Lau Erica Y, Bird Linda, Lau Anthony, Chau Yau-Lam Alex, Butcher Katherine, Buchkowsky Susan, Gossack-Keenan Kira, Sadowski Cheryl, Hohl Corinne M
Strategy, Planning and Implementation, BC Cancer, 601 West Broadway, Vancouver, BC, V5Z 4C2, Canada, 1 6048776000.
Department of Health Information Science, University of Victoria, Victoria, BC, Canada.
JMIR Med Inform. 2025 Jul 8;13:e70167. doi: 10.2196/70167.
Adverse drug events (ADEs) lead to more than 2 million emergency department visits in Canada annually, resulting in significant patient harm and more than CAD $1 billion in health care costs (in 2018, the average exchange rate for 1 CAD was 0.7711 USD; 1 billion CAD would have been approximately 771.1 million USD). Effective documentation and sharing of ADE information through electronic medical records (EMRs) are essential to inform subsequent care and improve safety when culprit medications can be replaced and reexposures avoided. Yet, current systems often lack standardized comprehensive ADE value sets.
This study aimed to develop a SNOMED CT value set for symptoms and diagnoses to standardize ADE documentation and improve ADE data integration into EMRs.
We used ADE data from ActionADE, a prospective reporting system implemented in 9 hospitals in British Columbia. We extract 5792 reports that yielded 827 unique ADE symptom and diagnosis terms based on Medical Dictionary for Regulatory Activities preferred terms. Two independent mappers used both automated and manual mapping approaches to match these terms to SNOMED CT concepts. Two clinical experts conducted validation, followed by a quality assurance review by a separate clinical team. Discrepancies were resolved through consensus discussions. Interrater reliability was assessed using Cohen κ.
The automated mapping process identified 63.1% (522/827) semantically equivalent matches from SNOMED CT's Clinical Finding hierarchy. Two mappers manually reviewed the automatically mapped terms and identified appropriate target concepts for the unmapped terms. After the manual mapping process, 95.3% (788/827) of the source terms were successfully mapped to SNOMED CT concepts, with 4.7% (39/827) remaining unmapped. Interrater reliability between the mappers was strong (κ=0.87, 95% CI 0.85-0.89). The validation phase identified and removed 1 irrelevant term, resulting in 98.4% (813/826) terms mapped, with 1.6% (13/826) unmapped, and a high interrater reliability (κ=0.88, 95% CI 0.80-0.95). During quality assurance, 6 terms were flagged for concerns regarding clinical relevance or safety risks and were resolved through discussions. The final value set comprised 813 SNOMED CT concepts, with 95.7% (778/813) of terms classified as semantically equivalent and 4.3% (35/813) as semantically similar. Thirteen additional terms remained unmapped and will be reviewed as new SNOMED CT codes are added.
This study developed a SNOMED CT-based value set to document symptoms and diagnoses for ADEs observed in adults in EMRs. Adopting this value set can improve the consistency, accuracy, and interoperability of ADE documentation in EMRs, helping to reduce repeat ADEs and enhance patient safety. Ongoing refinement and improved clinical usability are essential for its widespread adoption. Future research should assess the impact of integrating this value set into EMRs on ADE reporting, pharmacovigilance, and patient safety outcomes.
药物不良事件（ADEs）每年在加拿大导致超过200万次急诊就诊，造成重大患者伤害，并产生超过10亿加元的医疗保健费用（2018年，1加元的平均汇率为0.7711美元；10亿加元约为7.711亿美元）。通过电子病历（EMRs）有效记录和共享ADE信息对于指导后续治疗以及在能够更换致病药物并避免再次暴露时提高安全性至关重要。然而，当前系统通常缺乏标准化的综合ADE值集。
本研究旨在开发一个用于症状和诊断的SNOMED CT值集，以标准化ADE文档记录并改善ADE数据集成到电子病历中。
我们使用了来自ActionADE的ADE数据，这是一个在不列颠哥伦比亚省9家医院实施的前瞻性报告系统。我们提取了5792份报告，根据《药品监管活动医学词典》首选术语得出827个独特的ADE症状和诊断术语。两名独立的映射人员使用自动和手动映射方法将这些术语与SNOMED CT概念进行匹配。两名临床专家进行验证，随后由一个单独的临床团队进行质量保证审查。通过共识讨论解决差异。使用Cohen κ评估评分者间信度。
自动映射过程从SNOMED CT的临床发现层次结构中识别出63.1%（522/827）语义等效匹配项。两名映射人员手动审查了自动映射的术语，并为未映射的术语确定了合适的目标概念。经过手动映射过程后，95.3%（788/827）的源术语成功映射到SNOMED CT概念，4.7%（39/827）仍未映射。映射人员之间的评分者间信度很强（κ=0.87，95%CI 0.85 - 0.89）。验证阶段识别并删除了1个无关术语，导致98.4%（813/826）的术语被映射，1.6%（13/826）未映射，且评分者间信度很高（κ=0.88，95%CI 0.80 - 0.95）。在质量保证期间，6个术语因临床相关性或安全风险问题被标记，并通过讨论得到解决。最终值集包含813个SNOMED CT概念，95.7%（778/813）的术语被分类为语义等效，4.3%（35/813）为语义相似。另外13个术语仍未映射，将在添加新的SNOMED CT代码时进行审查。
本研究开发了一个基于SNOMED CT的用于在电子病历中记录成人中观察到的ADE症状和诊断的价值集。采用该价值集可以提高电子病历中ADE文档记录的一致性、准确性和互操作性，有助于减少重复的ADE并提高患者安全性。持续的完善和改善临床可用性对于其广泛采用至关重要。未来研究应评估将此价值集集成到电子病历中对ADE报告、药物警戒和患者安全结果的影响。
