POPULATION BASED MANAGEMENT OF DEPRESSION

基于人群的抑郁症管理

• 批准号: 2250587
• 负责人: GREGORY G SIMON
• 金额: $ 26.17万
• 依托单位: KAISER FOUNDATION HEALTH PLAN OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-06-01 至 1997-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2250587
• 关键词: antidepressants; drug administration rate /duration; functional ability; health care cost /financing; health care personnel performance; health care service utilization; human data; human morbidity; human subject; interview; longitudinal human study; major depression; managed care; mental disorder chemotherapy; mental disorder diagnosis; mental health epidemiology; mental health information system; patient /disease registry; patient care management; pharmacy administration; population survey; relapse /recurrence

Depressive illness is a common, serious condition associated with great personal suffering, significant disability, and high health care costs. While most depression treatment trials are conducted in specialty clinics, most depression treatment occurs in primary care. Previous research suggests that few patients treated in primary care receive the intensity of treatment recommended by speCialists. More recent data suggest, however, that many patients receiving low-intensity treatment have good short-term outcomes. Given that resources available to improve the treatment of depression will probably remain limited, intervention should focus on groups of patients in which more intensive treatment is likely to reduce morbidity, disability, or cost. The proposed research will focus on two dimensions of depression likely to influence clinical course, disability, and treatment response: stage of treatment (initial, recurrent, or chronic) and medical comorbidity. Longitudinal surveys of selected patient groups will assess the course of psychiatric symptoms, functional impairment, and lost productivity among patients treated for depression. Computerized data systems will be used to establish a population-based registry of all patients treated for depression in a large staff-model HMO. These computerized data will be used to assess the process of care, patterns of health care utilization, and risk of suicide for all treated patients and for specific subgroups. Data analyses will examine: * the influence of incidence, episode duration, and recurrence on overall prevalence * the prevalence and impact of comorbid medical illness * the burden of depressive illness as measured by functional impairment, lost productivity, health care costs, and suicide mortality * the process of care for patients treated with antidepressants * the relationship of process to clinical and functional outcomes Results of these analyses should help direct treatment resources to groups of depressed patients for whom more intensive treatment may reduce the overall burden of illness.

抑郁症是一种常见的严重疾病， 个人痛苦、严重残疾和高昂的医疗费用。 虽然大多数抑郁症治疗试验是在专业领域进行的， 大多数抑郁症治疗发生在初级保健中。先前 研究表明，在初级保健中接受治疗的患者很少 专家建议的治疗强度。最近的数据 然而，这表明，许多接受低强度治疗的患者 短期效果良好。考虑到现有资源可用于改善 抑郁症的治疗可能仍然是有限的，干预 应重点关注那些需要更密集治疗的患者群体， 可能降低发病率、残疾或成本。拟议研究 将重点关注抑郁症的两个维度， 病程、残疾和治疗反应：治疗阶段（初始， 复发或慢性）和医学合并症。纵向调查 选定的患者组将评估精神症状的病程， 功能障碍，并在接受治疗的患者中丧失生产力 萧条计算机化数据系统将用于建立一个 一项基于人群的登记研究，对所有接受抑郁症治疗的患者进行登记， 大型员工型健康维护组织这些计算机化的数据将用于评估 护理过程、卫生保健利用模式和自杀风险 所有治疗患者和特定亚组。数据分析将 检查： * 发病率、发作持续时间和复发的影响 对总体患病率的影响 * 共病医学疾病的患病率和影响 * 抑郁症的负担， 损伤、生产力损失、医疗保健费用和自杀死亡率 * 对接受抗抑郁药治疗的患者的护理过程 * 过程与临床和功能的关系 成果 这些分析的结果应有助于指导治疗资源， 对抑郁症患者进行更密集的治疗可能会减少 疾病的总体负担。