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Diagnosing and Treating Veterans with Chronic Pain and Opioid Misuse

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:
$0.0万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-01-01 至 2025-12-31
关键词:
AddressAffectAlgorithmsAmericanAnalgesicsAreaBuprenorphineCaringCenters for Disease Control and Prevention (U.S.)ClassificationClinicalComputerized Medical RecordConsumptionCountryDataDiagnosisDiagnosticDocumentationDoseEffectivenessElasticityEnrollmentEvidence based treatmentExclusionExhibitsFeedbackFrightFundingFutureGeneral PopulationGoalsGuidelinesHarm ReductionHealthHealth Services AccessibilityHealth Services ResearchIndividualInternational Classification of Disease CodesInterventionInterviewKnowledgeMental HealthMethodologyMethodsOpioidOpioid RotationOutcomeOverdosePainPain intensityPain managementPatient Self-ReportPatient-Focused OutcomesPatientsPharmaceutical PreparationsPharmacological TreatmentPharmacy facilityPopulationProcessProviderQualitative MethodsResearchResearch DesignRiskRisk BehaviorsSafetySamplingScreening procedureSelection BiasSigns and SymptomsSiteSpeedStructureSymptomsTestingTranslatingVeteransVeterans Health AdministrationWithdrawalWorkaddictionadverse outcomechronic painchronic pain managementchronic pain patientclinical practiceclinical research sitecohortcomparative effectivenesscomparative efficacycompare effectivenesscostdata warehousediagnostic criteriaeffective therapyevidence baseexperiencefallshigh riskimprovedinnovationlarge datasetsmedication for opioid use disordernovelopioid misuseopioid taperingopioid therapyopioid use disorderpatient orientedpatient populationpatient safetyprescription opioidprescription opioid misuserandomized, clinical trialsrecruitresearch and developmentsafety outcomessecondary analysisstructured datastudy populationsymptomatic improvementtooltreatment strategytrial readiness

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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.
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Mobile Technology to Optimize Depression Treatment
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Diagnosing and Treating Veterans with Chronic Pain and Opioid Misuse
  • 批准号:
    10313694
  • 项目类别:
  • 资助金额:
    $0.0万
  • 财政年份:
    2022
  • 负责人:
    Amy S B Bohnert
  • 依托单位:
Reducing Non-Medical Opioid Use: An automatically adaptive mHealth Intervention
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