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The goal of CloudMedx is to analyze all structured and unstructured data and try to understand the patient holistically, and display not only what has already been determined, but also empirical (statistics based) perspectives on related conditions, drugs, tests and other factors. 
Coding Analyzer
for coding and documentation analysis
The Coding Analyzer has the potential to be an augmentation tool for coders and billers that provides the necessary alerts to manage medical coding thereby dramatically speeding up the process. This providers a consistent and transparent view of the financial opportunities and risks to the organization.

The Coding Analyzer provides not only what has already been determined, but also empirical (statistics based) risks and perspectives on related conditions, drugs, tests and other factors. This provides a holistic perspective for both clinical and billing services.

The Coding Analyzer:  

 Mines both structured and unstructured data
 Uses NLP and machine learning to gain insights from data
 Provides collaboration tools between providers and billers

The solution helps improve operational efficiency by doing the following:

1- Using advanced NLP algorithms to convert clinical notes into the relevant ICD codes.

2- Allows providers and payers to be reimbursed based on health status or “actuarial risk” of a patient population. It is designed to pay health plans more precisely for the anticipated health cost costs of a patient population by adjusting payments based on demographics and health status. These attributes are used to generate a risk score - a measure of a patient’s cost to a plan.
The screenshot above shows how ICD codes are automatically generated from a doctor note using healthcare specific natural language processing.

Automating the Clinical Documentation and Coding Process for 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
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Automating the Clinical Documentation Process for Crescent Medical Center

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
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Key Features
Automated Coding from Doctor Notes
Automated Risk Adjustment
Seamless Collaboration with Physicians
Documentation Analysis