Measuring clinical
communication quality.

We develop analytic solutions that transform clinical conversations into structured, measurable insights—supporting healthcare quality improvement and research.

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Clinical care depends on communication, yet the quality of interaction between clinicians and patients is rarely measured systematically.

CCQ builds infrastructure to analyze clinical encounters and extract signals related to interaction and decision processes—using transcripts generated by existing ambient documentation technologies.

Our Methodology

We focus on measurement, not judgment. Our work is grounded in established decision-science and clinical communication literature and is designed to be:

  • Encounter-level and scalable
  • Vendor-agnostic and workflow-aware
  • Suitable for quality improvement and system-level analysis
Note: CCQ focuses on measurement and analysis and does not provide clinical recommendations or decision support.

Supporting the ecosystem of
clinical documentation.

01

Documentation Vendors

AI scribe and ambient documentation vendors seeking to evaluate communication and decision-related signals derived from transcripts.

02

Health Systems

Provider organizations conducting aggregated analysis of clinical communication patterns across clinicians, services, or care settings.

03

Researchers

Academic researchers and pilot partners studying clinical communication and decision-making processes in real-world settings.

Designed for Interoperability

CCQ is built to integrate with existing clinical documentation and AI scribe environments. Our tools are designed to complement—not replace—clinical workflows and existing health IT infrastructure.

The Team

CCQ is an early-stage healthcare analytics company led by a multidisciplinary founding team that includes a practicing clinician, health-services researchers, and health-system operators.

Together, we combine clinical insight with technical expertise to build scalable, policy-aware measurement infrastructure.