AHIMA calls for HIM professionals to be more active in HIEs

Accurate patient identification is crucial to the success of health information exchange efforts, which is why health information management professionals must actively pursue leadership roles within their local HIEs, according to a new white paper published by the American Health Information Management Association.

Such professionals, the paper's authors say, provide added peace of mind with regard to the delivery of quality data. "Ideally, the health data in an electronic record should be accurate, up-to-date and complete; but unfortunately the real world is far from ideal," they say. "High-quality data requires us to have a very clear understanding of the meaning, context, and intent of the data--unambiguous and, ideally, standardized computable definitions of data that can form the basis for future safe decision making."

For instance, with regard to patient identification, the authors write that much of the process of maintaining, correcting or updating information hinges on HIEs, which makes quality leadership at that level invaluable.

"Clear and concise policies and procedures are required at both the organizational and HIE levels to ensure corrections are handled in an appropriate manner," the authors say. "Since it is essential to propagate any change to all copies of the health records across the continuum of care, all participants within the HIE should understand how and when corrections will be made by the HIE and the impact those corrections may have on the patient's records."

In light of recently reported data breaches, such leadership becomes even more vital. Laptops with personal and health-related information on patients seem to be disappearing left and right of late, and just this week, the Government Accountability Office gave its two cents to Congress on such matters, calling for privacy protection laws to keep up with technology in healthcare and many other industries.

In June, the Bipartisan Policy Center released a brief calling for improved patient data matching in EHRs.

To learn more:
- read the white paper (.pdf)

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