The Fenway Institute, Fenway Community Health, Boston, MA, United States of America; Behavioral Medicine Program, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, United States of America; School of Social Work, Boston College, Newton, MA, United States of America.
The Fenway Institute, Fenway Community Health, Boston, MA, United States of America; Behavioral Medicine Program, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, United States of America; Harvard Medical School, Harvard University, Boston, MA, United States of America.
Contemp Clin Trials. 2021 Nov;110:106551. doi: 10.1016/j.cct.2021.106551. Epub 2021 Sep 2.
While addressing smoking cessation in the context of HIV primary care may increase the acceptability of smoking cessation treatment for patients, HIV care providers have not been trained in offering these treatments. Tools that aid providers in treatment selection, such as computer-generated algorithms, may address barriers to providing effective and efficient treatment options to their patients.
To test the effectiveness of a computer-generated smoking cessation pharmacotherapy recommendation algorithm fully integrated into HIV primary care against an enhanced usual care condition.
Six hundred adult smokers living with HIV will be recruited from 3 medical clinics that provide HIV care in Birmingham, AL, Seattle, WA, and Boston, MA. Participants will be asked to complete a baseline visit and 4 follow-up visits, which will include self-report assessments and carbon monoxide monitoring. Additionally, participants have the option to respond to weekly text-message based surveys sent over an 11-week period between baseline and end of treatment. Participants randomized to the AT condition will have a tailored, algorithm-generated smoking cessation pharmacotherapy recommendation delivered to their HIV care provider via EHR, with the potential to receive up to 12 weeks of smoking cessation pharmacotherapy.
A smoking cessation pharmacotherapy recommendation algorithm integrated into HIV primary care may increase treatment utilization and smoking abstinence among smokers living with HIV. If successful, the intervention would be ready for use across the entire CFAR Network of Integrated Clinical Systems network and, more broadly, in HIV clinics that utilize an EHR system.
在 HIV 初级保健中解决戒烟问题可能会提高患者对戒烟治疗的接受度，但 HIV 护理提供者并未接受提供这些治疗的培训。有助于提供者选择治疗方法的工具，如计算机生成的算法，可能会解决为患者提供有效和高效治疗方案的障碍。
测试完全集成到 HIV 初级保健中的计算机生成的戒烟药物治疗推荐算法对增强的常规护理条件的有效性。
将从提供 HIV 护理的伯明翰、西雅图和波士顿的 3 家医疗诊所招募 600 名成年 HIV 吸烟者。参与者将被要求完成基线访问和 4 次随访，其中包括自我报告评估和一氧化碳监测。此外，参与者可以选择在基线和治疗结束之间的 11 周期间回复每周基于文本的调查。随机分配到 AT 组的参与者将通过 EHR 获得针对其 HIV 护理提供者的个性化、算法生成的戒烟药物治疗推荐，有可能接受长达 12 周的戒烟药物治疗。
集成到 HIV 初级保健中的戒烟药物治疗推荐算法可能会增加 HIV 感染者的治疗利用率和戒烟成功率。如果成功，该干预措施将可在整个 CFAR 综合临床系统网络中使用，并且更广泛地在使用 EHR 系统的 HIV 诊所中使用。
