AHIMA16 – How to Unlock Big Data to Analyze Populations

Nick Orser

Nick Orser, Senior Manager, Product Marketing

AHIMA16 – How to Unlock Big Data to Analyze Populations

Population health and analytics are at the forefront of almost every discussion about the future of healthcare. But the ability to analyze the health of a population is dependent on the accuracy with which claims, clinical, biographical, and other data can be aggregated and assembled into complete views of each patient. And this is much easier said than done. Patients’ names and addresses frequently change, birthdates and SSNs are frequently entered incorrectly, and patient data frequently comes with very little identifying information attached to it. This makes it challenging to associate the correct data with the correct patient. And without an accurate view of each patient, it is impossible to gain an accurate view of a population.

Related Content: Deploy a SaaS EMPI solution in six weeks that is the most accurate, easiest to implement, most secure, and most cost effective EMPI on the market

Existing patient matching technologies like Enterprise Master Patient Index (EMPI) and Master Data Management (MDM) tools have only gotten us so far in solving the problem of associating the correct data with the correct patient. But a new generation of solutions have been developed that overcome the barriers faced by EMPI and MDM technologies.

If you’re attending AHIMA16 in Baltimore, come hear Verato Founder and Chief Technology Officer Brent Williams discuss how to unlock big data to analyze populations by using Referential Matching technology. Click here to learn more about the speaking session.

More information about the speaking session:
Date: Monday, October 17, 2016
Time: 3:15 PM – 4:15 PM
Location: Rooms 301-303 of the Baltimore Convention Center

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