Measurement of Completeness and Timeliness of Linked Electronic Health Record Pharmacy Data for Early Detection of Nonadherence to Breast Cancer Adjuvant Endocrine Therapy.

IF 3.3 Q2 ONCOLOGY JCO Clinical Cancer Informatics Pub Date : 2024-12-01 Epub Date: 2024-12-12 DOI:10.1200/CCI.24.00115
Chelsea McPeek, Shirlene Paul, Jordan Lieberenz, Mia Levy
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Abstract

Purpose: This retrospective cohort study evaluated whether linked electronic health record (EHR) pharmacy data were adequately complete and timely to detect primary nonadherence to breast cancer adjuvant endocrine therapy (AET).

Materials and methods: Linked EHR pharmacy data were extracted from the EHR for patients with stage 0 to III breast cancer who had their first prescription order for AET between 2016 and 2021. Patients with the first dispense event within 90 days of the prescription were classified as having sufficient or insufficient data available for early detection of primary adherence.

Results: A total of 1,446 eligible patients had a first AET prescription order between 2016 and 2021; these orders were routed to 871 unique pharmacies, of which 856 (98.2%) were contracted with the linked EHR pharmacy database and 15 (1.8%) were not contracted. Among the 1,428 patients with a first prescription sent to a contract pharmacy, 164 (13%) had incomplete linked EHR pharmacy data refresh events to assess primary adherence. Among the 1,244 patients with at least 1 refresh event after their first prescription, 82% occurred within 90 days and were sufficiently timely for early detection of primary adherence. Overall, 32% of patients would benefit from an intervention to verify or improve primary adherence to AET.

Conclusion: Although linked EHR pharmacy data have adequate completeness of contract pharmacy data, local configurations of data refresh events tailored to medication reconciliation workflows are incomplete (13%) and insufficiently timely (32%) to fully support clinical decision support (CDS) for early detection of primary medication nonadherence. Prospective CDS interventions using linked EHR pharmacy data are possible with enhancements to the frequency and timeliness of refresh events.

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测量关联电子健康记录药房数据的完整性和及时性,以早期发现不坚持乳腺癌辅助内分泌治疗的情况。
目的:本回顾性队列研究评估了相关的电子健康记录(EHR)药房数据是否足够完整和及时,以检测乳腺癌辅助内分泌治疗(AET)的原发性不依从。材料和方法:从2016年至2021年间首次开AET处方的0至III期乳腺癌患者的EHR中提取相关EHR药房数据。在处方90天内出现首次配药事件的患者被分类为具有足够或不足的可用于早期发现原发性依从性的数据。结果:2016年至2021年间,共有1446名符合条件的患者首次获得AET处方单;这些订单被发送到871家独特的药店,其中856家(98.2%)与EHR药房数据库签订了合同,15家(1.8%)没有签订合同。在1428名首次处方送到合同药房的患者中,164名(13%)的EHR药房数据刷新事件不完整,无法评估最初的依从性。在1244例患者中,首次处方后至少有一次刷新事件,82%发生在90天内,足以及时早期发现原发性依从性。总体而言,32%的患者将从验证或改善AET的初始依从性的干预中受益。结论:尽管关联的EHR药房数据具有合同药房数据的足够完整性,但针对药物调节工作流程量身定制的数据刷新事件的本地配置不完整(13%)且不够及时(32%),无法完全支持临床决策支持(CDS),以早期发现主要药物依从性。通过提高刷新事件的频率和及时性,使用关联EHR药房数据的前瞻性CDS干预成为可能。
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CiteScore
6.20
自引率
4.80%
发文量
190
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