Computerized Decision Support System for Depression

抑郁症计算机化决策支持系统

• 批准号: 6747253
• 负责人: MADHUKAR H. TRIVEDI
• 金额: $ 69.82万
• 依托单位: UT SOUTHWESTERN MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-05-12 至 2008-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6747253
• 关键词: clinical research; computer assisted medical decision making; health care cost /financing; health care service evaluation; health care service utilization; health services research tag; human subject; major depression; patient care management; patient oriented research; therapy compliance

DESCRIPTION (provided by applicant): This study proposes to test the clinical effectiveness of a Computerized Decision Support System for Depression (CDSS-D) in improving treatment outcomes for patients with a major depressive disorder (MDD). The Texas Medication Algorithm Project (TMAP) MDD algorithm provides the framework for the clinical content in the CDSS-D. The algorithm is an evidence-based algorithm that was developed by an expert consensus panel that included national experts in depression, local physicians, consumers and advocates. The CDSS-D is designed to ensure a high degree of adherence to a well-developed pharmacological algorithm for the treatment of MDD in the public health sector. After the initial database and rules engine for the CDSS-D application were developed, reliability testing was conducted. The last phase of testing involved psychiatrists using the CDSS-D program in two public mental health clinics. The field study demonstrated feasibility and acceptability of the CDSS-D. The proposed study will entail implementation at three mental health facilities (Bluebonnet Trails Community MHMR Center, Parkland Memorial Hospital Outpatient Clinic, and Texas Panhandle MHMR Center) in order to assess the effectiveness of the CDSS-D system. Psychiatrists will be randomized either to the computerized algorithm (CDSS-D), the paper and pencil algorithm for the treatment of depression (PPA-D), or Usual Care for Depression (UC-D). Physicians randomized to an algorithm treatment group will attend an additional workshop on the implementation of treatment algorithms, and they will be trained in the use of either the computerized algorithm platform or the use of a paper-pencil version of the algorithm. A total of 540 participants will be enrolled into the study who have major depressive disorder and are either entering treatment or are requiring a change in their treatment. The patient outcomes in the CDSS-D, PPA-D, and UC-D will be evaluated in terms of clinical symptoms, function, and quality of life (aim 1) assessed by an evaluator, blind to treatment assignment, every 3 months for a total of 12 months. The primary aims of the study are to: 1) assess the of CDSS-D implementation in terms of patient outcomes (reduction of symptoms, changes in level of functioning, and quality of life measures); 2) conduct an assessment of cost and utilization of the CDSS-D in a the public mental health sector; 3) directly assess the extent that the CDSS-D influences physician behavior; and 4) To compare the difference in patient outcomes with the difference in cost in the CDSS-D. Comparisons will be made between CDSS-D, PPA-D, and UC-D.

描述（由申请人提供）：本研究旨在测试抑郁症计算机决策支持系统（CDSS-D）在改善重度抑郁症（MDD）患者治疗结局方面的临床有效性。德克萨斯药物算法项目（TMAP）MDD算法为CDSS-D中的临床内容提供了框架。该算法是一种基于证据的算法，由专家共识小组开发，该小组包括国家抑郁症专家，当地医生，消费者和倡导者。CDSS-D旨在确保在公共卫生部门高度遵守用于治疗MDD的成熟药理学算法。在为CDSS-D应用程序开发了初始数据库和规则引擎之后，进行了可靠性测试。最后一阶段的测试涉及在两个公共精神卫生诊所使用CDSS-D程序的精神科医生。现场研究证明了CDSS-D的可行性和可接受性。拟议的研究将需要在三个精神卫生设施（Bluebonnet Trails社区MHMR中心，帕克兰纪念医院门诊和德克萨斯州潘汉德尔MHMR中心）实施，以评估CDSS-D系统的有效性。精神科医生将被随机分配到计算机化算法（CDSS-D），用于治疗抑郁症的纸笔算法（PPA-D）或抑郁症的家庭护理（UC-D）。随机分配到算法治疗组的医生将参加关于实施治疗算法的额外研讨会，他们将接受计算机化算法平台使用或算法纸笔版本使用的培训。共有540名患有重度抑郁症的参与者将入组本研究，他们要么正在接受治疗，要么需要改变治疗。CDSS-D、PPA-D和UC-D中的患者结局将在临床症状、功能和生活质量（目标1）方面进行评价，评价者对治疗分配不知情，每3个月进行一次，共12个月。该研究的主要目的是：1）评估CDSS-D实施对患者结局的影响（症状的减轻、功能水平的改变和生活质量测量）; 2）在公共精神卫生部门进行CDSS-D的成本和利用的评估; 3）直接评估CDSS-D影响医生行为的程度; 4）比较CDSS-D中患者结局的差异与成本的差异。将在CDSS-D、PPA-D和UC-D之间进行比较。