Events Calendar

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2015 HIMSS Annual Conference & Exhibition
2015-04-12 - 2015-04-16    
All Day
General Conference Information The 2015 HIMSS Annual Conference & Exhibition, April 12-16 in Chicago, brings together 38,000+ healthcare IT professionals, clinicians, executives and vendors from [...]
2015 CONVENTION - THE MEDICAL PROFESSION: TIME FOR A NEW SOCIAL CONTRACT
The 17th QMA's convention will be held April 16-18, 2015. The Québec Medical Association (QMA) invites you to share your opinion on the theme La profession médicale : vers un nouveau [...]
HCCA's 19th Annual Compliance Institute
2015-04-19 - 2015-04-22    
All Day
April 19-22, 2015 Lake Buena Vista, FL Early Bird Rates end January 7th The Annual Compliance Institute is HCCA’s largest event. Over the course of [...]
AAOE Annual Conference 2015
2015-04-25 - 2015-04-28    
All Day
AAOE Annual Conference 2015 The AAOE is the only professional association strictly dedicated to orthopaedic practice management. Currently, our membership has over 1,300 members in [...]
63rd ACOG ANNUAL MEETING - Annual Clinical and Scientific Meeting
2015-05-02 - 2015-05-06    
All Day
The 2015 Annual Meeting: Something for Every Ob-Gyn The New Year is a time for change! ACOG’s 2015 Annual Clinical and Scientific Meeting, May 2–6, [...]
Events on 2015-04-12
Events on 2015-04-19
Events on 2015-04-25
AAOE Annual Conference 2015
25 Apr 15
Chicago, IL 60605
Articles

Scientists Say EHRs Can Help Identify High-Risk Pregnancy Patients

The use of electronic health records could help identify high-risk pregnancy patients who require treatment to avoid medical complications, according to an article published in the Johns Hopkins Public Health magazine, FierceEMR reports.

Researchers — assisted by Johns Hopkins University’s Center for Population Health IT — are conducting a pilot program that uses predictive modeling and natural language processing to sort through the text in EHRs of pregnant Medicaid beneficiaries.

The researchers are looking for information such as whether beneficiaries smoke or live in abusive environments. Those beneficiaries typically do not receive regular or follow-up care, according to FierceEMR.

After the EHR data identify the high-risk beneficiaries, the researchers can contact them about receiving needed care.