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Modeling opioid addiction treatment policies using system dynamics

机译:使用系统动态建模阿片类成瘾治疗政策

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Treatment of opioid addiction has historical employed an opioid drug called Methadone that is dispensed in liquid form at treatment facilities. Drawbacks to this treatment include social stigma and relatively high risk due to the pharmacological properties of methadone and also its side effects. A newer therapy uses another opioid drug called Buprenorphine, which is safer and has less social stigma because it can be prescribed and dispensed in tablet form. Policy makers have been cautious, however, and have place a cap on the number of patients that a physician can treat using Buprenorphine, leading to a concern that even though it is safer, people seeking treatment might not be able to locate a physician and access the treatment because of the cap. An SD model was developed to represent the flows of opioid abusers into and out of treatment with Buprenorphine, as well as the number of physicians certified to treat with Buprenorphine. Treatment is constrained by the cap and also by the amount of budget available for subsidizing treatment. The main finding is the treatment budget is by far the most influential policy variable, and that changing the cap would probably not make much difference.
机译:阿片类药物成瘾的治疗历史使用了一种称为美沙酮的阿片类药物,该药物在治疗设施中以液体形式分配。这种治疗的缺点包括由于美沙酮的药理学性质以及其副作用,因此具有社会耻辱和较高的风险。较新的疗法使用另一个称为丁丙诺啡的阿片类药物,这更安全,并且具有较少的社交耻辱,因为它可以以片状形式规定和分配。然而,政策制定者一直谨慎,并且已经有一章,医生可以使用丁丙诺啡可以治疗的患者的数量,导致令人担忧,即使它更安全,寻求治疗的人可能无法找到医生和访问由于帽子而治疗。开发了一个SD模型,以代表阿片类药物的流动与丁丙诺啡的侵入和脱离治疗,以及用丁丙诺啡治疗的医生数量。治疗受到上限的限制,也受到补贴治疗的预算金额。主要发现是治疗预算是迄今为止最有影响力的政策变量,而改变帽子可能不会产生太大差异。

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