Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
HealthIT, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Appl Clin Inform. 2019 Jan;10(1):77-86. doi: 10.1055/s-0038-1675813. Epub 2019 Jan 30.
Managing prescription renewal requests is a labor-intensive challenge in ambulatory care. In 2009, Vanderbilt University Medical Center developed clinic-specific standing prescription renewal orders that allowed nurses, under specific conditions, to authorize renewal requests. Formulary and authorization changes made maintaining these documents very challenging.
This article aims to review, standardize, and restructure legacy standing prescription renewal orders into a modular, scalable, and easier to manage format for conversion and use in a new electronic health record (EHR).
We created an enterprise-wide renewal domain model using modular subgroups within the main institutional standing renewal order policy by extracting metadata, medication group names, medication ingredient names, and renewal criteria from approved legacy standing renewal orders. Instance-based matching compared medication groups in a pairwise manner to calculate a similarity score between medication groups. We grouped and standardized medication groups with high similarity by mapping them to medication classes from a medication terminology vendor and filtering them by intended route (e.g., oral, subcutaneous, inhalation). After standardizing the renewal criteria to a short list of reusable criteria, the Pharmacy and Therapeutics (P&T) committee reviewed and approved candidate medication groups and corresponding renewal criteria.
Seventy-eight legacy standing prescription renewal orders covered 135 clinics (some applied to multiple clinics). Several standing orders were perfectly congruent, listing identical medications for renewal. We consolidated 870 distinct medication classes to 164 subgroups and assigned renewal criteria. We consolidated 379 distinct legacy renewal criteria to 21 criteria. After approval by the P&T committee, we built subgroups in a structured and consistent format in the new EHR, where they facilitated chart review and standing order adherence by nurses. Additionally, clinicians could search an autogenerated document of the standing order content from the EHR data warehouse.
We describe a methodology for standardizing and scaling standing prescription renewal orders at an enterprise level while transitioning to a new EHR.
在门诊护理中,管理处方续方请求是一项劳动密集型的挑战。2009 年,范德比尔特大学医学中心开发了特定诊所的常备处方续方医嘱,允许护士在特定条件下授权续方请求。药物清单和授权变更使得维护这些文件极具挑战性。
本文旨在审查、标准化和重构遗留常备处方续方医嘱,将其转换为模块化、可扩展且更易于管理的格式,以便在新的电子健康记录(EHR)中使用。
我们通过从已批准的遗留常备续方医嘱中提取元数据、药物组名称、药物成分名称和续方标准,使用模块化子组在主要机构常备续方医嘱政策内创建了一个全企业范围的续方域模型。基于实例的匹配以两两方式比较药物组,以计算药物组之间的相似度得分。我们通过将它们映射到药物术语供应商的药物类别并按预期途径(例如口服、皮下、吸入)对药物组进行过滤,将具有高相似度的药物组分组并标准化。在将续方标准简化为一组可重复使用的标准后,药房和治疗学(P&T)委员会审查并批准了候选药物组和相应的续方标准。
78 份遗留常备处方续方医嘱涵盖了 135 个诊所(有些适用于多个诊所)。一些常备医嘱完全一致,列出了用于续方的相同药物。我们将 379 个不同的常备续方标准合并为 21 个标准。在 P&T 委员会批准后,我们在新的 EHR 中以结构化和一致的格式构建了子组,这便于护士进行图表审查和遵守常备医嘱。此外,临床医生可以从 EHR 数据仓库中搜索常备医嘱内容的自动生成文档。
我们描述了一种在向新的 EHR 过渡的同时,在企业层面标准化和扩展常备处方续方医嘱的方法。