Division of Epidemiology, School of Public Health, University of California, Berkeley, Berkeley, CA, USA.
Center on Substance Use and Health, San Francisco Department of Public Health, San Francisco, USA.
J Gen Intern Med. 2022 Jan;37(1):117-124. doi: 10.1007/s11606-021-06920-4. Epub 2021 Jun 25.
After decades of liberal opioid prescribing, multiple efforts have been made to reduce reliance upon opioids in clinical care. Little is known about the effects of opioid prescribing policies on outcomes beyond opioid prescribing.
To evaluate the combined effects of multiple opioid prescribing policies implemented in a safety-net primary care clinic in San Francisco, CA, in 2013-2014.
Retrospective cohort study and conditional difference-in-differences analysis of nonrandomized clinic-level policies.
273 patients prescribed opioids for chronic non-cancer pain in 2013 at either the treated (n=151) or control clinic (n=122) recruited and interviewed in 2017-2018.
Policies establishing standard protocols for dispensing opioid refills and conducting urine toxicology testing, and a new committee facilitating opioid treatment decisions for complex patient cases.
Opioid prescription (active prescription, mean dose in morphine milligram equivalents [MME]) from electronic medical charts, and heroin and opioid analgesics not prescribed to the patient (any use, use frequency) from a retrospective interview.
The interventions were associated with a reduction in mean prescribed opioid dose in the first three post-policy years (year 1 conditional difference-in-differences estimate: -52.0 MME [95% confidence interval: -109.9, -10.6]; year 2: -106.2 MME [-195.0, -34.6]; year 3: -98.6 MME [-198.7, -23.9]; year 4: -72.6 MME [-160.4, 3.6]). Estimates suggest a possible positive association between the interventions and non-prescribed opioid analgesic use (year 3: 5.2 absolute percentage points [-0.1, 11.2]) and use frequency (year 3: 0.21 ordinal frequency scale points [0.00, 0.47]) in the third post-policy year.
Clinic-level opioid prescribing policies were associated with reduced dose, although the control clinic achieved similar reductions by the fourth post-policy year, and the policies may have been associated with increased non-prescribed opioid analgesic use. Clinicians should balance the urgency to reduce opioid prescribing with potential harms from rapid change.
经过几十年的阿片类药物处方自由化,已经采取了多项措施来减少临床护理中对阿片类药物的依赖。然而,对于阿片类药物处方政策对阿片类药物处方以外的结果的影响,我们知之甚少。
评估 2013-2014 年在加利福尼亚州旧金山的一个医疗保障初级保健诊所实施的多种阿片类药物处方政策的综合效果。
对非随机诊所级政策的回顾性队列研究和条件差异分析。
2013 年在接受治疗的诊所(n=151)或对照诊所(n=122)接受慢性非癌症疼痛阿片类药物治疗的 273 名患者,于 2017-2018 年进行了招募和访谈。
为配药和进行尿液毒理学检测制定标准方案的政策,以及为复杂患者病例的阿片类药物治疗决策提供便利的新委员会。
从电子病历中获得的阿片类药物处方(有效处方,以吗啡毫克当量[MME]表示的平均剂量),以及从回顾性访谈中获得患者未处方的海洛因和阿片类镇痛药(任何使用,使用频率)。
干预措施与前三年(第一年条件差异估计:-52.0 MME [95%置信区间:-109.9,-10.6];第二年:-106.2 MME [-195.0,-34.6];第三年:-98.6 MME [-198.7,-23.9];第四年:-72.6 MME [-160.4,3.6])的平均处方阿片类药物剂量降低有关。研究结果表明,这些干预措施与非处方阿片类镇痛药的使用(第三年:5.2 个绝对百分点 [-0.1,11.2])和使用频率(第三年:0.21 个序数频率标度点 [0.00,0.47])可能存在正相关。
诊所级阿片类药物处方政策与剂量降低有关,尽管对照诊所到第四年后也实现了类似的降低,并且这些政策可能与非处方阿片类镇痛药的使用增加有关。临床医生应权衡减少阿片类药物处方的紧迫性与快速变化带来的潜在危害。