Category: Healthcare

For years, public health agencies have relied on paper-based case report forms to supplement the electronic laboratory reports (ELRs) they receive for reportable diseases. While ELRs provide positive test results, the accompanying case reports give public health agencies critical clinical, demographic, and risk factor data needed for effective disease investigation and response. However, the sheer volume of COVID-19 cases quickly overwhelmed this manual, paper-based process. Prior to the pandemic, the Office of the National Coordinator for Health IT (ONC) and the Centers for Disease Control and Prevention (CDC) developed standards for an electronic case report (eCR) form that could be automatically sent to public health agencies from providers’ electronic health records (EHRs).

About 4.5 million electroencephalogram (EEG) tests are performed in the US each year. That’s more than if every person in Oregon, Connecticut, or Iowa got an EEG. Because they provide insights into brain activity and not just structure, EEGs are one of the most common tests ordered by doctors to help make a diagnosis for people with brain problems. The Brain Data Science Platform (BDSP), hosted on Amazon Web Services (AWS), is increasing EEG accessibility through cooperative data sharing and research enabled by the cloud. Read this post to learn more.

Generative artificial intelligence (AI) innovation and inspiration dominated today’s AWS Summit Washington, DC keynote. But there was no shortage of newsworthy moments and key takeaways that extended beyond generative AI. Dave Levy, vice president of Worldwide Public Sector at Amazon Web Services (AWS), delivered the keynote and was joined onstage by three guest speakers who helped him set the tone for the annual two-day event that brings the public sector cloud community together in the nation’s capital.

In this post, we explore the complexities of data privacy and controls on Amazon Web Services (AWS), examine how creating a landing zone within which to contain such data is important, and highlight the differences between creating a landing zone from scratch compared with using the AWS Landing Zone Accelerator (LZA) for Healthcare. To aid explanation, we use a simple healthcare workload as an example. We also explain how LZA for Healthcare codifies HIPAA controls and AWS Security Best Practices to accelerate the creation of an environment to run protective health information workloads in AWS.

The European Health Data Space (EHDS) will establish a common framework and infrastructure for the use of health data for research, innovation, policy-making, and regulatory activities in the European Union (EU). It will also create common standards and practices enabling EU citizens to better access, control, and share their electronic personal health data. Read this post to learn why Amazon Web Services (AWS) welcomes the EHDS as an important step towards unleashing the vast potential of health data to benefit citizens across Europe and beyond.

The Amazon Web Services (AWS) Well-Architected Framework is designed to help build resilient, secure, and efficient solutions. Understanding this framework can greatly benefit AWS customers looking to enhance and refine their cloud environments. This post shares insights into how NHS England, responsible for running the vital national IT systems which support health and social care, revolutionized their approach to the AWS Well-Architected Framework review process.

This post discusses how Amazon Web Services (AWS) can help you successfully set up an Amazon DataZone domain, aggregate data from multiple sources into a single centralized environment, and perform analytics on that data. Additionally, this post provides a sample architecture as well as a walkthrough on how to set up that architecture. Ultimately, this post serves as a valuable resource if you’re seeking to optimize your data management processes and derive actionable insights to drive business growth.

Healthcare organizations invest heavily in technology and data. Generative artificial intelligence (AI) empowers healthcare organizations to leverage their investments in robust data foundations, improve patient experience through innovative interactive technologies, boost productivity to help address workforce challenges, and drive new insights to accelerate research. This post highlights three examples of how generative AI on Amazon Web Services (AWS) is being used in healthcare and discusses ways to leverage this technology in a responsible, safe way.

Applications and user experiences are poised to be reinvented with generative artificial intelligence (AI), and the public sector is no exception. Governments, education institutions, nonprofits, and health systems must constantly adapt and innovate to meet the changing needs of their constituents, students, beneficiaries, and patients. If used responsibly, this powerful technology can open doors to endless possibilities to increase creativity, productivity, and progress.

The University of Pittsburgh, the University of Illinois Urbana-Champaign (UIUC), the University of California Davis Health Cloud Innovation Center (UCDH CIC)—powered by Amazon Web Services (AWS)—and the AWS Digital Innovation (DI) team have built a prototype that uses machine learning (ML) and generative artificial intelligence (AI) to transform the public health communications landscape by giving officials the tools they need to fight medical misinformation, disinformation, and malinformation.