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Cadwell and MIC to launch neurodiagnostic data and monitoring for hospitals

The collaboration will provide a data platform that can integrate EEG data with additional bedside monitoring information.

Srivani Venna December 12 2025

Cadwell and Medical Informatics Corp (MIC) have formed an alliance to launch new integrated neurodiagnostic data and monitoring standards for hospitals.

Under the agreement, Cadwell’s neurodiagnostic product will be integrated with the enterprise-grade multimodal data architecture of MIC's Sickbay Clinical Platform.

This integration is designed to deliver unified clinical intelligence that surpasses traditional device-focused systems, offering hospitals a holistic view of patient health.

Hospitals will be able to access a complete physiological view of patients through synchronised multimodal data, integrated clinical context and continuous native-format waveform capture.

This capability will span critical care, neurology and acute care environments.

Clinicians will combine Cadwell's neurodiagnostic data with bedside monitors, infusion pumps, ventilators, cameras, laboratory, and electronic health record (EHR) streams for visualising and analysing patient information from any location.

Furthermore, they can facilitate tele-neuro and remote monitoring and obtain streaming near real-time, as well as retrospective information for quality improvement and research.

MIC CEO Emma Fauss said: “Clinicians want a complete and continuous picture of every patient. Together with Cadwell, we are giving them the multimodal visibility and intelligence needed to make critical decisions faster.”

Hospitals are presently confronted with difficulties arising from disjointed systems that retain restricted data and hinder collaboration among care teams.

The collaboration between Cadwell and MIC seeks to address these challenges by providing a high-fidelity data platform that can integrate electroencephalogram (EEG) data with additional bedside monitoring information, while also offering enterprise scalability for AI and enhanced decision support.

This unified intelligence is expected to empower healthcare providers with a complete view of patients, supporting improved care quality and cost efficiency.

For health systems, the approach reduces total ownership cost and provides a unified data foundation that advances research, clinical care and operational performance.

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