结合框架提高军队卫生系统质量和网络安全

Dr. Maureen L Schafer, Dr. Joseph H Schafer
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引用次数: 0

摘要

可以考虑现有的概念框架和商用技术,以便在军事卫生系统中快速实施质量措施(QM) (Costantino et al. 2020)。购买的医疗保健和数字医疗保健服务为从多个信息系统收集数据铺平了道路,从而为利益相关者提供可操作的情报,以指导和衡量医疗保健结果。然而,智能设备、异构信息系统、云服务和医疗物联网(IOMT)的次要数据收集对于安全专家来说是一个复杂的问题,它也会影响客户、利益相关者、组织和提供患者护理的企业。我们结合了三个概念框架:(1)Donabedian的质量属性框架(DQA),(2)国家医学院(NAM)框架,以及(3)医疗保健和公共卫生(HPH)网络安全框架(HCF)。这些框架中的每一个都经过了充分的测试,被广泛接受,并被引用为医疗保健提供高质量护理(DQA和NAM)和网络安全(HCF)的黄金标准。另外,每个框架都提供长期使用的分析、指导和医疗保健服务质量可靠度量的应用。合并的框架可以增强数据完整性(关于法规遵从性的数据收集和标准化安全)。合并后的框架还有助于确定护理质量方面的差距,支持优先采用可预见地改善患者预后的具有成本效益的方法,并支持DHA的质量措施。最后,我们提供了在维护信息技术(IT)治理遵从性的同时以更精确的方式理解质量度量的组件的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combining Frameworks to Improve Military Health System Quality and Cybersecurity
Existing conceptual frameworks and commercially available technology could be considered to rapidly operationalize the use of Quality Measures (QM) within military health systems (Costantino et al. 2020). Purchased healthcare as well as digital healthcare services have paved the way for data collection from multiple information systems thus offering stakeholders actionable intelligence to both guide and measure healthcare outcomes. However, the collection of data secondary to Smart Devices, disparate information systems, cloud services, and the Internet of Medical Things (IOMT) is a complication for security experts that also affect clients, stakeholders, organizations, and businesses delivering patient care. We have combined three conceptual frameworks: (1) Donabedian’s Quality Attributes Framework (DQA), (2) The National Academy of Medicine (NAM) framework, and the (3) Healthcare and Public Health (HPH) Cybersecurity Framework (HCF). Each of these frameworks is well-tested, widely accepted, and referenced as the gold standard in delivering quality care (DQA and NAM) and cybersecurity (HCF) for healthcare. Separately, each framework provides long-used analysis, guidance, and application of quality reliable measures of healthcare services. The combined frameworksmay enhance data integrity (collection and standardized safety of data in regard to regulatory compliance). The combined frameworks also support identifying gaps in quality of care, support the prioritization of cost-effective methodologies that predictably improve patient outcomes, and support DHA’s quality measures. Finally, we offer the importance of understanding the components of quality measures in a more precise manner while maintaining information technology (IT) governance compliance.
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