Diagnosing and Treating Veterans with Chronic Pain and Opioid Misuse

诊断和治疗患有慢性疼痛和阿片类药物滥用的退伍军人

• 批准号: 10595496
• 负责人: Amy S B Bohnert
• 金额: --
• 依托单位: VETERANS HEALTH ADMINISTRATION
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10595496
• 关键词: Address; Affect; Algorithms; American; Analgesics; Area; Buprenorphine; Caring; Centers for Disease Control and Prevention (U.S.); Classification; Clinical; Computerized Medical Record; Consumption; Country; Data; Diagnosis; Diagnostic; Documentation; Dose; Effectiveness; Elasticity; Enrollment; Evidence based treatment; Exclusion; Exhibits; Feedback; Fright; Funding; Future; General Population; Goals; Guidelines; Harm Reduction; Health; Health Services Accessibility; Health Services Research; Individual; International Classification of Disease Codes; Intervention; Interview; Knowledge; Mental Health; Methodology; Methods; Opioid; Opioid Rotation; Outcome; Overdose; Pain; Pain intensity; Pain management; Patient Self-Report; Patient-Focused Outcomes; Patients; Pharmaceutical Preparations; Pharmacological Treatment; Pharmacy facility; Population; Process; Provider; Qualitative Methods; Research; Research Design; Risk; Risk Behaviors; Safety; Sampling; Screening procedure; Selection Bias; Signs and Symptoms; Site; Speed; Structure; Symptoms; Testing; Translating; Veterans; Veterans Health Administration; Withdrawal; Work; addiction; adverse outcome; chronic pain; chronic pain management; chronic pain patient; clinical practice; clinical research site; cohort; comparative effectiveness; comparative efficacy; compare effectiveness; cost; data warehouse; diagnostic criteria; effective therapy; evidence base; experience; falls; high risk; improved; innovation; large datasets; medication for opioid use disorder; novel; opioid misuse; opioid tapering; opioid therapy; opioid use disorder; patient oriented; patient population; patient safety; prescription opioid; prescription opioid misuse; randomized, clinical trials; recruit; research and development; safety outcomes; secondary analysis; structured data; study population; symptomatic improvement; tool; treatment strategy; trial readiness

Background: As many as 30% of the ~10 million Americans prescribed long-term opioid therapy (LTOT) are estimated to misuse opioids. Receiving LTOT is associated with opioid-related harms, and misuse leads to an increase in the dose consumed and other risky behavior, further worsening outcomes. However, there is a gap in knowledge on how to identify and treat this patient population particularly when they do not meet diagnostic criteria to be treated by medications for Opioid Use Disorder (OUD). In recent years, guidelines from the Centers for Disease Control and the Veterans Health Administration (VHA) have effected widespread tapering to reduce misuse. Buprenorphine, a medication used for both pain and OUD, may also be effective in reducing opioid-related harms while controlling pain for patients on LTOT with misuse; however, buprenorphine is yet to be tested rigorously in this patient population. Therefore, studies are needed to identify patients on LTOT with misuse and to compare the efficacy of different treatments on patient outcomes. Significance: Chronic pain, LTOT for pain, and opioid misuse are common among Veterans and lead to multiple health-related harms. The VHA has made improving pain care and reducing opioid harms a major priority of clinical initiatives, and this proposal responds to the Health Services Research and Development (HSR&D) Funding Announcement #HX-21-024 to address those opioid-related priorities. By filling a crucial evidence gap, this proposal will significantly impact the way we treat pain and minimize harm for Veterans with opioid misuse. Innovation and Impact: This proposal is innovative and impactful in many ways. First, this project will utilize the unique capabilities of the VHA’s Corporate Data Warehouse (CDW) to develop a novel algorithm to identify patients on LTOT with misuse. If successful, this automated identification process has the potential to be scaled to VHA sites across the country. Second, the comparative effectiveness of different treatments will be determined by an emulated trial, an innovative and efficient study design that can lead to greater generalizability than standard trials, which suffer significantly from selection bias in this area. The treatments being evaluated in the emulated trial are readily available, so if specific treatments are found to improve patient symptoms and reduce adverse outcomes, it will be feasible for Veterans with opioid misuse to access these treatments nationwide. Finally, we will gather feedback from providers and Veterans to understand the best strategies and interventions to scale the identification process and better inform Veterans and providers of evidence-based treatment options. Specific Aims: This project aims to 1) Classify a cohort of patients on LTOT with opioid misuse but without OUD by a) building on a previously developed augmented chart review methodology and b) applying an algorithm to structured data; 2) Conduct an emulated trial to compare the effectiveness of pharmacologic treatment options on patient-centered and patient safety outcomes; and 3) Understand current practices and how to translate our findings into improved care via semi-structured interviews with providers and Veterans. Methodology: The study population is VHA patients on LTOT with opioid misuse 2014-present. The proposal uses mixed quantitative and qualitative methods including augmented structured chart review, large dataset classification using ordinal elastic net regression, emulated trials, and qualitative interviews. Next Steps/Implementation: We expect findings to be of use to VHA leaders, prescribing clinicians, and patients with chronic pain. If successful, the automated identification process from Aim 1 could be scaled to VHA sites, and if treatments evaluated in Aim 2 are effective in improving symptoms and reducing adverse outcomes, these could also be implemented widely. In Aim 3, we will gather Veteran input on how to best implement findings from Aims 1 and Aim 2 into clinical practice in a variety of settings.

背景：在约1000万美国人的长期阿片类药物治疗（LTOT）中，有多达30%的人服用了阿片类药物