背景:药物遗传学可以通过个性化选择药物来影响患者的护理和结果,从而提高疗效和减少有害的副作用。尽管有令人信服的临床证据和国际指南强调药物遗传学在临床实践中的益处,在英国国家卫生局内的实施是有限的。需要克服的一个重要障碍是开发支持将药物遗传学数据集成到医疗保健系统中的IT解决方案。这需要更好地了解电子健康记录(EHR)的作用以及临床医生可以接受的临床决策支持系统的设计。特别是那些在初级保健。
目的:从初级保健临床医生的角度探讨药物遗传学服务的需求和要求,以期共同设计原型解决方案。
方法:我们使用了人种学和大声思考的观察,用户研究研讨会,和原型。这项研究的参与者包括全科医生和药剂师。总的来说,我们进行了5次人种学观察,以了解当前的实践和工作流程。随后是3个用户研究研讨会,每个人都有自己的主题指南,从人物角色和早期想法开始,通过探索临床决策支持系统和原型设计的潜力。随后,我们使用亲和力图表分析了车间数据,并作为多学科项目团队协作完善了解决方案的关键要求。
结果:用户研究结果表明,必须将药物遗传学数据纳入现有的EHR中,而不是通过独立的门户。通过临床决策支持系统提供的信息必须清晰,可访问,并且用户友好,因为该服务将被一系列最终用户使用。严重的,信息应显示在处方工作流程中,而不是静态存储在EHR中的离散结果。最后,处方建议应具有权威性,以使人们对结果的有效性充满信心。基于这些发现,我们共同设计了一个交互式原型,证明药物遗传学临床决策支持整合在EHR的处方工作流程中。
结论:这项研究标志着在初级保健机构中设计支持药物遗传学指导处方的系统方面迈出了重要的一步。临床决策支持系统有可能增强药物的个性化,只要它们在EHR中有效实施,并以用户友好的方式呈现药物遗传学数据,可操作,标准化格式。实现这一点需要开发一个解耦的,基于标准的体系结构,允许将数据与应用程序分离,通过使用应用程序编程接口(API)促进跨各种EHR的集成。更全球,这项研究证明了健康信息学和以用户为中心的设计在大规模实现个性化医疗的潜力并确保基因组创新的益处有效地惠及患者和人群方面的作用.
BACKGROUND: Pharmacogenetics can impact patient care and outcomes through personalizing the selection of medicines, resulting in improved efficacy and a reduction in harmful side effects. Despite the existence of compelling clinical evidence and international guidelines highlighting the benefits of
pharmacogenetics in clinical practice, implementation within the National Health Service in the United Kingdom is limited. An important barrier to overcome is the development of IT solutions that support the integration of pharmacogenetic data into health care systems. This necessitates a better understanding of the role of electronic health records (EHRs) and the design of clinical decision support systems that are acceptable to clinicians, particularly those in primary care.
OBJECTIVE: Explore the needs and requirements of a pharmacogenetic service from the perspective of primary care clinicians with a view to co-design a prototype solution.
METHODS: We used ethnographic and think-aloud observations, user research workshops, and prototyping. The participants for this
study included general practitioners and pharmacists. In total, we undertook 5 sessions of ethnographic observation to understand current practices and workflows. This was followed by 3 user research workshops, each with its own topic guide starting with personas and early ideation, through to exploring the potential of clinical decision support systems and prototype design. We subsequently analyzed workshop data using affinity diagramming and refined the key requirements for the solution collaboratively as a multidisciplinary project team.
RESULTS: User research results identified that pharmacogenetic data must be incorporated within existing EHRs rather than through a stand-alone portal. The information presented through clinical decision support systems must be clear, accessible, and user-friendly as the service will be used by a range of end users. Critically, the information should be displayed within the prescribing workflow, rather than discrete results stored statically in the EHR. Finally, the prescribing recommendations should be authoritative to provide confidence in the validity of the results. Based on these findings we co-designed an interactive prototype, demonstrating pharmacogenetic clinical decision support integrated within the prescribing workflow of an EHR.
CONCLUSIONS: This
study marks a significant step forward in the design of systems that support pharmacogenetic-guided prescribing in primary care settings. Clinical decision support systems have the potential to enhance the personalization of medicines, provided they are effectively implemented within EHRs and present pharmacogenetic data in a user-friendly, actionable, and standardized format. Achieving this requires the development of a decoupled, standards-based architecture that allows for the separation of data from application, facilitating integration across various EHRs through the use of application programming interfaces (APIs). More globally, this
study demonstrates the role of health informatics and user-centered design in realizing the potential of personalized medicine at scale and ensuring that the benefits of genomic innovation reach patients and populations effectively.