Harvey R L, Roth E J, Heinemann A W, Lovell L L, McGuire J R, Diaz S
Department of Physical Medicine and Rehabilitation, Northwestern University Medical School, Chicago, IL, USA.
Arch Phys Med Rehabil. 1998 Nov;79(11):1349-55. doi: 10.1016/s0003-9993(98)90226-x.
To identify predictors of rehabilitation hospital resource utilization for patients with stroke, using demographic, medical, and functional information available on admission.
Statistical analysis of data prospectively collected from stroke rehabilitation patients.
Large, urban, academic freestanding rehabilitation facility.
A total of 945 stroke patients consecutively admitted for acute inpatient rehabilitation.
Resource utilization was measured by rehabilitation length of stay (LOS) and mean hospital charge per day (CPD).
Independent variables were organized into categories derived from four consecutive phases of clinical assessment: (1) patient referral information, (2) acute hospital record review and patient history, (3) physical examination, and (4) functional assessment. Predictors for LOS and CPD were identified separately using four stepwise multiple linear regression analyses starting with variables from the first category and adding new category data for each subsequent analysis.
Severe neurologic impairment, as measured by Rasch-converted NIH stroke scale and lower Rasch-converted motor measure of the Functional Independence Measure (FIM) instrument predicted longer LOS (F2,824 = 231.9, p < .001). Lower Rasch-converted motor FIM instrument measure, tracheostomy, feeding tube, and a history of pneumonia, coronary artery disease, or renal failure predicted higher CPD (F6,820 = 90.2, p < .001).
Stroke rehabilitation LOS and CPD are predicted by different factors. Severe impairment and motor disability are the main predictors of longer LOS; motor disability and medical comorbidities predict higher CPD. These findings will help clinicians anticipate resource needs of stroke rehabilitation patients using medical history, physical examination, and functional assessment.
利用入院时可获取的人口统计学、医学和功能信息,确定中风患者康复医院资源利用的预测因素。
对前瞻性收集的中风康复患者数据进行统计分析。
大型城市学术性独立康复机构。
共有945名中风患者连续入院接受急性住院康复治疗。
资源利用情况通过康复住院时间(LOS)和每日平均住院费用(CPD)来衡量。
自变量被分为来自临床评估四个连续阶段的类别:(1)患者转诊信息,(2)急性医院记录审查和患者病史,(3)体格检查,以及(4)功能评估。分别使用四个逐步多元线性回归分析来确定LOS和CPD的预测因素,从第一类变量开始,随后的每次分析都添加新类别的数据。
通过Rasch转换的美国国立卫生研究院中风量表和功能独立性测量(FIM)工具中较低的Rasch转换运动测量所衡量的严重神经功能损害,预测了更长的LOS(F2,824 = 231.9,p <.001)。较低的Rasch转换运动FIM工具测量、气管切开术、喂食管以及肺炎、冠状动脉疾病或肾衰竭病史预测了更高的CPD(F6,820 = 90.2,p <.001)。
中风康复的LOS和CPD由不同因素预测。严重损害和运动障碍是LOS延长的主要预测因素;运动障碍和医疗合并症预测了更高的CPD。这些发现将有助于临床医生利用病史、体格检查和功能评估来预测中风康复患者的资源需求。