AWS for Industries

re:Invent 2020 – Healthcare Industry Recap

2020 has taught us all a thing or two about adapting to change. Working, meeting with friends, and even doctors’ visits have all gone virtual. AWS re:Invent 2020 was no exception. Our premier event for the year, typically held over the course of one week in Las Vegas, was transformed into a multi-week virtual experience, filled with content, announcements, and meetings. The Healthcare Industry Track at re:Invent 2020 brought together thought leaders from throughout the care continuum to discuss how they are leveraging the power of AWS technology to lower cost, increase the pace of innovation, and ultimately improve patient care.

With over 100 launches and announcements of new services and major features during re:Invent, it can be hard to keep track of the most relevant information. In this post, we highlight information specifically for Healthcare applications, as well as provide links to the top Healthcare-focused breakout sessions of re:Invent 2020.

Top announcements for healthcare applications

  • Combine, share, and gain valuable insights from your data assets with Amazon HealthLake and AWS Glue Elastic Views. Amazon HealthLake is a new, secure HIPAA-eligible data lake designed for healthcare providers, payors, and healthcare technology companies that uses machine learning (ML) models trained to automatically understand and extract meaningful medical data from raw, disparate data. Amazon HealthLake can foster industry-wide collaboration by enabling data sharing because it formats data using the Health Level 7 (HL7) Fast Healthcare Interoperable Resources (FHIR) standard. Webpage | Video

AWS Glue Elastic Views lets you use SQL-based queries to combine disparate data sources into a single table to support a research mission. AWS Glue Elastic Views lets analysts with SQL skills combine and replicate data without having to engage a data engineer in the IT division. Webpage | Video

  • Machine learning just got easier. Simplify and accelerate data profiling, preparation, and feature engineering for ML using Amazon SageMaker Data Wrangler. It offers over 300 built-in data transformations with no need to write code, making data preparation for ML easier for a wider range of analyst roles. Once features are defined, they can be stored for reuse within the Amazon SageMaker Feature Store, both for new model discovery and for inference. As the use of ML models grows, you can deploy, monitor, and modify ML models in production using Amazon SageMaker Pipelines. These new SageMaker capabilities lower the barriers to ML adoption for any R&D team. Webpage | Blog
  • Foster collaboration and manage research environments with Service Workbench on AWS and AWS CloudFormation Modules. Service Workbench on AWS is a solution that allows researchers to self-provision research environments that can be pre-configured to be compliant with HIPAA/HITRUST, GxP, and GDPR regulations. All analytic tools and data connections can be configured to accelerate research missions without the worry of navigating cloud infrastructure. Teams of collaborating researchers, even from different institutions, can access data assets within the cloud, avoiding the need to download and share data. Webpage | Blog | Video

AWS CloudFormation Modules are pre-configured and reusable building blocks that can be used to provision researcher environments and other R&D platform components that are consistently secure by default. Webpage | Blog | User Guide

  • Implement ECP Epic instances on AWS using Amazon EC2. Amazon EC2 R5b instances are the next generation of memory optimized instances for the Amazon Elastic Compute Cloud. R5 instances are well suited for memory intensive applications such as high-performance databases, distributed web scale in-memory caches, mid-size in-memory databases, real time big data analytics, and other enterprise applications. Additionally, users can choose from a selection of instances that have options for local NVMe storage, EBS optimized storage (up to 60 Gbps), and networking (up to 100 Gbps). Webpage | Blog
  • Easily add location data to applications without sacrificing data security and user privacy. Location data is a vital ingredient in today’s applications, enabling capabilities ranging from asset tracking to location-based marketing. However, when integrating location data into applications, developers face significant barriers of cost, privacy and security compromises, and tedious and slow integration work. With Amazon Location Service, you can easily add capabilities such as maps, points of interest, geocoding, routing, geofences, and tracking to applications. You retain control of your location data with Amazon Location, so you can combine proprietary data with data from the service. Customers can use Amazon Location Service to develop applications to alert organizations when admitted patients wander off from designated areas so personnel can quickly locate them to return them to their necessary units. Additionally, upcoming routing features allow the implementation of way-finding applications helping patients navigate to their provider locations. Webpage | Blog
  • Build intelligent contact centers with new Amazon Connect services. The COVID-19 pandemic has drastically impacted every business, and call centers have become more important than ever before as consumers seek more help in these unfamiliar circumstances. With rising call volumes and employees transitioning to work from home, traditional call centers on aging legacy platforms can be updated with Amazon Connect, an easy-to-use omnichannel cloud contact center that helps you provide superior customer service at a lower cost. Webpage

