Medical Informatics Corp

Medical Informatics Corp. (MIC), a Houston-based company founded in 2010, operates at the intersection of medical device data and clinical analytics. The firm was established by CEO Dr. Emma Fauss and CTO Craig Rusin. Dr. Fauss's background in electrical and computer engineering, combined with an MBA focused on healthcare, converged with Rusin's academic research on using physiological data to predict patient deterioration. This synergy led to the creation of a scalable technology designed to be implemented in hospitals globally.

The company's core business revolves around its FDA-cleared, software-based platform, Sickbay™. This platform functions as a vendor-neutral clinical surveillance and analytics tool for hospitals and healthcare systems. MIC's business model is centered on providing this technology as a service to address critical challenges in healthcare, such as staff shortages and the need for more efficient patient monitoring. The company generates revenue through this SaaS model, which allows hospitals to reduce costs and improve operational efficiency.

Sickbay's primary function is to aggregate, archive, and process high-fidelity, time-series waveform data from disparate bedside medical devices in near real-time. This data, which includes vital signs like heart rate and oxygen saturation, is often discarded by individual monitoring systems after a short period. Sickbay captures and unifies this information with data from electronic medical records (EMRs), creating a comprehensive, continuous patient history accessible through a web-based interface. This allows for remote monitoring of up to 100 patients at a time, enabling the creation of scalable tele-ICUs and virtual care environments. A key feature is the platform's open APIs, which permit hospitals, physicians, and researchers to develop and deploy their own custom algorithms and predictive analytics on top of the aggregated data.

By providing a unified architecture, Sickbay aims to eliminate data silos created by proprietary device formats. This enables clinicians to make more informed, data-driven decisions by having access to complete patient data from anywhere, at any time. The platform's machine learning capabilities are used to develop analytics that can help predict patient risk and deterioration, aiming to shift care from reactive to proactive. The company has secured significant funding, including a Series B round, to fuel its expansion and support implementations in hospital systems across the United States.

Keywords: patient monitoring, clinical surveillance, healthcare analytics, waveform data, medical device integration, predictive analytics, remote patient monitoring, virtual care, tele-ICU, data-driven healthcare, clinical decision support, FDA-cleared medical software, hospital IT infrastructure, real-time analytics, alarm management, physiological data, patient deterioration prediction, healthcare data aggregation, vendor-neutral platform, health system technology