Journal of opioid management · 2017
Educational intervention for physicians to address the risk of opioid abuse.
Сравнительное исследованиеСтатьяРандомизированное исследованиеПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Pasquale Margaret K, Sheer Richard L, Mardekian Jack, Masters Elizabeth T, Patel Nick C, Hurwitch Amy R, Weber Jennifer J, Jorga Anamaria, Roland Carl L
Аннотация
OBJECTIVE: To evaluate the impact of a pilot intervention for physicians to support their treatment of patients at risk for opioid abuse.
SETTING, DESIGN AND PATIENTS, PARTICIPANTS: Patients at risk for opioid abuse enrolled in Medicare plans were identified from July 1, 2012 to April 30, 2014 (N = 2,391), based on a published predictive model, and linked to 4,353 opioid-prescribing physicians. Patient-physician clusters were randomly assigned to one of four interventions using factorial design.
INTERVENTIONS: Physicians received one of the following: Arm 1, patient information; Arm 2, links to educational materials for diagnosis and management of pain; Arm 3, both patient information and links to educational materials; or Arm 4, no communication.
MAIN OUTCOME MEASURES: Difference-in-difference analyses compared opioid and pain prescriptions, chronic high-dose opioid use, uncoordinated opioid use, and opioid-related emergency department (ED) visits. Logistic regression compared diagnosis of opioid abuse between cases and controls postindex.
RESULTS: Mailings had no significant impact on numbers of opioid or pain medications filled, chronic high-dose opioid use, uncoordinated opioid use, ED visits, or rate of diagnosed opioid abuse. Relative to Arm 4, odds ratios (95% CI) for diagnosed opioid abuse were Arm 1, 0.95(0.63-1.42); Arm 2, 0.83(0.55-1.27); Arm 3, 0.72(0.46-1.13). While 84.7 percent had ≥1 psychiatric diagnoses during preindex (p = 0.89 between arms), only 9.5 percent had ≥1 visit with mental health specialists (p = 0.53 between arms).
CONCLUSIONS: Although this intervention did not affect pain-related outcomes, future interventions involving care coordination across primary care and mental health may impact opioid abuse and improve quality of life of patients with pain.
SETTING, DESIGN AND PATIENTS, PARTICIPANTS: Patients at risk for opioid abuse enrolled in Medicare plans were identified from July 1, 2012 to April 30, 2014 (N = 2,391), based on a published predictive model, and linked to 4,353 opioid-prescribing physicians. Patient-physician clusters were randomly assigned to one of four interventions using factorial design.
INTERVENTIONS: Physicians received one of the following: Arm 1, patient information; Arm 2, links to educational materials for diagnosis and management of pain; Arm 3, both patient information and links to educational materials; or Arm 4, no communication.
MAIN OUTCOME MEASURES: Difference-in-difference analyses compared opioid and pain prescriptions, chronic high-dose opioid use, uncoordinated opioid use, and opioid-related emergency department (ED) visits. Logistic regression compared diagnosis of opioid abuse between cases and controls postindex.
RESULTS: Mailings had no significant impact on numbers of opioid or pain medications filled, chronic high-dose opioid use, uncoordinated opioid use, ED visits, or rate of diagnosed opioid abuse. Relative to Arm 4, odds ratios (95% CI) for diagnosed opioid abuse were Arm 1, 0.95(0.63-1.42); Arm 2, 0.83(0.55-1.27); Arm 3, 0.72(0.46-1.13). While 84.7 percent had ≥1 psychiatric diagnoses during preindex (p = 0.89 between arms), only 9.5 percent had ≥1 visit with mental health specialists (p = 0.53 between arms).
CONCLUSIONS: Although this intervention did not affect pain-related outcomes, future interventions involving care coordination across primary care and mental health may impact opioid abuse and improve quality of life of patients with pain.
Предметные рубрики MeSH
Administrative Claims, HealthcareAgedAnalgesics, OpioidChronic PainDrug PrescriptionsDrug UsersEducation, Medical, ContinuingFemaleHumansInservice TrainingLogistic ModelsMaleMedicareMiddle AgedMultivariate AnalysisOpioid-Related DisordersPain ManagementPhysiciansPilot ProjectsPractice Patterns, Physicians'Risk AssessmentRisk FactorsSubstance-Related DisordersTime FactorsTreatment OutcomeUnited States