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AWS Healthcare United States

Froedtert & the MCW Health Network

The Froedtert & the Medical College of Wisconsin (MCW) health network is using technology to reimagine healthcare. Its innovation arm, Inception Health , seeks to improve the patient experience through digital applications that use artificial intelligence (AI) and data analytics to personalize care and alleviate stress on clinicians.

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1.2 million
99.999 percent

Reported impact

Business outcome

Inception Health plans to become an early adopter of generative AI to further enhance the patient experience. Specifically, it is looking into Amazon Bedrock —a fully managed service that offers a choice of high-performing foundation models through a single API, along with a broad set of capabilities that organizations need to build generative AI applications with security, privacy, and responsible AI.

  • Risk Reduction

Solution

The Froedtert & the Medical College of Wisconsin (MCW) health network is using technology to reimagine healthcare. Its innovation arm, Inception Health , seeks to improve the patient experience through digital applications that use artificial intelligence (AI) and data analytics to personalize care and alleviate stress on clinicians. Inception Health’s small team quickly deploys highly reliable, secure digital products that personalize care for patients, using the Shared Responsibility Model for the security and compliance of its infrastructure. The serverless architecture uses AWS Lambda , a compute service that runs code in response to events and automatically manages the compute resources. An API layer helps to add patient-centric applications at scale. “Our developers build the entire user journey—infrastructure and logic—within the same code,” says Somai.

Data flow

Application logic runs on Amazon Bedrock, Amazon SageMaker and is surfaced through Amazon Pinpoint.

Solution architecture

5 components · 3 layers
  1. Ingest
    • Amazon Kinesis Data Firehose Streams data into downstream analytics or storage services.
  2. Compute
    • Amazon Bedrock Hosts the foundation models and generative AI application logic.
    • Amazon SageMaker Supports model training, tuning, deployment, or managed ML inference.
    • AWS Lambda Runs event-driven application logic and serverless processing tasks.
  3. Serving
    • Amazon Pinpoint Sends and personalizes patient or customer communications.

Architecture clues

  • The serverless architecture uses AWS Lambda , a compute service that runs code in response to events and automatically manages the compute resources.
  • To collect its data to power machine learning and other applications, Inception Health uses Amazon Kinesis Data Firehose , an extract, transform, load service that reliably capture

Evidence from the source

Healthcare systems typically use technology and analytics for supporting operations, such as population health programs and revenue-cycle or supply-chain management.
Inception Health’s small team quickly deploys highly reliable, secure digital products that personalize care for patients, using the Shared Responsibility Model for the security and compliance of its infrastructure.
Its innovation arm, Inception Health , seeks to improve the patient experience through digital applications that use artificial intelligence (AI) and data analytics to personalize care and alleviate stress on clinicians.
The Froedtert & the Medical College of Wisconsin (MCW) health network is using technology to reimagine healthcare.
The serverless architecture uses AWS Lambda , a compute service that runs code in response to events and automatically manages the compute resources.
With more than 1.2 million yearly visits to its network of more than 2,300 physicians, the Froedtert & MCW health network supports a mission of patient care, innovation, medical research, and education.
Transparency Evidence & methodology 66/100 reference value · 85% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value66/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth20/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity16/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact0/25
    0 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence85%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    6 direct source quotes retained.
  • Date provenance8/10
    The publication date comes from publisher-controlled metadata.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity8/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. AWS

    Froedtert & the MCW Health Network customer story

    First-party
    https://aws.amazon.com/solutions/case-studies/froedtert-mcw-case-study/
    Source type
    Vendor-published customer story
    Published
    Apr 11, 2024
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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