亚组的医院护理使用趋势。在随访期间，高影响使用者的年度再入院率持续较高。
