Clinical Decision Support
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Deliver convenient, quality care asynchronously
Bright.md’s asynchronous telehealth solution lets providers treat low-acuity conditions virtually, without a real-time interaction—all while driving patient satisfaction and quality outcomes. With evidence-based clinical content and seamless integration into your existing workflows, Bright.md automates administrative work to allow providers to practice at the top of their license.
What is Bright.md?
Bright.md is a complete, white-labeled solution for health systems to empower their patient population with self-service online tools that guides them to the optimal type of care based on their concern, and when determined appropriate, take a thorough symptom assessment to receive a diagnosis and treatment plan from their own providers.
Enable an accessible care option 24/7 for common conditions via a patient initiated, online symptom assessment to gather all necessary information for 130+ treatable diagnoses.
Treat low-acuity conditions quickly and efficiently, while preserving clinical judgment and autonomy with Bright.md’s evidence-based clinical decision support for diagnosing. Bright.md translates the patient interview into a chart-ready SOAP note and makes it readily available via MDM interface for integration as an encounter in the EHR (Epic, Cerner, Athena).
Achieve positive patient outcomes at lower costs with digital navigation that guides patients to the optimal venue of care, right from your website or portal.
Bright.md is trusted by enterprise health systems around the country including Presbyterian Healthcare Services, Baptist Health, UnityPoint Health, Prisma Health, Mercy Health, and OHSU.
Biofourmis Therapeutics accelerates therapy innovation and clinical research with its holistic, end-to-end solution to remotely capture and analyze continuous patient data utilizing FDA-cleared algorithms in clinical trial settings.
AdviNOW uses AI to interprete all data gathered during a patient encounter. Present rank ordered illlness & treatments based on peer reviewed literature, create a SOAP and discretely scribe into EMR