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Medical Notes
Risk Analysis
Our award winning platform leverages the latest clinical algorithms, machine learning technology,
advanced natural language processing, and a proprietary clinical contextual ontology to
improve patient journeys
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How it helps
Smart Health Insights for Providers, Patients and Partners
powerful APIs as well as proprietary solutions on
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CloudMedx Connecting the Dots
Our award winning platform leverages the latest clinical algorithms, machine learning technology, advanced natural language processing, and a proprietary clinical contextual ontology to improve patient journeys
Data exchanges
Patient encounters analyzed
Readmission reductions
Bonus payments
Chronic patients identified
key features
outcomes driven by data insights
CloudMedx is working with the Orthopaedic Department at UCSF (University of California San Francisco) to predict outcomes for patients that have had recent hip and/or knee replacement surgeries. The CloudMedx platform combines EHR data, patient reported outcomes and device data to come up with insights on patient recovery factors.
The CloudMedx platform has algorithms for Congestive Heart Failure monitoring and prediction. The goal is to identify high risk individuals and provide appropriate care for those individuals to prevent an adverse event.
The CloudMedx platform is deployed to predict and monitor disease progression for Chronic Kidney Disease patients. The goal is to identify high risk patients that may progress to End Stage Renal Disease quickly. The platform enables care providers to take appropriate measures ahead of time.
The CloudMedx platform enables care providers to manage and monitor their diabetic population. The platform not only identifies high risk individuals for diabetes progression but also identifies additional associated comorbidities that may lead to adverse events.
We help health systems streamline and optimize their clinical encounters in real time with our clinical knowledge engine. Overlooked data points come to the forefront, the clinician returns to the core of care and patient centered healthcare becomes a reality - driven by your data.
Working with CloudMedx provides us with insights from data and augment workflows, treatment options and planning (for liver cancer patients). Most of this work is currently done manually and adds to administrative burden. Some of this heavy lifting may be done by a technology that can assist physicians. CloudMedx provides its AI powered tools and services that are healthcare specific.
Bilal Hameed, MD Hepatologist, UCSF
For complex surgeries, there can be a huge variability in documentation and coding and this requires coders to have a great deal of knowledge of anatomy and regulations associated with a specific subspecialty. With CloudMedx, we are looking to automate parts of this process and improve communication between all stakeholders so that this process is streamlined and made efficient.
Richard Capra, Chief Administrative Officer, UCSF Orthopedics Department
Clinical documentation in surgical specialties is a diverse and difficult area. It requires a lot of manual interventions and is heavily workflow oriented. With our work with CloudMedx, we are looking to automate this process and reduce the manual entry burden and communication between billers, coders and physicians so that this process is streamlined and made efficient, with low documentation errors and queries.
Khalid Mehmood, MD. President of Crescent Medical Center Lancaster
As a heterogenous disease that varies from patient to patient, ALS poses numerous challenges to clinicians seeking better treatments...this leads to long delays in diagnosis because ALS can mimic other more common diseases. Additionally, the unpredictability in rate of progression makes treatment challenging. Our goal in working with Cloudmedx is to see if we can identify clinical features that will help us identify patients earlier and improve our ability to predict the course of their disease.
Shafeeq Ladha, M.D. Director, Greg Fulton ALS and Neuromuscular Disorders Center
We wanted to combine Patient Reported Outcomes, data from Electronic Medical Records and Sensor data that patients wear to see how patients were doing. For this we partnered with CloudMedx as they could handle large sets of data and give us a perspective on how patients were doing with very strong predictive analytics.
Stefano Bini, M.D. Orthopaedic Surgeon, UCSF
As an industry, we do not have a sufficiently sophisticated tool to predict certain things such as disease progression and resulting readmissions in hospitals. We are working with CloudMedx to use new guidelines and algorithms, using clinical data to determine these risks and predictors. CloudMedx has a fast, scalable platform that can allows us to do just that. We found CloudMedx to be very intuitive and useful.
Ashish Atreja, MD, MPH, Chief Innovation and Engagement Officer, Mount Sinai
As the healthcare industry transitions to value-based care and risk-based reimbursement models, provider and payer organizations are looking for solutions to help identify patients with chronic health conditions within their populations and actively manage their care. Our partnership with CloudMedx allows us to do that effectively.
John Bennett, Chief of Business Development at Sutter Physician Services
Clinical Evidence Based Algorithms
We are currently building a portfolio of risk predictors in...
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