RXNT
RXNT has spent over 25 years building cloud-based healthcare software designed for ambulatory practices and medical organizations of all sizes and specialties. Our innovative, AI-powered, and data-backed software solutions help practices grow, improve clinical efficiency, and streamline business operations—whether you're a solo provider, large healthcare organization, or billing services company.
With over 60,000 medical professionals across all 50 U.S. states relying on RXNT, our fully-integrated, ONC-certified software system includes Electronic Health Records (EHR), Physician Practice Management (PPMS), Medical Billing and Revenue Cycle Management (RCM), E-Prescribing (eRx), Scheduling, Patient Portal, mobile applications, and more. Every product works seamlessly as one system or can be used standalone, giving you flexibility to choose what works best for your practice.
Our SaaS-based Full Suite software solution integrates every area of RXNT through a secure, centralized database, enabling real-time data flow across clinical and administrative functions.
Whether you're modernizing your medical practice or scaling your healthcare business, RXNT delivers all-in-one technology to help you succeed. So far, users have transmitted over 125 million prescriptions and processed more than $7 billion in insurance claims.
Built for usability and accessibility, RXNT’s cloud-based software is available 24/7 from any device and includes mobile apps for iOS and Android. Simple, transparent pricing means no hidden fees, and every plan includes free implementation & training periods, data migration, storage, software updates, and U.S.-based customer service.
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Ensora Mental Health
TheraNest is designed to reduce the time therapists spend on administrative tasks, allowing them to focus on providing quality care. With features such as automated billing, appointment scheduling, and note-taking, TheraNest helps mental health practices run more efficiently and cost-effectively. The platform also includes integrated features like telehealth, client engagement tools, and reporting for streamlined operations and better patient outcomes. TheraNest is a powerful tool for therapists seeking to optimize their practice management while improving patient care and reducing burnout.
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Altis Labs Nota
Altis Labs has introduced Nota, a groundbreaking platform aimed at improving the efficiency of therapeutic research and development in the clinical field. By leveraging artificial intelligence, Nota assesses imaging data to forecast patient outcomes, enabling sponsors to better concentrate on their most viable therapies. This cutting-edge tool equips researchers with the ability to utilize imaging data from clinical trials, access predictive biomarkers, and accelerate research initiatives on a broader scale. With Altis' cloud-based software that employs deep learning techniques, biopharma companies can achieve comprehensive outcome predictions at the levels of individual images, patients, and entire cohorts, thereby enhancing the design of clinical trials and boosting confidence in predicting clinical endpoints. The insights provided by Nota hold the potential to significantly shorten development timelines, reduce drug development costs, and increase the likelihood of success in clinical trials across diverse therapeutic areas. Furthermore, Nota signifies a major leap forward in the fusion of technology with clinical research, ultimately paving the way for more streamlined and effective drug development methodologies. This innovation not only promises to transform the landscape of clinical trials but also aims to improve patient outcomes in the long run.
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Amazon Comprehend Medical
Amazon Comprehend Medical is an NLP service designed to adhere to HIPAA standards, employing machine learning to extract health information from medical documents without necessitating any prior expertise in machine learning from its users. A vast amount of healthcare data is found in unstructured formats, such as physicians' notes, clinical trial reports, and patient histories. Relying on traditional, manual methods for data extraction is not only time-consuming but also prone to errors, as rule-based automation often fails to capture essential contextual details, resulting in incomplete data retrieval. This lack of reliability can significantly undermine the effectiveness of large-scale analytics, which are critical for advancements in the healthcare and life sciences industries, ultimately impeding potential enhancements in patient care and operational effectiveness. By utilizing this sophisticated service, healthcare organizations can gain invaluable insights and improve their decision-making capabilities, ultimately leading to better outcomes for patients. This transformative approach represents a significant leap forward in how health data can be leveraged for greater efficiency and efficacy in medical practices.
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