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AWS in Healthcare 2022
A Deeper Look at Artificial Intelligence and Machine Learning Capabilities
Current Time Inside Cache Tag Helper: 5/29/2023 12:09:49 AM and Model.reportId = 2869
Excited by the potential time and money savings, many healthcare organizations want a deeper understanding of what artificial intelligence (AI) and machine learning (ML) technology from public cloud providers could do for them. This research, a follow-up to KLAS’ 2021 report on Amazon Web Services (AWS), examines the experiences of 13 payer and provider organizations using AWS AI/ML offerings. This study is meant to help organizations considering AWS understand what technologies are being used, the overall customer experience, and the impact of these offerings. This report also shares AWS clients’ insights into their selection process and their perceptions of Google Cloud Platform (GCP) and Microsoft Cloud (both of which will be the focus of future reports). To learn how KLAS defines AI and ML, see Healthcare AI CHIME Edition 2019: Actualizing the Potential of Artificial Intelligence.if you don't have a login, getting started is easy.
Key Findings:
- Operational Optimization Most Widely Deployed Use Case; Forward-Looking Energy Focused on Clinical Impact
- Reduced Manual Processes & Time Savings Are Key Outcomes
- Beyond Technology, Strong Service & Support Drive Perceptions of AWS as a Partner
- To Support Usability, Customers Encourage AWS to Make Training a Stronger Focus
- AWS Customers’ View of the Market: Microsoft Cloud a Viable Competitor, Less Enthusiasm for Google Cloud Platform

Writer
Amanda Wind Smith

Designer
Madison Moniz

Project Manager
Joel Sanchez
This material is copyrighted. Any organization gaining unauthorized access to this report will be liable to compensate KLAS for the full retail price. Please see the KLAS DATA USE POLICY for information regarding use of this report. © 2023 KLAS Research, LLC. All Rights Reserved. NOTE: Performance scores may change significantly when including newly interviewed provider organizations, especially when added to a smaller sample size like in emerging markets with a small number of live clients. The findings presented are not meant to be conclusive data for an entire client base.