Healthcare Orgs Report Improved Processes, Patient Experience with AWS

A new report from KLAS Research found that a majority of healthcare organizations reported better and faster processes, improved clinician and patient experience, and reduced costs while using Amazon Web Services (AWS).

The report outlines how some healthcare organizations are using AWS and its artificial intelligence (AI) and machine learning (ML) offerings, in addition to their perceptions of AWS, the Google Cloud Platform, and the Microsoft Cloud.

The report evaluated responses from 13 providers and payers regarding the AWS offerings they use, how they use them, the outcomes they achieve, their loyalty to AWS, how AWS can support usability for healthcare customers, and their perceptions of AWS competitors Google Cloud Platform and Microsoft Cloud.

AWS currently offers six HIPAA-eligible AI/ML technologies:

• Amazon Comprehend Medical, which extracts medical information from medical text using natural language processing (NLP) and can link the extracted information to allow users to build applications for specific healthcare use cases
• Amazon HealthLake, which enables organizations to import and store disparate medical information from multiple data sources in Fast Healthcare Interoperability Resources (FHIR) format, in addition to querying and analyzing data at scale
• Amazon Lex, which enables developers to build conversational interfaces for applications using voice and text, natural language understanding (NLU) and automatic speech recognition (ASR)
• Amazon SageMaker, an AI/ML platform used by developers and data scientists to build, train, deploy, and monitor ML models at scale
• Amazon Textract, which extracts data from handwritten, scanned, or other physical documents
• Amazon Transcribe Medical, an ASR service that uses ML to accurately convert discussions between clinicians and patients into text

Of the organizations surveyed, 69 percent used Amazon Comprehend Medical, 31 percent Amazon HealthLake, 23 percent Amazon Lex, 69 percent Amazon SageMaker, 23 percent Amazon Textract, and 8 percent Amazon Transcribe Medical.

In terms of use cases for these offerings, 46 percent of the organizations reported using them for operational optimization, 31 percent for patient/member engagement, 23 percent for health/disease management and prediction, and 15 percent for both clinical research and population health management.

The most common use cases for providers included incorporating consent forms in the EMR, improving patient flow in the operating room by gathering needed personal health information before surgery, and converting unstructured patient notes into structured formats.

Payers reported using AWS solutions to extract and convert information from physical documents, such as faxes for prior authorizations, in addition to grievances, appeals, and member enrollment forms. Both groups are leveraging AWS tools to better understand the consumer experience and to engage patients or members.

Organizations also reported that AWS AI/ML offerings helped them achieve outcomes across multiple categories. Sixty-two percent reported that they achieved better/faster processes, 54 percent reported improved patient or clinician experience, 23 percent reported reduced costs, and 15 percent reported both healthier patients/members and improved security.

Further, respondents indicated positive perceptions of AWS as a partner. All organizations in the survey stated that they would buy AWS products again and that the service is part of their long-term plans.

However, respondents did note issues with onboarding and ease of use of AWS products. Organizations that had positive onboarding and training experiences reported higher ease of use than those that reported weaker experiences in these areas. Overall, users stated that AWS could improve client success by advertising the availability and importance of training, along with making sure that training specialists understand various healthcare audiences.

When asked about their perceptions of and experiences with Google Cloud Platform and Microsoft Cloud, organizations shared multiple factors that influenced their decision to choose AWS as their primary cloud provider. Fifty-seven percent of respondents reported that they considered Google’s platform, but noted that either it was not comprehensive enough to fit their needs or that Google lacked focus and expertise in healthcare.

All the organizations that shared insights into their purchase decision process either considered Microsoft Cloud as a primary solution or selected it as a secondary solution behind AWS. Some respondents reported that they initially intended to use Microsoft’s platform but encountered issues that made them move to AWS. One organization reported finding Microsoft Cloud less developer-friendly than AWS, and another noted concerns about system performance. One midsize health system reportedly went with AWS because Microsoft’s platform seemed slower, the solutions more siloed, and the licensing more confusing.

KLAS Research will be releasing similar reports in the future, sharing insights from Google and Microsoft customers in healthcare.