Clinical Conflict Detection
Clinical Conflict Detection is an extension that flags potential conflicts in clinical notes.
- Category
- Machine Learning
- Registry category
- Operations & ProductivityWorkflow & Productivity
- Vendor
- Microsoftlisted as Microsoft Corporation
- Location
- REDMOND, WA
- Reviews
- Not rated (0 reviews on the listing)
- Listed on
- Microsoft Marketplace
- Pricing
- 1 plan listed
Each fact carries one Provenance score: the average of its Disclosure and Evidence scores, the same rule the page uses for the overall score. Click any score to see the math behind it.
Vendor Provenance
Who actually operates this agent.
Build Provenance
What the agent is built on.
Reach Provenance
How the agent is distributed and adopted.
Data Provenance
What the vendor discloses about data handling.
Compliance Provenance
What standards the vendor meets, and who verified them.
What the publisher says
Clinical Conflict Detection helps clinicians identify and review potential clinically inconsistent information within medical documentation, directly inside Dragon Copilot. It is designed for healthcare professionals to support the creation of accurate and consistent clinical documentation as part of their routine workflows.
This extension surfaces potential conflicts—such as laterality mismatches, opposing findings, or inconsistencies across sections of a clinical note—so clinicians can quickly review supporting context and decide whether updates are needed. The clinician remains fully in control of the final documentation.
Key Benefits
Show the rest of the publisher’s description (13 more lines)
- Improves clinical documentation quality by highlighting potential inconsistencies
- Supports patient safety and diagnostic confidence through early conflict awareness
- Reduces manual review effort by automatically flagging relevant sections
- Builds trust in AI‑assisted documentation workflows
Intended Users
- Physicians and clinicians creating or reviewing clinical notes
- Healthcare organizations using Dragon Copilot in clinical workflows
How It Works
Clinical Conflict Detection analyzes clinical documentation and identifies potential conflicts across findings, impressions, assessments, and history. Temporal context — such as when procedures were performed or measurements taken — is considered to ensure accurate conflict detection. Detected conflicts are presented with contextual evidence to support informed review. The feature is advisory in nature and does not make clinical decisions or automatically modify documentation. It is not intended for diagnosis or treatment
Industry & Category
- Healthcare IT
- Clinical Documentation Integrity
- AI‑assisted Clinical Workflow Support
Preview
2 imagesPlans and pricing
1 plan listed
Linked repositories
Unknown
Unknown means this listing does not publish a repository. It is not a statement that the code is closed.
Publisher resources
Sources
- Marketplace listingMicrosoft Marketplace (opens in a new tab)
- Legal linkPrivacy Policy (opens in a new tab)
- Legal linkLicense Terms (opens in a new tab)
- Company recordOutside company data, matched on microsoft.com
- Official registersearch.gleif.org (opens in a new tab)
Reading the score
Disclosure · how many sources corroborate it
Evidence · what kind of evidence backs it
The SettleTop steps above are possible but not automated yet, so today they sit open and a perfect 10 is out of reach. Open information like firmographics and reach has fewer steps to climb, so it sits a little higher for the same visible evidence.
Information shown here reflects the best available information at the time of assessment and may be incomplete, outdated, or subject to change. It should be independently verified before being relied upon for any decision. SettleTop is not liable for any errors, omissions, or decisions made in reliance on this information.
Have information about this agent?
Send it to us for consideration
Spot something missing, wrong, or out of date? Share what you know. Every note reaches our team. It does not change the passport by itself: we review it first.
