Department of Public Health Sciences, University of California, Davis, Davis, California, USA.
Violence Prevention Research Program, Department of Emergency Medicine, University of California, Davis, Sacramento, California, USA.
Pharmacoepidemiol Drug Saf. 2024 Jan;33(1):e5699. doi: 10.1002/pds.5699. Epub 2023 Oct 1.
To help prevent overdose deaths involving prescription drugs, accurate linkage of prescription drug monitoring program (PDMP) records for individual patients is essential.
To compare the accuracy of the linkage program used by California's PDMP against various record linkage programs with respect to accuracy in deduplicating patient identities in the PDMP, with implications for identifying high-risk opioid use and outlier behaviors.
We evaluated California's program, Link Plus, LinkSolv, and The Link King on 557 861 PDMP identity records with addresses in two 3-digit zip code areas for patients who filled a controlled substance prescription in 2013. Manual review was performed on a stratified sample of 720 paired records identified as matches by at least one program.
We estimated sensitivity and positive predictive value, and computed PDMP patient alerts for the patient entities identified by each program.
Sensitivity was 95% for LinkSolv and The Link King, 84% for Link Plus, and 73% for California's program; positive predictive value was ≥93% for all programs. The number of patient entities prompting a PDMP alert was similar among the programs for all alerts except multiple provider episodes (obtaining prescriptions from ≥6 prescribers or ≥6 pharmacies in the last 6 months), which were 10.9%, 26.6%, and 16.9% greater using The Link King, Link Plus, and LinkSolv, respectively, compared to California's program.
PDMPs should assess the accuracy of record linkage algorithms and the impacts of these algorithms on patient safety alerts and develop national best practices for PDMP record linkage.
为了帮助预防涉及处方药物的用药过量死亡，准确链接个人患者的处方药物监测计划（PDMP）记录至关重要。
针对加利福尼亚州 PDMP 所使用的链接程序，我们比较了其与各种记录链接程序在 PDMP 中重复识别患者身份方面的准确性，这对于识别高风险阿片类药物使用和异常行为具有重要意义。
我们评估了加利福尼亚州的 Link Plus、LinkSolv 和 The Link King 这三个程序，这些程序的评估对象为在 2013 年填写受控物质处方的、在两个三位数邮政编码区域有地址的 557861 名 PDMP 身份记录患者。对至少一个程序识别为匹配的 720 对记录的分层样本进行了手动审查。
我们估计了每个程序的敏感性和阳性预测值，并计算了 PDMP 患者实体的识别情况。
LinkSolv 和 The Link King 的敏感性为 95%，Link Plus 为 84%，而加利福尼亚州的程序为 73%；所有程序的阳性预测值均≥93%。对于所有警报，除了多重提供者情节（在过去 6 个月内从≥6 名开方者或≥6 家药店获得处方）之外，各个程序引发 PDMP 警报的患者实体数量相似，而使用 The Link King、Link Plus 和 LinkSolv 分别比加利福尼亚州的程序多 10.9%、26.6%和 16.9%。
PDMP 应评估记录链接算法的准确性以及这些算法对患者安全警报的影响，并为 PDMP 记录链接制定国家最佳实践。
