Variation in the Use of Opioid Agonist Treatment in Hospitals

医院中阿片类激动剂治疗使用的变化

基本信息

批准号：
9395373
负责人：
Kelsey Caroline Priest
金额：
$ 4.23万
依托单位：
OREGON HEALTH & SCIENCE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-07-01 至 2021-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9395373
关键词：
Accreditation Address Admission activity Affect Agonist Award Buprenorphine Caring Cessation of life Clinical Data Committee Members Data Databases Disease Doctor of Philosophy Educational process of instructing Effectiveness Elements Environment Expert Opinion Fellowship Formularies Gender General Hospitals Guidelines Health Services Healthcare Hospital Mortality Hospitalization Hospitals Insurance Coverage International Intervention Interview Joints Lead Link Literature Location Long-Term Care Maintenance Measurable Measures Mediating Medication Management Medicine Meta-Analysis Methadone Methods Modeling Naloxone National Institute of Drug Abuse Opioid Outcome Outpatients Overdose Patient-Focused Outcomes Patients Persons Pharmaceutical Preparations Pharmacotherapy Pharmacy facility Physicians Physicians&apos Offices Policies Prevalence Protocols documentation Public Health Race Recording of previous events Reporting Research Research Methodology Research Personnel Residential Treatment Resources Sampling State Hospitals Structure System Teaching Hospitals Testing Therapeutic Training Treatment outcome Uninsured United States Variant Withdrawal addiction base billing data career contextual factors evidence base experience federal policy health care delivery informant mental health center multilevel analysis opioid use opioid use disorder symptom management

项目摘要

PROJECT SUMMARY/ABSTRACT Persons with opioid use disorder (OUD) have longer and more expensive hospitalizations (over $15 billion annually) than general hospital admissions. Despite the magnitude of this issue, little research describes hospital use of evidence-based opioid agonist treatments (OATs). I propose to assess hospital variation, model associations with patient and hospital attributes, and explore hospital structures influencing OAT delivery in the context of local and broader environments. There are three OAT (continuation of pre-hospital OAT, OAT for withdrawal management, and OAT initiation for long-term care) and three non-OAT (short-acting opioids, symptom management medications, and other care) OUD care scenarios. I will measure patient disposition and 30-day readmissions for each care scenario. This study leverages health service delivery conceptual frameworks and a multilevel change model using a mixed methods approach. The study addresses two quantitative aims (analysis of OUD hospital admissions in the Premier Healthcare Database) and one qualitative aim (interviews with 20 hospital key informants from a purposive sample of 10 to 12 hospitals). Specific Aim 1. Assess variation in hospital OAT delivery and test the associations of OAT and non- OAT care scenarios with attributes and outcomes. I will evaluate whether meaningful variation exists in hospital OAT delivery and whether patient attributes (e.g., gender), hospital attributes (e.g., size) and patient outcomes (e.g., disposition) are associated with the provision of OAT in the hospital. H1a: Measurable differences exist among hospital OAT quartiles and between top and bottom OAT quartiles. H1b: Hospital OAT quartiles will be associated with at least one patient attribute, one hospital attribute, and one patient outcome domain. Specific Aim 2. Model and test the proposed relationships of patient and hospital attributes on hospital OAT delivery and patient outcomes. I will use multilevel modeling to identify specific associations of patient (e.g., race) and hospital (e.g., teaching status) attributes with hospital OAT variation, patient outcomes, and between-hospital variation. H2a: OAT delivery will be negatively associated with patient race (non-white), insurance status (uninsured), and hospital teaching status (non-teaching). H2b: In-hospital mortality and 30-day readmissions will be negatively associated with hospital OAT delivery. Specific Aim 3. Use qualitative interviews with key hospital informants to explore the environmental context and hospital structures that may mediate hospital OAT delivery. Findings from Aims 1 and 2 guide the purposive sampling and interview protocol for the key informant interviews. I will probe for local hospital (e.g., addiction medicine fellowship) and broader environmental contextual factors (e.g., federal policy) that may influence hospital structures (e.g., formulary) impeding or facilitating hospital OAT delivery.

项目摘要/摘要阿片类药物使用障碍（OUD）的患者拥有更长且更昂贵的住院治疗（超过150亿美元每年）比综合医院入院。尽管这个问题的幅度很大，但很少的研究描述医院使用基于证据的阿片类药物激动剂治疗（燕麦）。我建议评估医院变化，模型与患者和医院属性的关联，并探索影响燕麦递送的医院结构本地和更广泛的环境的背景。有三只燕麦（院前燕麦的延续，燕麦撤回管理和长期护理的燕麦启动）和三个非围坐（短效阿片类药物）症状管理药物和其他护理）场景。我将衡量患者的性格和每个护理方案的30天再入院。这项研究利用卫生服务提供概念使用混合方法方法的框架和多级变更模型。该研究针对两个定量目标（对总理医疗保健数据库中的OUD医院入院分析），一个定性目标（对10至12家医院的有目的样本的20位医院主要线人的访谈）。具体目的1。评估医院燕麦量的变化并测试燕麦与非燕麦的关联具有属性和结果的燕麦护理方案。我将评估是否存在有意义的变化医院燕麦递送以及患者属性（例如性别），医院属性（例如，大小）和患者结果（例如，处置）与医院的燕麦提供有关。 H1A：医院燕麦四分位数以及顶部和底部燕麦四分位数之间存在可测量的差异。 H1B：医院燕麦四分位数将与至少一个患者属性，一个医院属性和一个患者结果领域。特定目的2。模型并测试患者和医院属性的拟议关系医院燕麦递送和患者预后。我将使用多级建模来识别特定的关联患者（例如，种族）和医院（例如教学状态）属性，患者的属性结果和院之间变化。 H2A：燕麦交付将与患者种族（非白人），保险状况（未保险），燕麦交付负相关，和医院教学状况（非教学）。 H2B：住院死亡率和30天的再入院率将与医院燕麦送达负相关。特定目标3。使用与主要医院线人的定性访谈探索环境可以介导医院燕麦递送的上下文和医院结构。目标1和2的发现指导目的抽样和采访协议，以进行关键线人访谈。我会探究本地医院（例如成瘾医学奖学金）和更广泛的环境背景因素（例如，联邦政策）这可能会影响医院结构（例如，配方）阻碍或促进医院燕麦的交付。