887 results.
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Rules of the Road Differ for Inpatient and Outpatient Coding
Author: Quick, Tara; Hickman, Stephani
Source: Journal of AHIMA
Publication Date: June 2015
As facilities approach the final laps in the race towards implementation of the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM), they should heed the yellow caution flag warning of basic challenges with the vast differences between inpatient and....
Connecting the Disparate: Middleware’s Role in Solving Healthcare’s EHR Interoperability Problems
Author: Voltz, Donald M
Source: Journal of AHIMA
Publication Date: May 2015
According to data published on HealthIT.gov, 173 health IT vendors are supplying certified electronic health record (EHR) products to more than 4,500 hospitals. Despite wide penetration of EHRs in hospitals, clinics, and physician offices, a lack of access to patient information between sy....
Workaday Informatics: How Healthcare is Applying Practical Informatics to Save Dollars and Lives
Author: Butler, Mary
Source: Journal of AHIMA
Publication Date: May 2015
Watch and learn. For clinical informaticist Nathan Patrick Taylor, MPH, MS, CHDA, and others like him, watching patient-physician encounters and learning from them is just as important as knowing how to query data in a health IT system. Because as technical as informatics can get, at its....
Application of Search Analytics in the Healthcare Profession
Author: Regard, Dan; Hedges, Ron
Source: Journal of AHIMA
Publication Date: May 2015
As the healthcare industry moves into an electronic health record (EHR)-only environment, practitioners increasingly have to “search” electronically stored information (ESI). They may need to do this to find, for example, the date on which a patient was given a specific drug and the dosag....
Assessing and Improving EHR Data Quality (2015 update)
Author: AHIMA Work Group
Source: AHIMA practice brief | Journal of AHIMA
Publication Date: May 2015
Editor’s Note: This Practice Brief supersedes the March 2007 [and March 2013] Practice Brief “Assessing and Improving EHR Data Quality.”
The United States-based Institute of Medicine (IOM) reported in 1999 that “at least 44,000 people, and perhaps as many a....
Standardization of Standards
Author: Orlova, Anna
Source: Journal of AHIMA
Publication Date: May 2015
In 1898 Yale University graduate Charles Dudley, PhD, looked for a solution to the seemingly intractable problem of building a consensus on standards for industrial materials used on the Pennsylvania Railroad. To sooth the antagonistic attitudes that marred relationships between the Penns....
Healthcare Moving Toward an 'Information Ecosystem'
Author: Kowalski, Christine
Source: Journal of AHIMA
Publication Date: May 2015
Just as the world is held together and shaped by a delicate and intricate global ecosystem, the US healthcare system’s community of connected components, surviving and thriving when working together toward common goals, represents its own sort of ecosystem. As healthcare moves toward an i....
Data Analysis Starter Kit: How to Apply Informatics and Analyze ROI as an e-HIM Professional
Author: Dolezel, Diane
Source: Journal of AHIMA
Publication Date: May 2015
The digital era of Big Data has generated a growing need for more electronic health information management (e-HIM) professionals who can assume the emerging role of data analyst.1 This new role requires learning how to analyze data and perform statistical calculations to support informed d....
AHIMA Comments on the ONC 2015 Interoperability Standards Advisory
Author: Gordon, Lynne Thomas
Source: AHIMA testimony and comments
Publication Date: April 23, 2015
Letter to the Office of the National Coordinator for Health Information Technology (ONC)
Quality Data Starts With Us
Author: Dooling, Julie A
Source: AHIMA blog post | Journal of AHIMA - website
Publication Date: April 15, 2015
This monthly column will highlight and discuss emerging trends and challenges related to healthcare data and its ever changing life cycle.
Identifying patients correctly the first time is where data quality begins. Think of yourself as a patient for a moment.....
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