Opioid Overdoses among Medicaid Beneficiaries: Predictors, Outcomes, and State Policy Effects

医疗补助受益人中阿片类药物过量：预测因素、结果和国家政策影响

• 批准号: 10348125
• 负责人: Stephen Crystal
• 金额: $ 79.29万
• 依托单位: RUTGERS, THE STATE UNIV OF N.J.
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-03-01 至 2025-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10348125
• 关键词: Address; Adult; Affect; Alcohols; Benzodiazepines; Caring; Cause of Death; Cessation of life; Characteristics; Clinical; Clinical Management; Clinical Treatment; Communities; Complex; Contracts; Data; Diagnosis; Disease; Event; Goals; Health Policy; Health system; Healthcare Systems; Incidence; Individual; Intervention; Knowledge; Link; Medicaid; Medical; Mental Health; Missouri; Modeling; Natural experiment; New Jersey; Opiate Addiction; Opioid; Outcome; Overdose; Pain management; Patients; Pattern; Play; Policies; Polypharmacy; Population; Predictive Factor; Public Health; Risk; Risk Reduction; Role; Spottings; Statutes and Laws; Substance abuse problem; Suicide; Survivors; System; Treatment outcome; Update; Variant; beneficiary; clinical risk; cohort; comorbidity; disability; dosage; experience; experimental study; heroin use; high risk; high risk population; improved; improved outcome; indexing; medication-assisted treatment; multiple chronic conditions; opioid abuse; opioid epidemic; opioid overdose; opioid use; opioid use disorder; outcome prediction; overdose prevention; overdose risk; prescription opioid; programs; respiratory; response; success; systemic intervention; treatment disparity; treatment services

Reducing opioid overdose is an urgent national goal that needs to be supported with the best available understanding of the clinical, treatment, and health system factors that predict overdoses, and points of intervention for their reduction. For individuals surviving medically treated overdoses, there is a need to better understand the factors affecting risk of fatal overdose, including effects of post-overdose treatment, in order to reduce the death toll in this high-risk population. To inform systemic intervention, there is an urgent need for evidence on the role of state policies in reducing risk and improving outcomes. These issues are particularly vital in the Medicaid population, which contributes disproportionately to the national overdose toll. To build evidence on these vital issues, we will use 45-state Medicaid data from 2001-2019, linked to the National Death Index (NDI), supplemented with regularly updated state data from New Jersey and Missouri, to identify the interacting factors contributing to overdose risk and to outcomes for overdose survivors. Under Aim 1, overdose risk will be examined in national incidence cohorts of Medicaid beneficiaries with new episodes of persistent opioid use, and those with new diagnoses of opioid use disorder (OUD). To analyze both non-fatal and fatal overdoses, we will link Medicaid data with the NDI for 50,000 individuals with new persistent use, and 50,000 individuals with new OUD diagnoses, for each year of the Medicaid data, totaling 950,000 in each cohort over the study period. Under Aim 2, we will examine treatment engagement and survival following non-fatal medically treated overdoses, linking Medicaid and NDI data on these overdoses to identify factors affecting post-overdose treatment and outcomes. Under Aim 3, we will examine the impact of an important natural experiment in state policy: the 2017 enactment of major New Jersey legislation. Changes included new limitations on opioid prescribing; use of pain management contracts; and expanded access to medication assisted treatment (MAT) for opioid use disorder. Substantial increases in Medicaid rates for MAT and other OUD treatment were implemented concurrently. Using analytic models similar to those in Aims 1 and 2, we will examine changes in overdose risk among individuals with new long- term opioid use, and among those with new OUD diagnoses, before and after the implementation of the new legislation, relative to comparison populations in states that did not implement similar policies. These analyses will advance our fundamental understanding of opioid risks and outcomes in the Medicaid population with its distinctive demographic characteristics and clinical challenges. By grounding intervention policy in a more comprehensive understanding of overdose risk, and the complex intersection of disability, multi-morbidity, and treatment services within which overdose events are embedded, results can change the paradigm of overdose prevention to one that is informed by a better understanding of these events and the individuals experiencing them.

减少阿片类药物过量是一项紧迫的国家目标，需要得到最好的支持 了解预测用药过量的临床、治疗和卫生系统因素以及注意事项 干预以减少它们。对于服药过量后幸存的人来说，需要更好地 了解影响致命过量风险的因素，包括过量后治疗的影响，以便 减少这一高危人群的死亡人数。为了为系统干预提供信息，迫切需要 关于国家政策在降低风险和改善结果方面的作用的证据。这些问题尤其 对医疗补助人群至关重要，这对全国药物过量死亡人数造成了不成比例的影响。 为了就这些重要问题建立证据，我们将使用 2001 年至 2019 年 45 个州的医疗补助数据，这些数据链接到 国家死亡指数 (NDI)，并定期更新新泽西州和 密苏里州，确定导致用药过量风险和用药过量结果的相互作用因素 幸存者。根据目标 1，将在医疗补助受益人的国家发病率队列中检查用药过量风险 出现新的持续阿片类药物使用事件，以及新诊断出阿片类药物使用障碍 (OUD) 的患者。到 分析非致命和致命的用药过量，我们将把医疗补助数据与 NDI 联系起来，涉及 50,000 名患有以下疾病的人： 医疗补助数据每年都有新的持续使用，以及 50,000 名新的 OUD 诊断患者， 研究期间每个队列的人数总计为 950,000 人。在目标 2 下，我们将检查治疗参与度 以及非致命性药物治疗过量后的生存率，将医疗补助和 NDI 数据与这些数据联系起来 药物过量以确定影响药物过量后治疗和结果的因素。在目标 3 下，我们将检查 一项重要的自然实验对国家政策的影响：2017 年新泽西州重大法案的颁布 立法。变化包括阿片类药物处方的新限制；使用疼痛管理合同；和 扩大阿片类药物使用障碍的药物辅助治疗 (MAT) 范围。大幅增加 MAT 和其他 OUD 治疗的医疗补助费率同时实施。使用分析模型 与目标 1 和 2 类似，我们将检查新长期服用药物的个体中药物过量风险的变化。 术语阿片类药物的使用，以及新 OUD 诊断的患者，在新政策实施之前和之后 立法，相对于未实施类似政策的国家的比较人口。 这些分析将增进我们对阿片类药物风险和结果的基本了解 医疗补助人群具有独特的人口特征和临床挑战。通过接地 更全面地了解用药过量风险的干预政策以及复杂的交叉点 残疾、多种疾病和包含过量事件的治疗服务，结果可以 将过量预防的范式转变为通过更好地了解这些事件而获得信息的范式 以及经历它们的个人。