Alter David A, Austin Peter C, Naylor C David, Tu Jack V
Division of Cardiology, Schulich Heart Centre, University of Toronto, Ontario.
Med Care. 2002 Jan;40(1):60-7. doi: 10.1097/00005650-200201000-00008.
Critics of "scorecard medicine" often highlight the incompleteness of risk-adjustment methods used when accounting for baseline patient differences. Although socioeconomic status is a highly important determinant of adverse outcome for patients admitted to the hospital with acute myocardial infarction, it has not been used in most risk-adjustment models for cardiovascular report cards.
To determine the incremental impact of socioeconomic status adjustments on age, sex, and illness severity for hospital-specific 30-day mortality rates after acute myocardial infarction.
The authors compared the absolute and relative hospital-specific 30-day acute myocardial infarction mortality rates in 169 hospitals throughout Ontario between April 1, 1994 and March 31, 1997. Patient socioeconomic status was characterized by median neighborhood income using postal codes and 1996 Canadian census data. They examined two risk-adjustment models: the first adjusted for age, sex, and illness severity (standard), whereas the second adjusted for age, sex, illness severity, and median neighborhood income level (socioeconomic status).
There was an extremely strong correlation between 'standard' and 'socioeconomic status' risk-adjusted mortality rates (r = 0.99). Absolute differences in 30-day risk-adjusted mortality rates between the socioeconomic status and standard risk-adjustment models were small (median, 0.1%; 25th-75th percentile, 0.1-0.2). The agreement in the quintile rankings of hospitals between the socioeconomic status and standard risk-adjustment models was high (weighted kappa = 0.93).
Despite its importance as a determinant of patient outcomes, the effect of socioeconomic status on hospital-specific mortality rates over and above standard risk-adjustment methods for acute myocardial infarction hospital profiling in Ontario was negligible.
“计分卡医学”的批评者常常强调，在考虑患者基线差异时，所使用的风险调整方法并不完善。尽管社会经济地位是急性心肌梗死入院患者不良结局的一个非常重要的决定因素，但在大多数心血管疾病报告卡的风险调整模型中，它并未被采用。
确定社会经济地位调整对急性心肌梗死后特定医院30天死亡率的年龄、性别和疾病严重程度的增量影响。
作者比较了1994年4月1日至1997年3月31日安大略省169家医院中特定医院的30天急性心肌梗死绝对死亡率和相对死亡率。利用邮政编码和1996年加拿大人口普查数据，通过社区收入中位数来描述患者的社会经济地位。他们研究了两种风险调整模型：第一种针对年龄、性别和疾病严重程度进行调整（标准模型），而第二种针对年龄、性别、疾病严重程度和社区收入中位数水平（社会经济地位）进行调整。
“标准”风险调整死亡率与“社会经济地位”风险调整死亡率之间存在极强的相关性（r = 0.99）。社会经济地位风险调整模型与标准风险调整模型之间在30天风险调整死亡率上的绝对差异很小（中位数为0.1%；第25至75百分位数为0.1 - 0.2）。社会经济地位风险调整模型与标准风险调整模型在医院五分位排名上的一致性很高（加权kappa = 0.93）。
尽管社会经济地位作为患者结局的决定因素很重要，但在安大略省，对于急性心肌梗死医院概况分析而言，社会经济地位对特定医院死亡率的影响，相对于标准风险调整方法来说微不足道。
