Hornbrook M C, Goodman M J
Center for Health Research, Kaiser Permanente, Portland, OR 97227-1098, USA.
Inquiry. 1995 Spring;32(1):56-74.
Unbiased risk assessment models base health plan payments on enrollee health care needs. We explored the risk structure of employed adult health maintenance organization (HMO) members using the RAND-36 health survey. We used multivariate techniques to estimate risk weights on demographic and health status factors. The dependent variable was annual real total health plan expense for covered services for the year following the survey. Repeated random-split-sample validation techniques minimized outlier influences. Five scales improved prediction over simple demographic factors, but demographic factors still were required to achieve unbiased forecasts. Self-reported health status is a useful and powerful risk measure for adults.
无偏风险评估模型根据参保人的医疗保健需求来确定健康计划支付金额。我们使用兰德36项健康调查对在职成年健康维护组织（HMO）成员的风险结构进行了探究。我们运用多变量技术来估算人口统计学和健康状况因素的风险权重。因变量是调查后一年中所涵盖服务的年度实际健康计划总费用。重复随机分割样本验证技术将异常值的影响降至最低。五个量表比简单的人口统计学因素能更好地进行预测，但仍需要人口统计学因素来实现无偏预测。自我报告的健康状况是成年人一项有用且有力的风险衡量指标。
