Feasibility of semiautomated surveillance of healthcare-associated Staphylococcus aureus bloodstream infections using hospital electronic health records in Victoria, Australia

在澳大利亚维多利亚州,利用医院电子健康记录对医疗相关金黄色葡萄球菌血流感染进行半自动化监测的可行性研究

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Abstract

OBJECTIVE: Many hospitals struggle to transform electronic health record (EHR) data to support performance, continuous improvement and patient safety. Our study aimed to explore the feasibility of semiautomated surveillance for healthcare-associated infections (HAIs) in Australian hospitals, focussing on Staphylococcus aureus bloodstream infection (SABSI) surveillance. METHOD: National surveillance case definitions were reviewed with an inventory list of data elements created to identify high-probability healthcare-associated SABSI events. An interview schedule was developed to assess the availability, characteristics and quality of EHR data for data elements. Interviews were conducted with hospital infection prevention and control (IPC) staff. RESULTS: 12 IPC staff representing 12 hospitals and 11 healthcare organisations were interviewed. EHRs were in place at nine (75%) sites, supplied by six different vendors. Heterogeneity was observed in EHR functionalities, data capture methods for routine care and local approaches to use electronic systems to reduce HAI surveillance workload. None reported using automated surveillance systems. Most core data elements for the SABSI algorithm were present in EHRs, suggesting only minor modification to the SABSI definitions may be needed for automation, but issues with data quality were also described. DISCUSSION: We propose that modification of the national SABSI definitions is needed for automation. While many Victorian hospitals have adopted EHRs, data quality and interoperability issues limit the leveraging of EHR data for secondary purposes. CONCLUSIONS: We have taken the initial steps of evaluating the feasibility of semiautomated HAI surveillance in Victorian hospitals. With further development, this offers the promise of enhanced efficiency and reduced human resources required for HAI surveillance.

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