POPULATION BASED MANAGEMENT OF DEPRESSION

基于人群的抑郁症管理

• 批准号: 2250586
• 负责人: GREGORY G SIMON
• 金额: $ 20.59万
• 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/2250586
• 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.

抑郁症是一种常见且严重的疾病，与巨大的疾病相关 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都是在专业领域进行的 在诊所，大多数抑郁症治疗发生在初级保健中。以前的 研究表明，在初级保健中接受治疗的患者很少能接受 专家推荐的治疗强度。更多最新数据 然而，表明许多接受低强度治疗的患者 取得良好的短期成果。鉴于可用于改进的资源 抑郁症的治疗可能仍然有限，干预 应重点关注接受更强化治疗的患者群体 可能降低发病率、残疾或费用。拟议的研究 将重点关注可能影响临床的抑郁症的两个方面 病程、残疾和治疗反应：治疗阶段（初始、 复发性或慢性）和医疗合并症。纵向调查 选定的患者组将评估精神症状的过程， 接受治疗的患者的功能障碍和生产力丧失 沮丧。计算机化数据系统将用于建立 以人口为基础的登记册，记录了某个地区所有接受抑郁症治疗的患者 大型员工模式 HMO。这些计算机化数据将用于评估 护理过程、医疗保健利用模式和自杀风险 对于所有接受治疗的患者和特定亚组。数据分析将 检查： * 发病率、发作持续时间和复发的影响 总体患病率 * 合并症的患病率和影响 * 通过功能衡量的抑郁症负担 损伤、生产力损失、医疗保健费用和自杀死亡率 * 接受抗抑郁药物治疗的患者的护理过程 * 过程与临床和功能的关系 结果 这些分析的结果应有助于将治疗资源引导至 抑郁症患者群体，强化治疗可能会减少 疾病的总体负担。