Chang Samantha H, Hirsch Shawn C, Thomas Sonia M, Edlund Mark J, Dolor Rowena J, Ives Timothy J, Dewey Charlene M, Gulur Padma, Chelminski Paul R, Archer Kristin R, Wu Li-Tzy, Curtis Janis, Goldstein Adam O, McCormack Lauren A
Center for Clinical Research, RTI International, Research Triangle Park, NC 27709, United States.
Community Health & Implementation Research Program, RTI International, Research Triangle Park, NC 27709, United States.
JAMIA Open. 2025 Jun 16;8(3):ooaf053. doi: 10.1093/jamiaopen/ooaf053. eCollection 2025 Jun.
To describe challenges and solutions for calculating longitudinal daily opioid dose in morphine milligram equivalents from electronic health record prescriptions for a clinical trial of voluntary opioid reduction in patients with chronic non-cancer pain.
Researchers obtained opioid prescriptions for 525 participants from the National Patient-Centered Clinical Research Network datamart at three health systems. Daily opioid dose was calculated using dose conversions and summing across prescriptions after applying assumptions, reviewing suspect prescribing patterns, and removing spurious prescriptions.
Out of 16 071 extracted prescriptions, 1207 (8%) were unusable, and 14 864 (92%) were analyzed.
Numerous challenges were identified related to incomplete data, inaccurate refill dates, and overlapping or duplicate prescriptions.
Using electronic prescription data to calculate daily doses of opioid consumption is challenging and requires significant cleaning prior to use in research. This paper recommends steps to review and clean electronic opioid prescription data.
描述在一项针对慢性非癌性疼痛患者自愿减少阿片类药物使用的临床试验中,根据电子健康记录处方以毫克吗啡当量计算纵向每日阿片类药物剂量时所面临的挑战及解决方案。
研究人员从三个医疗系统的国家以患者为中心的临床研究网络数据集市中获取了525名参与者的阿片类药物处方。在应用假设、审查可疑处方模式并去除虚假处方后,通过剂量转换并汇总各处方来计算每日阿片类药物剂量。
在提取的16071份处方中,1207份(8%)不可用,14864份(92%)进行了分析。
发现了许多与数据不完整、续方日期不准确以及处方重叠或重复相关的挑战。
利用电子处方数据计算每日阿片类药物消耗量具有挑战性,在用于研究之前需要进行大量清理工作。本文推荐了审查和清理电子阿片类药物处方数据的步骤。