Microsoft Healthcare United States

Brown Health

Document Processing

As Brown Health expanded its regional footprint, clinicians faced rising patient demand, financial pressures, labor shortages, burnout, and heavy documentation demands that made it increasingly difficult to dedicate time for patient-centered care.

Burnout rates among physicians in some specialties can be 40% or more.
Copilot Studio has enabled Brown Health to build 24+ AI agents for ED guidance, routing, translation, scheduling and operations.
Dragon Copilot has now helped over 400 Brown Health clinicians reduce documentation burden and after-hours work.

Reported impact

Business outcome

Dragon Copilot has helped more than 400 Brown Health clinicians reduce documentation burden and after-hours work, while Copilot Studio has enabled the organization to build more than 24 AI agents for ED guidance, routing, translation, scheduling, and operations.

  • Customer Experience
  • Productivity Improvement
  • Scalability

Solution

Brown Health used Dragon Copilot, Microsoft 365 Copilot, and Microsoft Copilot Studio to reduce clinician documentation burden and extend AI into day-to-day care-delivery operations. After acquisitions and a physician-practice merger expanded the health system, clinicians were under pressure to see more patients, document more complex encounters, and keep pace with enterprise standardization across core platforms. Dragon Copilot records visits and drafts clinical documentation in parallel with the encounter, Microsoft 365 Copilot supports follow-on knowledge work, and Copilot Studio powers agents for ED guidance, policy lookup, patient access, translation, scheduling, and other operational workflows. Brown Health tied these tools into its broader digital transformation so staff could capture information once, route requests faster, and spend more time on direct patient care while scaling AI use across the organization.

Data flow

Clinical conversations are captured during patient visits, Dragon Copilot drafts documentation in real time, and Copilot Studio agents route policy, translation, patient-access, scheduling, and operational requests back to clinicians and staff while Microsoft 365 Copilot supports follow-on knowledge work.

Solution architecture

3 components · 2 layers
  1. Compute
    • Dragon Copilot Captures clinical conversations and drafts care documentation in real time.
  2. Serving
    • Microsoft 365 Copilot Supports knowledge work and follow-up tasks around clinical and operational workflows.
    • Microsoft Copilot Studio Builds AI agents for ED guidance, policy lookup, routing, translation, scheduling, and other operational processes.

Architecture clues

  • Extends a core Copilot rollout with agent-based workflows for policy, access, translation, scheduling, and operations.
  • Uses ambient clinical documentation to capture visit details in parallel with patient engagement.

Evidence from the source

As Brown Health expanded its regional footprint, clinicians faced rising patient demand, financial pressures, labor shortages, burnout, and heavy documentation demands that made it increasingly difficult to dedicate time for patient-centered care.
Brown Health adopted Microsoft Dragon Copilot and Microsoft 365 Copilot and then used Copilot Studio to build AI agents that support clinical workflows, hospital policies, patient access and operational processes.
Dragon Copilot has now helped over 400 Brown Health clinicians reduce documentation burden and after-hours work, while Copilot Studio has enabled Brown Health to build 24+ AI agents for ED guidance, routing, translation, scheduling and operations.
Now, I can focus on what I think is going on with you and hearing you and being with you. The documentation is happening in parallel with engagement with the patient.
One of the main challenges in health care these days is that our clinicians—our doctors, our nurses, our pharmacists, really any of our clinical staff—are increasingly burned out.
Transparency Evidence & methodology 95/100 reference value · 89% 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 value95/100
  • 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 specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    2 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence89%
  • 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
    5 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 specificity10/10
    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

    Brown Health customer story

    First-party
    https://www.microsoft.com/en/customers/story/26765-brown-university-health-microsoft-365-copilot
    Source type
    Vendor-published customer story
    Published
    Jul 25, 2026
    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 Jul 25, 2026 · 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.