Healthcare

Regard

AI clinical insights platform that improves diagnosis and documentation

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Clinical Decision Support Healthcare AI Medical Documentation Diagnosis Assistance Electronic Health Records Clinical Insights Hospital Technology Medical Analytics
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About Regard

Regard is an AI-powered clinical insights platform designed to help healthcare providers identify diagnoses and generate more complete clinical documentation. The platform analyzes patient records and surfaces relevant clinical findings at the point of care. It helps clinicians improve documentation accuracy, reduce administrative burden, and capture missed diagnoses. Regard reviews large amounts of patient data to provide actionable recommendations before and during patient visits. The platform is used by hospitals and health systems to improve care quality and operational performance. Its primary focus is proactive clinical decision support and documentation enhancement.

Frequently Asked Questions

What is Regard and what clinical problem does it solve?
Regard is an enterprise AI co-pilot designed for hospitalists and healthcare systems to bridge the "Clinical Insights Gap." In modern medicine, a single patient record can contain an average of 50,000 data points, meaning busy doctors can realistically review only a tiny fraction of a patient's historical chart at the point of care. Regard solves this by automatically scanning, synthesizing, and analyzing the entirety of a patient's Electronic Health Record (EHR) data before the doctor even steps into the room. It uncovers hidden or overlooked data trends to recommend highly accurate diagnoses with supporting evidence.
What is meant by "Proactive Documentation" and how does it function?
Traditional medical documentation and medical coding solutions are reactive—they look over clinical notes after care has already been delivered to catch errors or fix billing codes. Regard shifts this framework from reactive to Proactive Documentation. By compiling and cross-referencing lab results, vitals, imaging, and past medical history beforehand, it surfaces relevant diagnostic insights and generates an automated draft of the clinical note in moments. The physician simply reviews, verifies, and accepts the findings, integrating the data seamlessly into their existing workflow.
How does Regard utilize OpenAI's GPT-4 and its chatbot "Max"?
To deeply operationalize large language models inside high-stakes hospital environments, Regard includes advanced functionality built on OpenAI's GPT-4 alongside an intelligent clinical assistant named Max. Operating like a highly efficient "AI Medical Resident," this system automatically drafts precise text sections of clinical documentation fully backed by real patient files. It also equips healthcare providers with an intelligent autocomplete search engine to rapidly dig through complex chart histories and continuously checks clinical notes against official medical guidelines to ensure strict auditing compliance.
What major ecosystem collaborations and hospital systems support the platform?
Regard is natively integrated with dominant electronic medical record architectures and is deployed across over 150 hospitals nationwide, including major enterprise-wide rollouts with nonprofit healthcare networks like Banner Health and Cedars-Sinai. To further scale its clinical reach, Regard collaborates directly with Microsoft Dragon Copilot. This integration merges Dragon Copilot's ambient voice listening and speech dictation workflows with Regard's deep data mining algorithms, enabling clinicians to harness comprehensive real-time EHR data insights straight through their primary voice assistant interface.
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