Oracle Healthcare United States

AtlantiCare

Document Processing · IT Operations Automation

AtlantiCare wanted to reduce clinician documentation burden and improve emergency department workflows without disrupting care delivery, so it needed a clinical documentation solution tightly integrated with emergency medicine processes and the EHR.

99% of physician notes were created using the new documentation workflows
Nursing active EHR time per patient decreased 6%, from 7:53 to 7:36
Nursing chart-review usage increased by 40 percentage points
Physician documentation time per patient decreased 37%, from 5:36 to 3:18

Reported impact

Business outcome

AtlantiCare reduced physician documentation time, lowered nursing EHR effort, and drove strong workflow adoption in the emergency department, improving both clinician efficiency and day-to-day quality of life for care teams and patients.

  • Customer Experience
  • Productivity Improvement

Solution

AtlantiCare worked with Oracle Health to redesign emergency department workflows around Oracle Health AI Agents, Oracle Health Emergency Medicine, ED LaunchPoint, and Oracle Health Foundation EHR. Oracle first performed a workflow and documentation assessment, then used a design-build-test-educate method to optimize physician processes and introduce AI note creation inside the emergency medicine environment. Voice- and workflow-driven documentation capabilities now draft notes directly within the EHR, while chart-review views help clinicians and nurses retrieve patient information more efficiently during ED care. Because the implementation was grounded in workflow analysis instead of a standalone transcription tool, AtlantiCare could align the AI documentation layer with emergency medicine processes, chart review, and team adoption across providers and nurses. The result is an AI-enabled ED workflow that shortens documentation time while improving usability and staff acceptance.

Data flow

Patient encounters in the emergency department flow through Oracle Health Emergency Medicine and Oracle Health Foundation EHR, where Oracle Health AI Agents draft documentation and ED LaunchPoint supports workflow changes; chart-review views in the EHR then surface patient information for clinicians and nurses with less active time and manual navigation.

Solution architecture

4 components · 2 layers
  1. Storage
    • Oracle Health Foundation EHR Hosts the clinical documentation and chart-review workflows used by physicians and nurses.
  2. Serving
    • Oracle Health AI Agents Creates AI-enabled documentation workflows that reduce per-patient note time for emergency physicians.
    • Oracle Health Emergency Medicine Provides the emergency department workflow context that Oracle optimized before and during deployment.
    • ED LaunchPoint Supports streamlined emergency department workflow transitions alongside the new documentation process.

Architecture clues

  • AI documentation is embedded inside Oracle Health Foundation EHR workflows
  • Deployment followed a design-build-test-educate methodology
  • Emergency department transformation included workflow assessment before implementation

Evidence from the source

By April 2026, 99% of physician notes were created using the new documentation workflows.
Following implementation, physician documentation time per patient decreased by 37%, dropping from 5 minutes and 36 seconds to 3 minutes and 18 seconds.
Oracle Health worked with AtlantiCare to optimize physician workflows and documentation while implementing Oracle Health AI Agents and ED LaunchPoint.
Transparency Evidence & methodology 100/100 reference value · 74% 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 value100/100
  • 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 impact25/25
    5 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence74%
  • 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 evidence15/20
    3 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • 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. Oracle

    AtlantiCare customer story

    First-party
    https://www.oracle.com/customers/atlanticare/
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes

Date evidence

  • First archived Jun 26, 2025 · Internet Archive · Independent First Wayback Machine capture; confirms the page existed by this date, not when it was published.
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.