Traumatic Brain Injury Anti-Seizure Prophylaxis in the Medicare Program

医疗保险计划中的创伤性脑损伤抗癫痫预防

基本信息

批准号：
10715238
负责人：
Lidia Maria Veras Rocha de Moura
金额：
$ 85.42万
依托单位：
MASSACHUSETTS GENERAL HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-09-15 至 2028-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10715238
关键词：
Acute Address Admission activity Adverse effects Adverse event Age Algorithms Alzheimer&apos s disease related dementia Alzheimer&apos s disease risk Anticonvulsants Caring Clinical Clinical Trials Cognitive Data Data Set Data Sources Dementia Diagnosis Drug usage Effectiveness Elderly Electronic Health Record Emergency Situation Equilibrium Ethnic Origin Event Family Formularies Future Glasgow Coma Scale Goals Guidelines Health Health system Heterogeneity Impaired cognition Incentives Incidence Individual Inpatients Institutionalization Levetiracetam Life Link Literature Machine Learning Marketing Measures Medicare Medicare claim Medicare/Medicaid Metabolism Minority Groups Natural experiment Observational Study Outcome Pathway interactions Patients Pharmaceutical Preparations Phenytoin Physicians Policies Policy Maker Population Predisposition Prophylactic treatment Quality of life Race Recommendation Registries Risk Risk Factors Safety Science Seizures Serious Adverse Event Severities Sodium Channel Blockers Synapses TBI Patients Testing Traumatic Brain Injury Treatment Effectiveness Uncertainty Visit Work administrative database adverse event risk aged analytical tool beneficiary cerebrovascular classification algorithm clinical care cohort comorbidity comparative effectiveness study comparative safety cost dementia care design disease classification experience fall injury falls high risk improved large datasets medical specialties modifiable risk mortality neurotransmitter release novel patient population programs public health priorities recruit safety study sex side effect treatment effect treatment strategy young adult

项目摘要

Each year thousands of Medicare beneficiaries routinely receive anti-seizure medication (ASM) for prophylaxis after a traumatic brain injury (TBI). These drugs are potentially life-saving given the severity of seizure sequelae, but also potentially life-threatening because of frequent, serious adverse events, e.g., falls. Older adults with Alzheimer’s Disease and Related Dementias (ADRD) are at higher risk for TBIs and post TBI complications. They are also more vulnerable to ASM adverse effects including cognitive slowing. Despite the known delicate balance between benefit and harm, there are no trial data to guide decisions about prophylaxis after a TBI among older adults, and particularly those with ADRD. The sparse and conflicted existing literature has been limited by the difficulty assessing relevant measures, e.g., TBI severity in large data sets. Medicare claims data offer potential, but lack well-validated definitions for TBI severity or treatment-related adverse effects. We will leverage multiple novel linked data sources: Traditional Medicare claims linked to a TBI registry and Electronic Health Records (EHR) of a large regional health system, and National Medicare linked to the Minimum Dataset (a national registry of post-acute institutionalized Medicare/Medicaid beneficiaries, 2009-2022). First, we will improve classification algorithms for TBI severity for use in common administrative databases. Then, we will assess a critical decision in the setting of moderate to severe TBI, particularly among those with ADRD: stopping prophylaxis within 7 days versus continuing. We will apply multiple state-of-the science analytical tools to address confounding and other challenges. We have three aims: 1) To improve classification algorithms for TBI severity for use in common administrative databases; 2) To examine the impact of the duration of ASM prophylaxis for post-TBI patients on 6-month event rates; and 3) To examine differences in treatment effects with preexisting ADRD status. This comparative effectiveness and safety study could inform future policy and clinical care and improve TBI and ADRD care, e.g., through adjustments in Medicare quality incentives and clinical guidelines. Moreover, these data could help inform patients, families, clinicians, and policy makers about how we can improve care the rapidly expanding population of patients with ADRD.

每年，数以千计的医疗保险受益人在发生创伤性脑损伤 (TBI) 后定期接受抗癫痫药物 (ASM) 进行预防，鉴于癫痫后遗症的严重性，这些药物可能会挽救生命，但也可能因频繁发生的癫痫发作而危及生命。患有阿尔茨海默病和相关痴呆症 (ADRD) 的老年人发生 TBI 和 TBI 后并发症的风险更高，他们也更容易受到 ASM 不良反应（包括认知减慢）的影响。尽管已知益处和危害之间存在微妙的平衡，但尚无试验数据来指导老年人，特别是患有 ADRD 的 TBI 后的预防决策，现有文献的稀少且相互矛盾，因评估相关措施的困难而受到限制。大型数据集中的 TBI 严重程度数据提供了潜力，但缺乏针对 TBI 严重程度或治疗相关不良反应的经过充分验证的定义。我们将利用多个新颖的关联数据源：与 TBI 登记处和电子健康相关的传统医疗保险索赔。记录首先，我们将改进 TBI 严重程度的分类算法，以用于大型区域卫生系统的 EHR 和与最低数据集相关的国家医疗保险（急性后制度化医疗保险/医疗补助受益人的国家登记处，2009-2022 年）。然后，我们将评估中度至重度 TBI 的关键决定，特别是对于 ADRD 患者：在 7 天内停止预防还是继续预防。我们有三个目标：1）改进用于通用管理数据库的 TBI 严重程度分类算法；2）检查 ASM 预防持续时间对 TBI 后患者的影响。月事件发生率；3) 检查治疗效果与先前存在的 ADRD 状态的差异。这项比较有效性和安全性研究可以为未来的政策和临床护理提供信息，并改善 TBI 和 ADRD 护理，例如通过调整医疗保险质量激励措施和临床。此外，这些数据可以帮助患者、家庭、赞助人和政策制定者了解如何改善对迅速增加的 ADRD 患者的护理。