Evidence: Low35/100

Contrast AI automates physician documentation with AWS HealthScribe

Contrast AI reduces physician administrative burden from EHR documentation and improves efficiency and satisfaction during patient visits using AWS HealthScribe, Amazon S3, Amazon Comprehend Medical, and Amazon RDS in its ContrastHub workflow.

Organization
Contrast AI
Industry
Healthcare
Published
December 2024

Reported outcomes

+93%

physician satisfaction with documentation processCustomer experience

−80%documentation time per patient visit400 recordspatient records processed daily−99.8%critical data access time+99%patient consent rate

Strategic outcomes

Customer experience & trustImproved doctor-patient engagementOther strategic outcomeReduced physician burnout burden

Catalog median for customer experience deployments: +25% across 53 reported metrics. Compare benchmarks →

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Documentation time per patient visit: 80% decrease

AWS Healthcare & Life Sciences BlogDec 6, 2024Blog postExplicit claimLow evidence strength

"helped healthcare providers achieve an 80% reduction in documentation time per patient visit"

Normalized claim

Patient records processed daily: 400 records increase

AWS Healthcare & Life Sciences BlogDec 6, 2024Blog postExplicit claimLow evidence strength

"Clinics can now process up to 1,000 patient records daily, compared to 200 previously"

Normalized claim

Critical data access time: 99.8% decrease

AWS Healthcare & Life Sciences BlogDec 6, 2024Blog postInferred claimLow evidence strength

"access critical data within 24 hours instead of weeks"

Normalized claim

Patient consent rate: 99% increase

AWS Healthcare & Life Sciences BlogDec 6, 2024Blog postExplicit claimLow evidence strength

"99% of patients consented to the use of Contrast AI's technology"

Normalized claim

Physician satisfaction with documentation process: 93% increase

AWS Healthcare & Life Sciences BlogDec 6, 2024Blog postExplicit claimLow evidence strength

"reported a 93% increase in satisfaction with the documentation process"

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
Customer
Contrast AI
Provider
AWS
Maturity
Unknown

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 2 of 2

  • 1Clinical documentation
  • 2Workflow automation
Reduce physician administrative burden from EHR documentation and improve efficiency and satisfaction during patient visits.
ContrastHub records patient-doctor conversations, uploads audio to Amazon S3, uses AWS HealthScribe to convert audio into structured clinical documentation summaries and transcripts, and uses Amazon Comprehend Medical to extract key medical entities for physician review and approval before EHR update.
  • AWS HealthScribe helped reduce documentation time per patient visit by 80%.
  • Clinics can process up to 1,000 patient records daily instead of 200.
  • Critical data can be accessed within 24 hours instead of weeks.
  • 99% of patients consented to use of the technology.
  • Physicians reported a 93% increase in satisfaction with the documentation process.
Architecture

After patient consent, visit audio is recorded in ContrastHub via mobile app or web client, securely uploaded to Amazon S3, processed by AWS HealthScribe into standardized H&P/SOAP notes with transcripts, speaker roles, dialogue relevance classification, and evidence linking, then enriched with Amazon Comprehend Medical to extract diagnoses and medications for physician review and EHR update. Amazon RDS is used for data storage.

Sources & evidence1
Evidence: Low35/100Evidence strength
  • Customer explicitly identified
  • Quantified outcome available
  • Technical implementation details available
Type: Blog PostPublished: Dec 6, 2024Publisher: AWS Healthcare & Life Sciences BlogEvidence: VendorConfidence: High

AI-generated summary. Verify important details with the linked sources before relying on this case.

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