Events Calendar

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12:00 AM - PFF Summit 2015
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NextEdge Health Experience Summit
2015-11-03 - 2015-11-04    
All Day
With a remarkable array of speakers and panelists, the Next Edge: Health Experience Summit is shaping-up to be an event that attracts healthcare professionals who [...]
mHealthSummit 2015
2015-11-08 - 2015-11-11    
All Day
Anytime, Anywhere: Engaging Patients and ProvidersThe 7th annual mHealth Summit, which is now part of the HIMSS Connected Health Conference, puts new emphasis on innovation [...]
24th Annual Healthcare Conference
2015-11-09 - 2015-11-11    
All Day
The Credit Suisse Healthcare team is delighted to invite you to the 2015 Healthcare Conference that takes place November 9th-11th in Arizona. We have over [...]
PFF Summit 2015
2015-11-12 - 2015-11-14    
All Day
PFF Summit 2015 will be held at the JW Marriott in Washington, DC. Presented by Pulmonary Fibrosis Foundation Visit the www.pffsummit.org website often for all [...]
2nd International Conference on Gynecology & Obstetrics
2015-11-16 - 2015-11-18    
All Day
Welcome Message OMICS Group is esteemed to invite you to join the 2nd International conference on Gynecology and Obstetrics which will be held from November [...]
Events on 2015-11-03
NextEdge Health Experience Summit
3 Nov 15
Philadelphia
Events on 2015-11-08
mHealthSummit 2015
8 Nov 15
National Harbor
Events on 2015-11-09
Events on 2015-11-12
PFF Summit 2015
12 Nov 15
Washington, DC
Events on 2015-11-16
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.