Normalized claim
Nursing hours saved: 11,000 hours
Acentra Health saves 11,000 nursing hours with MedScribe, built on Azure OpenAI.
AI in Action: How Microsoft is Powering the Next Era of US Healthcare
Use case typeHealthcare workflow automationUpdated Sep 10, 2025
Microsoft highlights healthcare organizations in the US using Azure OpenAI, Microsoft Dynamics 365 Cloud for Healthcare, Microsoft AI and GitHub Copilot to automate clinical and administrative workflows. Examples include Acentra Health's MedScribe appeals workflow, Sayvant's discharge instruction generation, City of Hope's patient summaries, Carle Health's automated SMS reminders, Virtual Dental Care's Smart Scan screening app, CareSource's documentation automation and Syneos Health's drug development acceleration.
- Organization
- Acentra Health
- Industry
- Healthcare
- Location
- United States
- Published
- September 2025
Reported outcomes
125,000 USD
savingsCost savings
11,000 hoursnursing hours saved50%letter-writing time reduction30 letters per dayletters reviewed per day50,000 hoursclinician hours redirected87%appointment response rate
Strategic outcomes
Customer experience & trustImproved patient access and engagementOther strategic outcomeReduced clinician documentation burdenSpeed & agilityAccelerated drug development decisions
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Letter-writing time reduction: 50%
reducing letter-writing time by 50%.
Normalized claim
Letters reviewed per day: 30 letters per day
Nurses now review up to 30 letters per day (up from 12)
Normalized claim
Clinician hours redirected: 50,000 hours
Sayvant redirects 50,000 clinician hours to care
Normalized claim
Appointment response rate: 87%
boosting response to 87%
Normalized claim
Screening paperwork reduction: 75%
reducing school screening paperwork by 75%
Normalized claim
Documentation timeline reduction: 75% decrease
documentation timelines have been reduced from two months to two weeks
Normalized claim
Savings: 125,000 USD decrease
automation has delivered over $125K in savings
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Acentra Health, Sayvant, City of Hope, Carle Health, Virtual Dental Care, CareSource, Syneos Health
- Provider
- Microsoft
- Maturity
- Pilot
- Linked source
- Microsoft in Business Team
The article positions these deployments as moving from pilot projects to real-world transformation
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 3
- 1Healthcare workflow automation
- 2Clinical documentation
- 3Patient engagement
- Managing clinical documentation burdens
- improving patient access
- reducing clinician burnout
- speeding drug development
- AI-powered automation tools built on Microsoft Azure OpenAI and other Microsoft cloud services are used to generate summaries, reminders, discharge instructions and documentation, and to support predictive modeling and automation.
- The article positions these deployments as moving from pilot projects to real-world transformation.
- Acentra Health reduced letter-writing time by 50% and saved 11,000 nursing hours.
- Sayvant redirected 50,000 clinician hours to care.
- Carle Health boosted response rates to 87%.
- Virtual Dental Care reduced school screening paperwork by 75%.
- CareSource reduced documentation timelines from two months to two weeks, delivered over $125K in savings and saw 20-30% productivity gains.
- Syneos Health cut activation time by 10% in 2024 and reduced site selection from months to 24-48 hours.
Sources & evidence1
Evidence: Medium50/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Quantified outcome available
- Technical implementation details available
Type: Blog PostPublished: Sep 10, 2025Publisher: Microsoft in Business TeamEvidence: VendorConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
Explore related AI use cases
Customer evidence
Provider evidence
Was this useful?
Community
Comments
No published comments yet.