PREDICTION OF ALCOHOL TREATMENT DROP-OUT VIA IVR

通过 IVR 预测酒精治疗退出

• 批准号: 6213311
• 负责人: JAMES C. MUNDT
• 金额: $ 16.45万
• 依托单位: HEALTHCARE TECHNOLOGY SYSTEMS, LLC
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-22 至 2002-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6213311
• 关键词: alcoholism /alcohol abuse therapy; behavior prediction; computer human interaction; computer program /software; computer system design /evaluation; human subject; neuropsychological tests; self help; therapy compliance; voice

This application proposes to develop and implement an interactive voice response (IVR) program to obtain self-report and neuropsychological data from 120 treatment-seeking patients that is predictive of alcohol treatment drop-out with six weeks of treatment intake. The proposed research will compare the neuropsychological data collected by IVR to data obtained using computer software that has previously been validated. Machine learning algorithms will be applied to the IVR data to derive models predictive of treatment drop-out. The generalizability of these models will be evaluated using an independent validation sample. PROPOSED COMMERCIAL APPLICATIONS: Substance abuse treatment trends toward increased treatment durations with decreased intensity cannot succeed if patients discontinue treatment soon after initiation. An inexpensive, telephone driven computer system that provided valid prognostic information offers both the providers and payors of services opportunities to develop and enhance more effective treatment programs in an increasingly competitive marketplace.

该应用建议开发和实施交互式语音反应（IVR）计划，以从120名寻求治疗的患者中获取自我报告和神经心理学数据，这些患者可预测酒精治疗降级，并通过六周的治疗摄入量进行。 拟议的研究将比较IVR收集的神经心理学数据与先前已验证的计算机软件获得的数据。 机器学习算法将应用于IVR数据，以得出预测治疗辍学的模型。这些模型的普遍性将使用独立的验证样本进行评估。拟议的商业应用：如果患者在开始后不久停止治疗，则滥用药物治疗趋势无法成功。提供有效的预后信息的廉价，电话驱动的计算机系统为服务提供者和付款人提供了开发和增强竞争激烈的市场中更有效治疗计划的机会。