GENDER, ALCOHOL, COMORBIDITY, AND USE OF HEALTH SERVICES

申请者摘要：医疗保健计划和提供者越来越意识到 他们必须识别、治疗和管理有酒精问题的人 以及抑郁症和慢性病等并存的疾病。然而，为了 识别这样的患者并适当地解决他们的问题，我们需要 了解这些并存情况是如何相互作用的，以及如何耐心 这些特征会影响这些情况及其结果。研究人员已经 我一直在努力了解影响饮酒的因素，以及 了解这种消费如何影响发病率、死亡率和对健康的利用 服务。到目前为止，我们对这些关系的了解仍然有限 因为影响饮酒和健康利用的过程 服务是复杂的。为了提高我们的知识，模型现在必须包括一个 精神和身体并存的复杂组合，功能状态和 个人特点。最重要的个人层面之一 影响饮酒和医疗服务使用的因素是性别：IT 影响饮酒模式、医疗护理的数量和类型 以及共同的精神疾病和健康状况 酒精和服务用途。在这项试探性/发展性拨款中，我们将使用 现有数据集，以解决四个主要问题：(1)人口统计如何 因素、抑郁、健康和功能状态以及慢性病 影响饮酒消费(2)人口统计因素如何影响饮酒 消费、抑郁、健康和功能状态以及慢性病 影响卫生服务总成本？(3)针对性别的模型 与问题1和问题2对应提供了更好的解释 联合性别模特？(4)结构方程模型是否提高了我们的 与两部分回归比较时对这些复杂现象的理解 模特？使用随机抽样的7844名25岁HMO成员的现有数据集 和老年人，我们将构建全面的回归和结构方程 导致饮酒的过程模型，然后使用相同的 研究酒精消费如何影响健康服务的建模策略 用途和成本。我们将比较按性别划分的模型和按性别组合的模型 模型来确定男性和女性之间的潜在过程是否不同， 并对从两部分回归和结构中获得的知识进行评估 方程模型，以评估它们对我们的总体 对这些结果的理解。

APPLICANT'S ABSTRACT: Health care plans and providers are increasingly aware that they must identify, treat, and manage people who have alcohol problems and comorbid conditions such as depression and chronic illnesses. However, to identify such patients and address their problems appropriately, we need to understand how these comorbid conditions interact, and how patient characteristics affect such conditions and their outcomes. Researchers have been working to understand the factors that influence alcohol consumption, and to learn how that consumption affects morbidity, mortality, and use of health services. To date, our understanding of these relationships remains limited because the processes that affect alcohol use and utilization of health services are complex. To advance our knowledge, models must now include a complex mix of mental and physical comorbidities, functional status and individual characteristics. One of the most important of the individual-level factors affecting alcohol consumption and health service use is gender: It affects patterns of alcohol consumption, amounts and types of medical care used, and comorbid psychiatric and health conditions that underlie both alcohol and service use. In this exploratory/developmental grant, we will use existing data sets to address four main questions: (1) How do demographic factors, depression, health and functional status, and chronic illness jointly influence alcohol consumptions (2) How do demographic factors, alcohol consumption, depression, health and functional status, and chronic illness influence total cost of health services? (3) Do gender-specific models corresponding to Questions 1 and 2 provide superior explanations when compared to combined-gender models? (4) Do structural equation models enhance our understanding of these complex phenomena when compared to two-part regression models? Using an existing data set of 7844 randomly sampled HMO members age 25 and older, we will construct comprehensive regression and structural equation models of the processes leading to alcohol consumption, and then use the same modeling strategies to study how alcohol consumption affects health services use and costs. We will compare gender-specific models with combined-gender models to determine if the underlying processes differ between men and women, and evaluate the knowledge gained from the two-part regression and structural equation models to assess their relative contribution to our overall understanding of these outcomes.