Events Calendar

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12:00 AM - DEVICE TALKS
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DEVICE TALKS
DEVICE TALKS BOSTON 2018: BIGGER AND BETTER THAN EVER! Join us Oct. 8-10 for the 7th annual DeviceTalks Boston, back in the city where it [...]
6th Annual HealthIMPACT Midwest
2018-10-10    
All Day
REV1 VENTURES COLUMBUS, OH The Provider-Patient Experience Summit - Disrupting Delivery without Disrupting Care HealthIMPACT Midwest is focused on technologies impacting clinician satisfaction and performance. [...]
15 Oct
2018-10-15 - 2018-10-16    
All Day
Conference Series Ltd invites all the participants from all over the world to attend “3rd International Conference on Environmental Health” during October 15-16, 2018 in Warsaw, Poland which includes prompt keynote [...]
17 Oct
2018-10-17 - 2018-10-19    
7:00 am - 6:00 pm
BALANCING TECHNOLOGY AND THE HUMAN ELEMENT In an era when digital technologies enable individuals to track health statistics such as daily activity and vital signs, [...]
Epigenetics Congress 2018
2018-10-25 - 2018-10-26    
All Day
Conference: 5th World Congress on Epigenetics and Chromosome Date: October 25-26, 2018 Place: Istanbul, Turkey Email: epigeneticscongress@gmail.com About Conference: Epigenetics congress 2018 invites all the [...]
Events on 2018-10-08
DEVICE TALKS
8 Oct 18
425 Summer Street
Events on 2018-10-10
Events on 2018-10-17
17 Oct
Events on 2018-10-25
Epigenetics Congress 2018
25 Oct 18
Istanbul
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.