Truong Ngan-Ha, Rashidzada Zohal, Maleki Jenna, Varghese Pramode, Elkins Sri, Chen Caroline, James Rod, Thursky Karin
Royal Melbourne Hospital Guidance Group, Royal Melbourne Hospital.
National Centre for Antimicrobial Stewardship, Department of Infectious Diseases, University of Melbourne.
Stud Health Technol Inform. 2025 Aug 7;329:278-282. doi: 10.3233/SHTI250845.
Antimicrobial resistance is a significant global health issue, and Antimicrobial Stewardship (AMS) services in hospitals are key to addressing this. Clinical Decision Support Systems (CDSS) are vital tools that support AMS programs. Guidance MS, a CDSS developed in 2005, has been implemented in over 60 Australian hospitals, yielding positive outcomes such as reduced gram-negative resistance, decreased antimicrobial consumption, and improved prescribing practices. This CDSS was redesigned to continue to support national AMS accreditation standards and meet evolving needs in digital healthcare. The CDSS included features for formulary restriction, clinical decision support, post-prescription review, auditing, and interactive reports for feedback. This paper outlines how the Learning Health System (LHS) framework was applied to redesign, develop, implement and evaluate the updated CDSS. The LHS framework operates through iterative cycles of practice-to-data, data-to-knowledge, and knowledge-to-practice. A Learning Health Community was established, which provided input to guide system design. Key considerations for the new CDSS included a user-centred approach, interoperability with electronic medical records (EMR), and adherence to national regulatory standards for Software As a Medical Device. Following an Agile development process, the redesigned system underwent extensive testing and iterative improvements. The program was then implemented in a beta site, a large, tertiary hospital. Extensive User Acceptance Testing was conducted, with feedback and improvements incorporated into the first version release. The program was then implemented in a network of thirteen hospitals. Formal and anecdotal feedback from the project team and clinicians showed high satisfaction regarding usability, performance, clinician workflow improvement, content quality, and efficiency. The LHS framework enabled user feedback to drive rapid enhancements to the program, ensuring it met identified needs. The implementation projects provided valuable insights into workflows, enhancing project delivery and informing strategies for future application improvements and scalability. Future development will include establishing two-way integration with EMRs and mobile devices. A socio-technical evaluation will assess the program's perceived usability and usefulness, supporting continuous improvement as part of LHS methodology. A formal evaluation will assess clinical impact on hospital and patient outcomes, providing evidence to guide ongoing optimisation.The LHS is a useful framework for designing, developing, implementing and evaluating digital healthcare solutions for AMS, which continues to inform improvements, enabling provision of an effective, scalable and sustainable, digital solution.
抗菌药物耐药性是一个重大的全球健康问题，医院的抗菌药物管理（AMS）服务是解决这一问题的关键。临床决策支持系统（CDSS）是支持AMS项目的重要工具。2005年开发的CDSS“指导MS”已在澳大利亚60多家医院实施，取得了诸如降低革兰氏阴性菌耐药性、减少抗菌药物消耗以及改善处方行为等积极成果。该CDSS进行了重新设计，以继续支持国家AMS认证标准并满足数字医疗不断变化的需求。该CDSS包括处方集限制、临床决策支持、处方后审查、审计以及用于反馈的交互式报告等功能。本文概述了学习健康系统（LHS）框架如何应用于重新设计、开发、实施和评估更新后的CDSS。LHS框架通过实践到数据、数据到知识以及知识到实践的迭代循环来运作。建立了一个学习健康社区，为指导系统设计提供了意见。新CDSS的关键考虑因素包括以用户为中心的方法、与电子病历（EMR）的互操作性以及遵守医疗器械软件的国家监管标准。遵循敏捷开发过程，重新设计的系统进行了广泛测试和迭代改进。该项目随后在一家大型三级医院的试点进行了实施。进行了广泛的用户接受度测试，并将反馈和改进纳入了第一个版本发布。该项目随后在由13家医院组成的网络中实施。项目团队和临床医生的正式和非正式反馈显示，在可用性、性能、临床医生工作流程改进、内容质量和效率方面满意度很高。LHS框架使用户反馈能够推动对该项目的快速改进，确保其满足已确定的需求。实施项目为工作流程提供了宝贵见解，加强了项目交付，并为未来应用改进和可扩展性的策略提供了信息。未来的发展将包括与EMR和移动设备建立双向集成。社会技术评估将评估该项目的感知可用性和实用性，作为LHS方法的一部分支持持续改进。正式评估将评估对医院和患者结果的临床影响，为指导持续优化提供证据。LHS是设计、开发、实施和评估AMS数字医疗解决方案的有用框架，它继续为改进提供信息，从而能够提供有效、可扩展和可持续的数字解决方案。