    • Real-time contact center analytics with Contact Lens for Amazon Connect. Automatically identify issues during in‐progress calls based on sentiment or keywords, such as adverse events or side effect. When a call needs to be transferred, the call center agent can pass the real-time transcript along with conversation details to the medical subject matter expert, so customers don’t have to repeat themselves or wait on hold while the subject matter experts gets up to speed with the case. Amazon Contact Lens can be used to analyze post-call metrics, sentiment, and trends to understand customers better and provide superior, proactive service. Webpage | Blog
    • Enhance personalized service with Amazon Connect Customer Profiles. This feature equips agents with a more unified view of a customer’s profile for more personalized service during a call. It aggregates customer information like contact history, address, phone number, and recent engagements from multiple repositories, such as medical information requests or product sample orders. Webpage | Blog
    • Improve productivity with Amazon Connect Tasks. With traditional contact center solutions, agents track their tasks and customer follow-up items manually. This is time consuming and prone to errors, especially when tasks span multiple systems, as they often do in comprehensive patient support programs. Amazon Connect Tasks makes it easy to prioritize, assign, and track all contact center agent tasks to completion, improving agent productivity and ensuring customer issues are quickly resolved. Follow-ups can also be automated through connectors to external applications such as Salesforce, Amazon Lex chatbots, and Amazon Pinpoint. Webpage
    • Drastically reduce the time agents spend searching for answers with Amazon Connect Wisdom. Knowledge articles, Wikis, and FAQs are spread across separate repositories and siloes. Agents lose time trying to navigate all those databases, while the customer waits for the answer. With Amazon Connect Wisdom, agents use ML to search across connected repositories based on phrases and questions exactly as the customer would ask them to find answers quickly. Wisdom connects to relevant knowledge repositories with built-in connectors for third-party applications like Salesforce and ServiceNow, or other internal knowledge stores to aggregate information such as frequently asked questions (FAQs), wikis, documents, and help guides. Webpage
    • Quickly authenticate callers with Amazon Connect Voice ID. This feature authenticates callers with real-time ML-powered voice analysis. When a customer opts-in to streamline their authentication, Amazon Connect Voice ID creates a digital voiceprint by analyzing the caller’s speech attributes like rhythm, pitch, and tone, as well as the device and network metadata. When the customer calls back, Amazon Connect Voice ID matches the caller voiceprint against the claimed identity and sends an ‘authentication’ or ‘not authenticated’ notification. Webpage
  • Reduce friction when integrating with a hybrid cloud environment with Amazon EKS, ECS Anywhere, and AWS Lambda container image support. Amazon EKS and Amazon ECS Anywhere brings a consistent AWS management experience to customers’ data centers. Amazon EKS and Amazon ECS Anywhere saves you the complexity of buying or building your own management tooling to create clusters, configure the operating environment, update software, and handle backup and recovery. Amazon EKS and Amazon ECS Anywhere enables automated cluster management and reduced support costs, and eliminates the redundant effort of using multiple open source or third party tools for operating Kubernetes clusters. Additionally, AWS Lambda now supports packaging and deploying functions as container images, so you can easily build Lambda-based applications by using familiar container image tooling, workflows, and dependencies. Webpage | Blog
  • Optimize cost by upgrading to the latest instance and storage types. The new general purpose (M6g), general purpose burstable (T4g), compute optimized (C6g), and memory optimized (R6g) Amazon EC2 instances deliver up to 40% improved price performance over comparable x86-based instances for a broad spectrum of workloads. The new storage-focused D3 and D3en instances offer 100% higher disk throughput, 7x more storage capacity (up to 336 TB), and 80% lower cost per-TB of storage compared to D2 instances. Lastly, gp3, the next-generation general purpose SSD volumes for Amazon Elastic Block Store (Amazon EBS) lets you provision performance independent of storage capacity, and offers up to 20% lower price-point per GB than existing gp2 volumes. With gp3 volumes, you can scale IOPS (input/output operations per second) and throughput without needing to provision additional block storage capacity, and pay only for the resources needed. Webpage

Healthcare announcements and press coverage

On-demand healthcare sessions

A big thank you to all of you who joined us for AWS re:Invent 2020. Together, we can accelerate the digital transformations of the global healthcare industry enabling the delivery of patient-centric healthcare, improving cost, quality, outcomes, and access to care. We look forward to seeing you back next year at AWS re:Invent 2021!

If you are looking to learn more about AWS for Healthcare & Life Sciences, join us on the web at

David Niewolny

David Niewolny

David Niewolny is the Head of Marketing for Healthcare at Amazon Web Services (AWS). Prior to joining AWS, David helped build and lead, healthcare focused businesses within Freescale Semiconductor, NXP, and Real Time Innovations. He is considered an industry authority on the use of new technology in healthcare applications. David holds an MBA from the University of Texas at Austin and a B.S. in Biomedical/Biochemical Engineering from the Iowa State University.