Microsoft Healthcare United States

Shriners Children's

Customer Service Automation · Data Lake / Data Warehouse Modernization · Enterprise Knowledge Search

Shriners Children's offers patient care to as many children as possible. Before its solution, the organization had to rely on the analytics team to provide them insights from patient clinical notes and history. This process was time-consuming and inefficient.

Reported impact

Business outcome

"The foundational models and user-friendly bot interface utilized by ChatGPT and similar tools increased buy-in to AI technologies in an incredible way. We were intrigued in taking these tools that were designed for general use by the public and utilizing them in a more specific use case for our research and clinical practices.

  • Compliance
  • Customer Experience
  • Productivity Improvement
  • Scalability

Solution

Shriners Children's offers patient care to as many children as possible. Before its solution, the organization had to rely on the analytics team to provide them insights from patient clinical notes and history. This process was time-consuming and inefficient. Healthcare professionals diagnose and treat patients based on information gathered in clinical notes. But oftentimes, these notes are housed in outdated systems. Some are even handwritten and, therefore, difficult to comprehend. For clinicians to treat patients promptly, there must be a more efficient solution and one that minimizes errors. Shriners Children's is an international healthcare system offering patient-centered care. But, to do this, it knew it had to house all clinical notes in a secure, cloud-based infrastructure. Fractal, a pure-play analytics company, focuses on data engineering, AI, and design to help its customers across industries.

Data flow

Operational and business data is gathered from the customer's source systems processed in Microsoft Fabric.

Solution architecture

2 components · 2 layers
  1. Compute
    • Azure OpenAI Service Runs the large-language-model features for classification, summarization, retrieval, or conversational responses in the solution.
  2. Storage
    • Microsoft Fabric Provides the shared data platform for storing, governing, and analyzing enterprise data across teams.

Architecture clues

  • Azure OpenAI Service: Runs the large-language-model features for classification, summarization, retrieval, or conversational responses in the solution.
  • Fractal decided to work with Microsoft Azure to build Shriners Children's solution because of its long-standing partnership, use of state-of-the-art technology, and security.
  • Fractal, a pure-play analytics company, focuses on data engineering, AI, and design to help its customers across industries.
  • Healthcare professionals diagnose and treat patients based on information gathered in clinical notes. But oftentimes, these notes are housed in outdated systems.
  • Microsoft Fabric: Provides the shared data platform for storing, governing, and analyzing enterprise data across teams.
  • Shriners Children's is an international healthcare system offering patient-centered care. But, to do this, it knew it had to house all clinical notes in a secure

Evidence from the source

"The foundational models and user-friendly bot interface utilized by ChatGPT and similar tools increased buy-in to AI technologies in an incredible way.
Healthcare professionals diagnose and treat patients based on information gathered in clinical notes. But oftentimes, these notes are housed in outdated systems.
Shriners Children's is an international healthcare system offering patient-centered care. But, to do this, it knew it had to house all clinical notes in a secure, cloud-based infrastructure.
Shriners Children's offers patient care to as many children as possible. Before its solution, the organization had to rely on the analytics team to provide them insights from patient clinical notes and history.
Transparency Evidence & methodology 75/100 reference value · 87% 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 value75/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    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 confidence87%
  • 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
    4 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • 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. Microsoft

    Shriners Children's customer story

    First-party
    https://www.microsoft.com/en/customers/story/1768027434711024743-shrinerschildrens-azure-health-provider-en-united-states
    Source type
    Vendor-published customer story
    Published
    May 16, 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

  • Published on source page May 16, 2024 · Microsoft · First-party
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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