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ezDI, Inc.
33 followers -
"Empowering people to deliver innovative solutions that enhance human life."
"Empowering people to deliver innovative solutions that enhance human life."

33 followers
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ezDI, Inc.'s posts

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There is nothing more magical than decorated trees, lights, presents, family and friends to brighten up your life. Merry Christmas! Happy Holidays!
#MerryChristmas #HappyHolidays
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WEBINAR: CAC and CDI Technology 101: Learn about the current technologies available today when evaluating CAC and CDI.
This webinar will provide insight into:
– Different technologies available (Cloud and Premise-based) as well as PROS and CONS
– Who should you engage internally in order to make sure you have everyone’s buy in at all levels
– Key features to evaluate that will make the difference between a good platform and an inadequate system
– Key functions you should expect in a system that need to be a part of any application that you evaluate
Please register today for this FREE Webinar! We look forward to your participation on the webinar.

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Visit ezDI Inc, a venture of Mediscribes Inc. at TORCH & ILHIMA 2016 Annual Meeting and learn more about how our ezCAC & ezCDI solution help your hospital steamline coding wokflow.

Learn more at - www.ezDI.com

#ILHIMA2016   #TorchConf   #HealthIT   #ICD10   #ComputerAssistedCoding   #ClinicalDocumentationImprovement   #CAC   #CDI   #HealthCare   #HealthCareIT   #HIT100   #HIT99  
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We are all set for Ohio Health Information Management Association (OHIMA) 2016 Annual Conference". Visit our booth # 51 and meet our Regional Vice President Art Erickson in person.

We look forward to having the chance to learn about your facility and discovering opportunities to speed up revenue recognition.

Learn more about our product offerings at www.ezDI.com
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Here we are at ILHIMA 2015. Do visit our booth
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ezDI’s ezNLP Wins SemEval 2015 Competition

ezDI™, a leading provider of Computer-Assisted Coding, Automated CDI, Speech Recognition solutions and clinical documentation services, has been ranked #1 in the Semantic Evaluation of Clinical Data (SemEval - Task 14-1) competition for year 2015.

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ezCDI helps you overcome your challenges

Challenges
 
Hospitals face several challenges which can be addressed by a strong CDI Program. 

Some of the challenges are captured below:
Incomplete (pending or improper) documentation (e.g. lack of code specificity and severity of illness) resulting in insufficient information for coding. This impacts quality of care and hospital revenues.
 
Improve DNFB (Discharge Not Final Billed) and CMI (Case Mix Index) metrics
 
Establish the CDI program and set up ongoing process to improve clinical documentation
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ezCDI Technology

Automated Data Collection & Prioritization
 
ezCDI makes things you do every day easier, better and faster. By abstracting clinical data concurrently and analyzing the health records for conflicting, incomplete or nonspecific provider documentation, ezCDI streamlines and strengthens your CDI process. Our proprietary CDI algorithm analyzes the documentation for the illness identified and creates the query if a specific documentation is not available. The CDI specialist validates the queries and sends it to the Physician for necessary approval.
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ezAudit

Identify Coding Errors
 
With ezAudit, you can review cases to ensure that coding is being done in compliance with coding rules and official guidelines. Comprehensive search filters makes it easy to perform audit in areas identified such DRG targets, RAC goals, etc. You can easily compare the clinical documentation to the codes assigned and evaluate for compliant and efficient coding and complete documentation. ezAudit has built-in OIG (Office of the Inspector General) recommended sampling algorithm that ensures compliance with statutory auditing sampling guidelines.
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ezCDI

Proprietary CDI Algorithm
With Integrated NLP, Semantic Web & Machine Learning
 
The queries are automatically generated by our proprietary CDI algorithm and sent to the CDI specialist for validation and approval before sending it to the Physician. Using the NLP and the ontology, the system looks for specific documentation based on the illness identified and it creates a query if specific documentation is not available. For example, duration of occurrence for Myocardial Infarction is not mentioned, For example, it will identify that the Duration of occurrence of Myocardial Infarction is not mentioned, Stage of Decubitus Ulcer not mentioned etc.
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