Meder M, Farin E
Universitätsklinikum Freiburg, Abteilung Qualitätsmanagement und Sozialmedizin, Freiburg.
Rehabilitation (Stuttg). 2011 Aug;50(4):222-31. doi: 10.1055/s-0030-1263120. Epub 2011 May 30.
The study deals with the question of how patients with chronic ischemic heart disease assess different health situations that can be achieved by rehabilitation. Furthermore it examines which factors influence these health valuations and whether the predictors vary depending on the level of education.
The health valuations of n = 331 patients with chronic ischemic heart disease are compiled using visual analogue scales (VAS). In addition to sociodemographic questions, generic and illness-specific scales (SF-12, MacNew) for the health-related quality of life (HRQOL) are used as potential predictors of the health valuations. Additional basic medical data were provided by the physician. Hierarchical regression analyses are conducted; the sociodemographic, medical and HRQOL variables are included stepwise. Since many variables are observed for the regression models, an imputation of missing values is made.
The health dimensions "Self-care and domestic life" and "Mobility" are assigned the highest values on the VAS. The lowest preference is assigned to the dimensions "Reduction of symptoms" and "Information about the disease". The differences between the health dimensions are statistically significant. Sociodemographic variables explain up to 3.6% of the variance of health valuations, with level of education and living with a partner being the most important predictors. The medical variables included in the second step explain between 2.1 and 6.8% incremental variance; the most important predictor is the operation performed prior to rehabilitation (bypass, heart valve). The HRQOL variables in the third block provide 7.1-24.9% incremental explanation of variance, by far the highest percentage. This is mainly achieved using the 3 MacNew scales (emotional, social and physical functioning). The overall explanation of variance for the health valuations is 17.1-28.8%. For patients with a higher level of education, the total explanation of variance is about 9.2% higher on average than for the total sample and lies between 21.2 and 44.1%.
The health dimensions examined are assessed quite differently by the patients. The most significant factor of influence is the HRQOL. In the subgroup of patients with a higher level of education, the predictive strength of the variables examined is considerably higher in comparison with the total sample. Since the health valuations can be predicted to a limited extent only using other data arising during routine care, it is necessary to implement special methods for compiling health valuations.
本研究探讨慢性缺血性心脏病患者如何评估通过康复可实现的不同健康状况。此外，研究还考察了哪些因素会影响这些健康评估，以及预测因素是否因教育程度而异。
使用视觉模拟量表（VAS）对n = 331例慢性缺血性心脏病患者的健康评估进行汇总。除社会人口学问题外，用于健康相关生活质量（HRQOL）的通用和疾病特异性量表（SF - 12，MacNew）被用作健康评估的潜在预测因素。医生提供了额外的基础医学数据。进行分层回归分析；社会人口学、医学和HRQOL变量逐步纳入。由于回归模型观察到许多变量，因此对缺失值进行了插补。
在VAS上，“自我护理和家庭生活”以及“活动能力”这两个健康维度被赋予最高值。“症状减轻”和“疾病信息”维度的偏好最低。各健康维度之间的差异具有统计学意义。社会人口学变量最多可解释健康评估方差的3.6%，其中教育程度和与伴侣同住是最重要的预测因素。第二步纳入的医学变量解释了2.1%至6.8%的增量方差；最重要的预测因素是康复前进行的手术（搭桥、心脏瓣膜）。第三步中的HRQOL变量对方差的增量解释为7.1% - 24.9%，是迄今为止最高的百分比。这主要通过3个MacNew量表（情感、社会和身体功能）实现。健康评估的总体方差解释率为17.1% - 28.8%。对于教育程度较高的患者，方差的总解释率平均比总样本高约9.2%，介于21.2%和44.1%之间。
患者对所考察的健康维度的评估差异很大。最显著的影响因素是HRQOL。在教育程度较高的患者亚组中，与总样本相比，所考察变量的预测强度明显更高。由于仅使用常规护理期间产生的其他数据只能在有限程度上预测健康评估，因此有必要实施特殊的健康评估编制方法。
