Physician Prescribing Patterns and Risk of Future Long-Term Opioid Use Among Patients With Rheumatoid Arthritis: A Prospective Observational Cohort Study.
Physician Prescribing Patterns and Risk of Future Long-Term Opioid Use Among Patients With Rheumatoid Arthritis: A Prospective Observational Cohort Study.
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类风湿关节炎患者的医生处方模式和未来长期使用阿片类药物的风险：一项前瞻性观察队列研究。
DOI：
10.1002/art.41240
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Solomon,DanielH
中科院分区：
文献类型：
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作者：
Lee,YvonneC;Lu,Bing;Guan,Hongshu;Greenberg,JeffreyD;Kremer,Joel;Solomon,DanielH
目的 确定美国类风湿性关节炎 (RA) 患者阿片类药物处方率的差异程度，并确定基线阿片类药物处方率对未来长期使用阿片类药物的可能性的影响。方法我们从参与 Corrona RA 登记的前 12 个月内贡献 ≥10 名患者的医生中筛选出 RA 患者。基线阿片类药物处方率的计算方法是将前 12 个月内报告阿片类药物使用的 RA 患者人数除以当年提供数据的 RA 患者人数。为了估计长期阿片类药物使用的比值比 (OR)，我们使用了广义线性混合模型。 结果在随访期间，阿片类药物处方率极低（参考）的医生的患者中，有 7.0%（2,322 名中的 163 名）患者报告长期使用阿片类药物，而处方率低的医生中，这一比例为 6.8%（2,254 名中的 153 名） 12.5%（2,352 名患者中的 294 名）患者的处方率为中等，12.7%（2,409 名中的 307 名）患者的医生为高处方率。基线期后长期使用阿片类药物的 OR，对于低强度处方医生的患者为 1.16（95% 置信区间 [95% CI] 0.79-1.70），对于中等强度处方医生的患者为 1.89（95% CI 1.27-2.82），对于 2.01（95% CI 1.43-2.83）。与低强度处方医生相比，高强度处方医生的患者。结论阿片类药物处方率差异很大。我们的研究结果表明，在控制患者特征后，基线阿片类药物处方率是患者未来是否会成为长期阿片类药物使用者的有力预测因素。
ObjectiveTo identify the extent to which opioid prescribing rates for patients with rheumatoid arthritis (RA) vary in the US and to determine the implications of baseline opioid prescribing rates on the probability of future long‐term opioid use.MethodsWe identified patients with RA from physicians who contributed ≥10 patients within the first 12 months of participation in the Corrona RA Registry. The baseline opioid prescribing rate was calculated by dividing the number of patients with RA reporting opioid use during the first 12 months by the number of patients with RA providing data that year. To estimate odds ratios (ORs) for long‐term opioid use, we used generalized linear mixed models.ResultsDuring the follow‐up period, long‐term opioid use was reported by 7.0% (163 of 2,322) of patients of physicians with a very low rate of opioid prescribing (referent) compared to 6.8% (153 of 2,254) of patients of physicians with a low prescribing rate, 12.5% (294 of 2,352) of patients of physicians with a moderate prescribing rate, and 12.7% (307 of 2,409) of patients of physicians with a high prescribing rate. The OR for long‐term opioid use after the baseline period was 1.16 (95% confidence interval [95% CI] 0.79–1.70) for patients of low‐intensity prescribing physicians, 1.89 (95% CI 1.27–2.82) for patients of moderate‐intensity prescribing physicians, and 2.01 (95% CI 1.43–2.83) for patients of high‐intensity prescribing physicians, compared to very low‐intensity prescribing physicians.ConclusionRates of opioid prescriptions vary widely. Our findings indicate that baseline opioid prescribing rates are a strong predictor of whether a patient will become a long‐term opioid user in the future, after controlling for patient characteristics.