Electronic health records can help identify high risk pregnancy patients so that they can receive treatment before suffering medical complications, according to a new article published in Johns Hopkins Public Health.
In a pilot program assisted by Johns Hopkins' new Center for Population Health IT, researchers are using predictive modeling and natural language processing to cull useful information from the free text in EHRs of pregnant patients on Medicaid, such as whether the patients are smokers or live in abusive environments. Since many of those patients typically don't receive regular or follow-up care, they're viewed as "missing." Once the EHR identifies which ones may need additional treatment, the researchers know to reach out and contact them so that they can receive needed care.
The center is also using EHRs with Maryland's health information organization to flag patients at higher risk for rehospitalization, and is working with health plans' electronic data to better treat members with chronic diseases. Center officials eventually plan to use EHRs across populations to improve patient health on a wider scale.
Says Jonathan Weiner, professor of health policy and management and founder of the center, "Making sure that all this helps to improve the public's health ... that's our vision."
Studies have shown that EHRs can not only improve direct patient care, but also can be helpful for secondary uses such as research and quality management.
To learn more:
- read the article