PillHarmonics: An Orchestrated Medication Clinical Decision Support Service

PillHarmonics：精心策划的药物临床决策支持服务

• 批准号: 10382886
• 负责人: James Shalaby
• 金额: $ 27.46万
• 依托单位: ELIMU INFORMATICS, INC.
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-20 至 2023-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10382886
• 关键词: Address; Adverse drug event; Adverse event; Affect; Algorithms; Automobile Driving; Clinical; Clinical Data; Clinical Research; Complete Blood Count; Conflict (Psychology); Data; Data Element; Disease; Dose; Drug Hypersensitivity; Electronic Health Record; Environment; Evaluation; Exposure to; FDA approved; Failure; Fast Healthcare Interoperability Resources; Fatigue; Genes; Genomics; Growth; Guidelines; Individual; Knowledge; Lead; Length of Stay; Logic; Mainstreaming; Medical Genetics; Medication Management; Modeling; Motivation; National Human Genome Research Institute; Office Visits; Output; Patient Care; Patients; Pharmaceutical Preparations; Pharmacogenomics; Phase; Policies; Primary Health Care; Privatization; Questionnaires; Recommendation; Regimen; Renal function; Reporting; Risk; Services; Source; Specific qualifier value; Specificity; Strategic vision; Structure; Surface; Tacrolimus; Technology; Testing; Time; Translating; United States; Vendor; actionable mutation; base; clinical decision support; clinically relevant; clinically significant; clopidogrel; cloud based; data repository; drug efficacy; drug structure; electronic structure; experimental study; gene interaction; genetic testing; genomic data; holistic approach; improved; instrument; medication safety; novel; patient safety; prototype; response; success; testing services; usability

Project Summary Medication related adverse events account for over 2 million hospital stays and 3.5 million physician office visits per year. Medication decision support, when implemented correctly, can have a significant impact on these numbers, enhancing patient safety and improving drug efficacy. But while drug decision support is now commonplace in Electronic Health Records (EHRs), many issues remain, and clinicians are generally unsatisfied with the lack of patient specificity and inappropriate context of medication alerts. Add to this the fact that drug-gene alerts are becoming increasingly important. Studies show that over half of all primary care patients are exposed to pharmacogenomics (PGx) relevant drugs; that 7% of FDA- approved medications and 18% of the 4 billion prescriptions written in the United States per year are affected by PGx interactions; and that nearly 98% of individuals have at least one actionable variant by current guidelines. PGx findings are most commonly integrated into the EHR as non-actionable PDF reports. Structured EHR-specific solutions are emerging, and several groups are experimenting with HL7 FHIR and CDS Hooks standards. A common theme across these efforts is that PGx is implemented apart from other types of medication decision support, leading to disjointedness of alerts. For many years, groups have suggested the need to integrate PGx with other types of identified medication interactions. Evidence suggests that such a holistic approach can address patient safety issues (e.g., by juxtaposing conflicting drug recommendations) and alert fatigue (e.g., through greater alert precision). However, merging PGx into an environment that already has many usability challenges risks obscuring the benefits of such alerts. In response, this project aims to develop a medication decision support service, ‘PillHarmonics’, that seamlessly integrates drug-gene interaction checking with other types of medication alerting (such as drug-drug, drug-allergy, and drug-condition), thereby enhancing patient safety through minimization of adverse drug events and decreasing alert fatigue via more precise surfacing of relevant alerts. In the planned prototype, PillHarmonics will gather FHIR-formatted clinical data from an EHR, simulated by a HAPI FHIR server; FHIR-formatted genomic data, in this case from Elimu’s genomic data server; and drug knowledge, in this case from First DataBank and PharmGKB. The service translates identified interactions into normalized data elements which are exposed as structured FHIR DetectedIssues, one DetectedIssue per interaction. The PillHarmonics service will be demonstrated via a CDS Hooks application that generates integrated alerts in response to the addition of tacrolimus or clopidogrel to a patient's existing medication regimen. AIM 2 evaluation will entail a ‘perceived usefulness’ assessment of the PillHarmonics algorithm using an established evaluation instrument.

项目摘要 与药物相关的不良事件占了超过200万医院的住院和350万个物理学 每年办公室访问。药物决策支持正确实施后可能会产生重大影响 在这些数字上，提高患者的安全性并提高药物效率。但是尽管药物决策支持是 现在在电子健康记录（EHR）中司空见惯，仍然存在许多问题，临床医生通常是 对缺乏患者特异性和药物警报的不适当上下文感到不满意。 再加上这一事实，即毒品警报变得越来越重要。研究表明， 在所有初级保健患者中，一半暴露于药物（PGX）相关药物中；那7％的FDA- 批准的药物和每年在美国编写的40亿处方中的18％受到影响 通过PGX相互作用；而且，几乎98％的个体至少具有一个可操作的变体 指南。 PGX发现最常见于EHR中，作为不可操作的PDF报告。结构 EHR特异性解决方案正在出现，几个组正在使用HL7 FHIR和CDS钩进行实验 标准。这些努力的一个共同主题是，除其他类型的 药物决策支持，导致警报的脱节。多年以来，小组建议 需要将PGX与其他类型的已识别药物相互作用集成。有证据表明这样的 整体方法可以解决患者的安全问题（例如，通过将冲突的药物建议并列） 并提醒疲劳（例如，通过更高的警报精度）。 但是，将PGX合并到已经存在许多可用性挑战的环境中，风险掩盖了 此类警报的好处。作为回应，该项目旨在开发药物决策支持服务， “ Pillharmonics”，无缝将药物互动与其他类型的药物进行检查 警报（例如药物，药物过敏和药物条件），从而通过 通过更精确的相关警报表面表面，最大程度地减少不良药物事件并减少警报疲劳。 在计划的原型中，Pillharmonics将从EHR中收集FHIR形式的临床数据，模拟 由hapi fhir服务器； FHIR形成的基因组数据，在这种情况下，来自Elemu的基因组数据服务器；和药物 知识，在这种情况下，First Databank和PharmGKB。该服务将确定的交互转换为 归一化的数据元素，这些元素被暴露为结构化的FHIR检测器，一个检测到每一个 相互作用。 Pillharmonics服务将通过生成的CDS钩应用程序进行演示 综合警报以回应将他克莫司或氯吡格雷添加到患者现有药物中 方案。 AIM 2评估将需要对Pillharmonics算法进行“感知的有用性”评估 已建立的评估工具。