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Integrating mHealth for Alcohol Use Disorders into Clinical Practice

Integrating mHealth for Alcohol Use Disorders into Clinical Practice
将针对酒精使用障碍的移动医疗融入临床实践
批准号:
9753819
负责人:
Andrew Quanbeck
金额:
$58.9万
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-08-01 至 2023-04-30

项目摘要

项目成果

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中文摘要
翻译
项目总结/摘要 移动的健康(mHealth)技术(例如,智能手机应用程序)有可能不断 监测患者,并在需要的时间和地点提供干预措施。这些功能使mHealth 特别有希望用于治疗酒精和其它物质使用障碍。患者提供的数据 移动医疗设备还可以帮助临床医生计划治疗和对患者做出反应。然而,mHealth很少 部分原因是基于证据的移动医疗系统太少。 该项目解决了使用mHealth治疗酒精使用障碍(AUD)的潜力, 护理诊所两个问题驱动着这个项目:(1)A-CHESS是一个已经被证明的移动健康系统吗? 对因AUD而离开住院治疗的患者有效,对初级保健患者有效?(2)是 将A-CHESS整合到临床过程中的相关成本是值得的,还是足以让患者 独立使用A-CHESS,而不集成到电子健康记录和临床医生监测中? 该项目使用1型混合设计(检查患者结局和实施), 回答这些问题患者将被随机分配至(1)AUD常规治疗组,(2)临床医生介导的 患者接受A-CHESS,临床医生监测患者提供的A-CHESS数据, 仪表板集成到电子健康记录中,或(3)一个以患者为导向的小组,其中临床医生只需 鼓励患者自行使用A-CHESS。定量分析将研究 危险饮酒天数和生活质量的组,以检验患者在临床医生介导的假设, 组将有更大的改善比患者在常规护理组。此外,我们假设, 两个A-CHESS组的患者在危险饮酒天数和生活质量方面都有更大的改善, 常规护理组的患者和临床医生介导组的患者将看到最大的改善。 将进行亚组分析,以了解结局与(1)性别,(2) 患者和临床医生对A-CHESS生成的警报的响应,以及(3)A-CHESS的使用。定性 分析将主要寻求了解临床医生如何使用仪表板来监控患者护理。半- 结构化访谈将询问仪表板使用量、潜在污染(是否 临床医生使用仪表板建议的其他两组患者的方法), 进行干预。最后,成本分析将确定将A-CHESS整合到临床的成本 实践与患者独立使用A-CHESS的成本,以及临床整合A-CHESS的成本是否 CHESS被减少的AUD相关护理(例如,住院、急诊、住院 治疗和解毒)。这项研究将告知临床领导者和政策制定者是否以及如何 移动医疗系统应纳入临床护理,以治疗AUD和其他潜在的慢性疾病。
英文摘要
Project Summary/Abstract Mobile health (mHealth) technologies (e.g., smartphone applications) have the potential to continuously monitor patients and deliver interventions when and where they are needed. These features make mHealth particularly promising for the treatment of alcohol and other substance use disorders. Patient-provided data from mHealth devices could also help clinicians plan treatment and respond to patients. Yet mHealth is rarely integrated into treatment, in part because so few evidence-based mHealth systems are available. This project addresses the potential of using mHealth to treat alcohol use disorder (AUD) in primary care clinics. Two questions drive the project: (1) Is A-CHESS, an mHealth system that has been proven effective for patients leaving residential treatment for AUD, effective with patients in primary care? (2) Are the costs associated with integrating A-CHESS into clinical processes worthwhile, or does it suffice for patients to use A-CHESS independently, without integration into the electronic health record and clinician monitoring? The project uses a Type 1 hybrid design (examining both patient outcomes and implementation) to answer these questions. Patients will be randomly assigned to (1) usual care for AUD, (2) a clinician-mediated group in which patients receive A-CHESS and clinicians monitor patient-supplied A-CHESS data from a dashboard integrated into the electronic health record, or (3) a patient-directed group in which clinicians simply encourage patients to use A-CHESS on their own. The quantitative analysis will examine differences between the groups in risky drinking days and quality of life to test the hypothesis that patients in the clinician-mediated group will have greater improvements than patients in the usual care group. Additionally, we hypothesize that patients in both A-CHESS groups will have greater improvements in risky drinking days and quality of life vs. patients in the usual care group, and those in the clinician-mediated group will see the greatest improvements. Subgroup analyses will be conducted to understand the relationship between the outcomes and (1) gender, (2) patient and clinician responses to alerts generated by A-CHESS, and (3) use of A-CHESS. The qualitative analysis will mainly seek to understand how clinicians use the dashboard to monitor patient care. Semi- structured interviews will inquire about the amount of dashboard use, potential contamination (whether clinicians used approaches suggested by the dashboard with patients in the other two groups), and the quality of intervention delivery. Finally, the cost analysis will determine the cost of integrating A-CHESS into clinical practice vs. the cost of patients using A-CHESS independently, and whether the cost of clinically integrating A- CHESS is offset by savings from reduced AUD-related care (e.g., hospitalizations, ER visits, residential treatment, and detoxification). This research will inform clinical leaders and policymakers on whether and how mHealth systems should be incorporated into clinical care to treat AUD and potentially other chronic diseases.
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海外基金