Overloaded with episodic and incomplete information, medical establishments sorely need digital health solutions for improved decision-making. Data analytics platforms are supporting medical staff and healthcare establishments to make more informed and data-based decisions. These solutions can help solve pressing problems, such as predicting what the best course of treatment for a certain patient is, or calculating the optimal time to release a patient from the hospital.
MedAware solutions are designed to identify and prevent prescription errors in real time in order to save lives, improve patient safety, and significantly reduce healthcare costs. The company’s patent-pending technology uses big data analytics and machine learning algorithms to analyze the large-scale data of electronic medical records to learn how physicians treat patients in real-life scenarios. Prescriptions deviating greatly from the spectrum of standard treatment patterns are flagged as potential errors, with high specificity and low alert fatigue.See full profile >>
Efficacy Care specializes in prescriptive health analytics, focusing on the delivery of real-time, evidence-based patient care to deliver better quality and increased safety while also setting a new standard of patient care outcomes. The company seeks to help stakeholders hospital-wide maximize value and improve quality of care. Efficacy Care’s real-time, data-driven use cases are ready for deployment. The first provides FTR/PSI04 recognition in acute care patients. The real-time analytics are designed to reduce patient harm by diminishing “failure to rescue” incidents by predicting patient deterioration and identifying patients at risk for PSI04 (specifically FTR2-FTR6). Efficacy Care’s second solution provides TPS system/hospital-wide HVBP monitoring. The results presented in the TPS visualization are calculated based on a bottom-up approach from patient-level data and represent the sum of four domains, including CMS: measures of efficiency; clinical process of care; patient experience of care; and outcomes and costs. The company’s third solution addresses clinical utilization reviews.See full profile >>
CLEW uses artificial intelligence and data science to develop patient-level physiological predictive models. Originally developed and proven in the intensive care unit (ICU), the models are now being extended to all care settings, where they are used to assist healthcare providers in forecasting the state of their patients. Deployable from the patient’s bedside to a centralized command-and-control facility, CLEW is designed to help providers make better-informed clinical decisions, improve outcomes and safety, streamline patient care, better cope with increased regulation and penalties, lower the cost of care, and remove discharge barriers. CLEW is currently being deployed in ICUs across Israel and in the United States for telemedicine capabilities. In February 2021, the company received FDA clearance for its AI-based predictive analytics technology that supports patient assessment in adult intensive care units.See full profile >>
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Last updated: January 2018
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Last Updated: January, 2018