Gallo Carlos, Abram Karen, Hannah Nanette, Caton Lauren, Cimaglio Barbara, McGovern Mark, Brown C Hendricks
Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States of America.
Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, California, United States of America.
PLoS One. 2021 Jan 28;16(1):e0245920. doi: 10.1371/journal.pone.0245920. eCollection 2021.
Between January 2016 and June 2020, the Substance Abuse and Mental Health Services Administration rapidly distributed $7.5 billion in response to the U.S. opioid crisis. These funds are designed to increase access to medications for addiction treatment, reduce unmet treatment need, reduce overdose death rates, and provide and sustain effective prevention, treatment and recovery activities. It is unclear whether or not the services developed using these funds will be sustained beyond the start-up period. Based on 34 (64%) State Opioid Response (SOR) applications, we assessed the states' sustainability plans focusing on potential funding sources, policies, and quality monitoring. We found variable commitment to sustainability across response plans with less than half the states adequately describing sustainability plans. States with higher proportions of opioid prescribing, opioid misuse, and poverty had somewhat higher scores on sustainment. A text mining/machine learning approach automatically rated sustainability in SOR applications with an 82% accuracy compared to human ratings. Because life saving evidence-based programs and services may be lost, intentional commitment to sustainment beyond the bolus of start-up funding is essential.
2016年1月至2020年6月期间，美国药物滥用和精神健康服务管理局迅速发放了75亿美元，以应对美国的阿片类药物危机。这些资金旨在增加获得成瘾治疗药物的机会，减少未满足的治疗需求，降低过量死亡率，并提供和维持有效的预防、治疗及康复活动。目前尚不清楚利用这些资金开展的服务在启动期之后是否能够持续下去。基于34份（64%）州阿片类药物应对（SOR）申请，我们评估了各州的可持续性计划，重点关注潜在的资金来源、政策和质量监测。我们发现，不同应对计划对可持续性的承诺程度各不相同，只有不到一半的州充分描述了可持续性计划。阿片类药物处方、阿片类药物滥用和贫困比例较高的州在可持续性方面的得分略高。一种文本挖掘/机器学习方法对SOR申请中的可持续性进行自动评分，与人工评分相比，准确率达到82%。由于可能会失去挽救生命的循证项目和服务，因此在启动资金之外有意致力于维持这些项目和服务至关重要。
