Suppr超能文献

创建一种算法,为初级保健中使用丁丙诺啡治疗阿片类药物使用障碍提供临床决策支持。

Creation of an algorithm for clinical decision support for treatment of opioid use disorder with buprenorphine in primary care.

机构信息

Department of Psychiatry, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390, USA.

出版信息

Addict Sci Clin Pract. 2021 Feb 19;16(1):12. doi: 10.1186/s13722-021-00222-0.

Abstract

BACKGROUND

The treatment capacity for opioid use disorder (OUD) lags far behind the number of patients in need of treatment. Capacity is limited, in part, by the limited number of physicians who offer office based OUD treatment with buprenorphine. Measurement based care (MBC) has been proposed as a means to support primary care physicians in treating OUD. Here, we propose a set of measures and a clinical decision support algorithm to provide MBC for the treatment of OUD.

METHODS

We utilized literature search and expert consensus to identify measures for universal screening and symptom tracking. We used expert consensus to create the clinical decision support algorithm.

RESULTS

The Tobacco, Alcohol, Prescription medication, and other Substance use (TAPS) tool was selected as the best published measure for universal screening in primary care. No published measure was identified as appropriate for symptom tracking or medication adherence; therefore, we created the OUD Symptom Checklist from the DSM-5 criteria for OUD and the Patient Adherence Questionnaire for Opioid Use Disorder Treatment (PAQ-OUD) to assess medication adherence. We developed and present a clinical decision support algorithm to provide direct guidance regarding treatment interventions during the first 12 weeks of buprenorphine treatment.

CONCLUSION

Creation of these tools is the necessary first step for implementation of MBC for the treatment of OUD with buprenorphine in primary care. Further work is needed to test the feasibility and acceptability of these tools. Trial Registration ClinicalTrials.gov; NCT04059016; 16 August 2019; retrospectively registered; https://clinicaltrials.gov/ct2/show/NCT04059016.

摘要

背景

阿片类药物使用障碍(OUD)的治疗能力远远落后于需要治疗的患者数量。能力有限,部分原因是提供办公室内 OUD 治疗伴丁丙诺啡的医生人数有限。基于测量的护理(MBC)已被提议作为支持初级保健医生治疗 OUD 的一种手段。在这里,我们提出了一组措施和临床决策支持算法,为 OUD 的治疗提供 MBC。

方法

我们利用文献检索和专家共识来确定用于普遍筛查和症状跟踪的措施。我们使用专家共识来创建临床决策支持算法。

结果

烟草、酒精、处方药物和其他物质使用(TAPS)工具被选为初级保健中普遍筛查的最佳已发表措施。没有发现合适的已发表措施用于症状跟踪或药物依从性;因此,我们根据 OUD 的 DSM-5 标准和阿片类药物使用障碍治疗患者依从性问卷(PAQ-OUD)创建了 OUD 症状清单,以评估药物依从性。我们开发并提出了一个临床决策支持算法,在丁丙诺啡治疗的前 12 周内为治疗干预提供直接指导。

结论

这些工具的创建是在初级保健中使用丁丙诺啡治疗 OUD 实施 MBC 的必要第一步。需要进一步的工作来测试这些工具的可行性和可接受性。

试验注册

ClinicalTrials.gov;NCT04059016;2019 年 8 月 16 日;回顾性注册;https://clinicaltrials.gov/ct2/show/NCT04059016。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a21/7893913/d59f0a461743/13722_2021_222_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验