HEALTH CARE COSTS AND PERSONAL RISK FACTORS

工作场所健康促进计划旨在减少医疗费用 支出；然而，缺乏显示这种节省的数据。这个项目 将研究可更改的个人风险因素与 纺织工人和他们的人群对医疗保健的高成本利用 家属。理论模型认为，所有其他事物都是 同样，不断增加的风险因素会导致健康状况低迷， 导致服务利用率增加和支出增加。 个人特点、工作情况与医疗保健 系统将被评估为潜在的修饰者或混杂因素 理论化的关系。 在人群中需要回答的具体问题是：(1)哪些类型的 使用率与高成本护理相关？(2)哪些特征 个人(包括健康状况和风险因素)、就业或 医疗服务与高昂的医疗费用有关吗？(3)哪一项 特征与提高利用率有关吗？和(4)哪一个 与健康状况不佳有关吗？ 这是一项为期一年的医疗费用和医疗费用患病率研究 与风险和其他因素有关的利用率。它使用的是一个行业的 约20,000名员工的集中保险索赔记录 以及用于成本和利用率数据的30,000名家属。员工记录 提供人口统计和身份识别数据。对六个人的问卷调查 有代表性的工厂(约3000家)将提供健康状况和 风险因素数据(香烟、酒精、锻炼、安全带、压力等)。 多变量分析将评估不良的显著相关性 健康状况和高成本使用。这一结果将指导对 预防方案对改善健康状况和 控制该行业的医疗保健成本。

Workplace health promotion programs are intended to reduce medical expenditures; however data are lacking to show such savings. This project will study the relationship between modifiable personal risk factors and high-cost use of health care in a population of textile workers and their dependents. The theoretical model holds that, all other things being equal, increasing risk factors leads to depressed health status, which leads to increased utilization of services and to higher expenditures. Characteristics of individuals, the work situation and the health care system will be assessed as potential modifiers or confounders of the theorized relationship. Specific questions to be answered in the population are: (1) What types of utilization are associated with high cost care? (2) What characteristics of individuals (including health status and risk factors), employment or health services are associated with high cost care? (3) Which characteristics are associated with increased utilization? and (4) Which are associated with poor health status? This is a one year period prevalence study of health care costs and utilization in relation to risk and other factors. It uses an industries' centralized insurance claims records from approximately 20,000 employees and 30,000 dependents for cost and utilization data. Employee records provide demographic and identification data. A questionnaire survey of six representative plants (n approximately 3000) will provide health status and risk factor data (cigarettes, alcohol, exercise, seat belts, stress, etc.). Multivariable analyses will assess the significant correlates of poor health status and high cost use. The results will guide a discussion of the relevance of prevention programs for improving health status and containing health care costs in the industry.