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 了解预测过量用药的临床、治疗和卫生系统因素，以及 进行干预以减少他们的数量。对于在药物过量治疗中存活下来的个人来说，有必要更好地 了解影响服药过量致死风险的因素，包括服药过量后治疗的影响，以便 减少这一高危人群的死亡人数。为了向系统性干预提供信息，迫切需要 国家政策在降低风险和改善结果方面的作用的证据。这些问题尤其是 在医疗补助人口中至关重要，这对全国过量服药人数的贡献不成比例。 为了在这些重要问题上建立证据，我们将使用2001-2019年45个州的医疗补助数据，这些数据与 国家死亡指数(NDI)，补充了新泽西州和 密苏里州，以确定导致过量服药风险和过度服药后果的相互作用因素 幸存者。根据目标1，将在医疗补助受益人的全国发病队列中检查过量用药的风险 持续使用阿片类药物的新发作，以及那些被新诊断为阿片使用障碍的人(OUD)。至 分析非致命和致命的过量用药，我们将把医疗补助数据与NDI联系起来， 新的持续使用，以及每年医疗补助数据的50,000名新的OUD诊断患者， 在研究期间，每个队列总共有950,000人。在目标2下，我们将审查治疗参与度 以及非致命性药物过量治疗后的存活率，将医疗补助和NDI数据联系起来 过量用药以确定影响过量用药后治疗和结果的因素。在目标3下，我们将审查 州政策中一项重要的自然实验的影响：2017年新泽西州主要法案的颁布 立法。变化包括对阿片类药物处方的新限制；使用疼痛管理合同；以及 扩大获得阿片类药物使用障碍的药物辅助治疗(MAT)的机会。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和目标2中的类似，我们将检查患有新的长期服用药物的个人过量服药风险的变化。 长期阿片类药物的使用，以及在新的OUD诊断中，在新的实施前后 立法，相对于没有实施类似政策的州的比较人口。 这些分析将促进我们对阿片类药物风险和结果的基本理解 医疗补助人群以其鲜明的人口学特征和临床挑战。通过停飞 干预政策在更全面地了解服药过量的风险，以及复杂的交叉点 残疾、多种疾病和治疗服务，其中包含过量用药事件，结果可能 将预防过量用药的范例改为通过更好地了解这些事件而获得信息的范例 以及经历它们的个体。