RXNT
RXNT's cloud-based, ambulatory healthcare software empowers medical practices and healthcare organizations of all sizes and most specialties to launch, succeed, and scale through innovative, data-backed, AI-powered software.
Our integrated, ONC-certified healthcare software system—including Electronic Health Records, Practice Management, Medical Billing and RCM, E-Prescribing, Practice Scheduling, Patient Portal, and more—will streamline clinical outcomes, practice management, and revenue cycle management for your medical organization.
RXNT is trusted by over 60 thousand providers and medical professionals across all 50 states in the U.S.A. to drive business growth, optimize operations, and improve the quality of patient care.
All of our SaaS-based software products can be purchased standalone, but you can run you entire practice—from encounter to billing—with our unified Full Suite system. It utilizes a secure, central database so your data passes through every product in real-time from anywhere. Using our software, more than 125MM prescriptions have been transmitted and over $7B in claims have been processed.
Our predictable, transparent subscription pricing model includes free setup & training, support, mobile apps, and more.
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Elation Health
Elation Health is the leading platform for primary care, empowering 32,000 clinicians to deliver personalized care to over 16 million patients. With a clinical-first EHR, integrated billing, and AI-powered tools, Elation simplifies care workflows to help independent practices thrive.
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Google Cloud Natural Language API
Leverage advanced machine learning techniques for thorough text analysis that can extract, interpret, and securely store textual data. With AutoML, you can create top-tier custom machine learning models effortlessly, without writing any code. Implement natural language understanding through the Natural Language API to enhance your applications. Utilize entity analysis to pinpoint and categorize various fields in documents, such as emails, chats, and social media interactions, followed by sentiment analysis to gauge customer feedback and derive actionable insights for product improvements and user experience. The Natural Language API, combined with speech-to-text capabilities, can also provide valuable insights from audio sources. Additionally, the Vision API enhances your capabilities with optical character recognition (OCR) for digitizing scanned documents. The Translation API further enables sentiment understanding across diverse languages. With custom entity extraction, you can identify specialized entities within your documents that may not be recognized by standard models, saving both time and resources on manual processing. Ultimately, you can train your own high-quality machine learning models to effectively classify, extract, and assess sentiment, making your analysis more targeted and efficient. This comprehensive approach ensures a robust understanding of textual and audio data, empowering businesses with deeper insights.
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Verana Health
Verana Health operates as a platform for real-world data that converts both structured and unstructured information from electronic health records into curated, de-identified, disease-focused data modules through its clinician-informed and AI-enhanced VeraQ population health data engine. By aggregating data from key collaborations with prominent medical registries, including the American Academies of Ophthalmology, Neurology, and Urological Association, the platform integrates insights from over 20,000 clinicians and approximately 90 million patient records, thereby supplying high-quality datasets in near real-time for the purposes of generating real-world evidence, identifying clinical trial sites and subjects, reporting clinician quality, and managing medical registries. Users can access this wealth of information through cloud services like AWS Data Exchange and Amazon Redshift, which provide self-service API access, a user-friendly dashboard, and tools for customizable cohort discovery. Furthermore, the system employs advanced AI and machine learning algorithms along with comprehensive data quality assessments to ensure the reliability and accuracy of the information provided. This innovative approach not only facilitates efficient data utilization but also enhances the overall quality of healthcare research and practice.
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