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Transforming Medicine: Evidence-Driven mHealth
2015-09-30 - 2015-10-02    
8:00 am - 5:00 pm
September 30-October 2, 2015Digital Medicine 2015 Save the Date (PDF, 1.23 MB) Download the Scripps CME app to your smart phone and/or tablet for the conference [...]
Health 2.0 9th Annual Fall Conference
2015-10-04 - 2015-10-07    
All Day
October 4th - 7th, 2015 Join us for our 9th Annual Fall Conference, October 4-7th. Set over 3 1/2 days, the 9th Annual Fall Conference will [...]
2nd International Conference on Health Informatics and Technology
2015-10-05    
All Day
OMICS Group is one of leading scientific event organizer, conducting more than 100 Scientific Conferences around the world. It has about 30,000 editorial board members, [...]
MGMA 2015 Annual Conference
2015-10-11 - 2015-10-14    
All Day
In the business of care delivery®, you have to be ready for everything. As a valued member of your organization, you’re the person that others [...]
5th International Conference on Wireless Mobile Communication and Healthcare
2015-10-14 - 2015-10-16    
All Day
5th International Conference on Wireless Mobile Communication and Healthcare - "Transforming healthcare through innovations in mobile and wireless technologies" The fifth edition of MobiHealth proposes [...]
International Health and Wealth Conference
2015-10-15 - 2015-10-17    
All Day
The International Health and Wealth Conference (IHW) is one of the world's foremost events connecting Health and Wealth: the industries of healthcare, wellness, tourism, real [...]
Events on 2015-09-30
Events on 2015-10-04
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MGMA 2015 Annual Conference
11 Oct 15
Nashville
Events on 2015-10-15
Latest News Press Releases

A new digital tool may enhance early detection of childhood asthma

EMR Industry

Researchers Develop Enhanced Digital Tool for Early Childhood Asthma Detection Using EHR Data

A team from the Indiana University School of Medicine and the Regenstrief Institute has created a more accurate and cost-effective method for predicting childhood asthma using standard electronic health records (EHRs). This scalable approach could significantly improve early diagnosis and reduce the likelihood of asthma progression in young patients.

The researchers improved upon the existing Pediatric Asthma Risk Score by tailoring it to utilize EHR data, resulting in a new “passive digital marker.” This marker is derived from routinely collected medical history information and is designed to assess asthma risk in children without requiring additional input from clinicians. The study was led by Arthur Owora, PhD, MPH, associate professor of pediatrics at IU School of Medicine and research scientist at the Regenstrief Institute.

“Our goal is to integrate this passive digital marker into clinical settings to identify high-risk children earlier, enabling timely interventions that may enhance asthma control and lower the risk of hospitalization,” said Dr. Owora. “Ultimately, we aim to determine if early intervention can slow or prevent the progression to more severe asthma, which is often linked with increased healthcare demands and costs. This would benefit not only the children and their families but also physicians and the broader healthcare system.”

Dr. Owora collaborated with Dr. Benjamin Gaston, vice chair of translational research and the Billie Lou Wood Professor of Pediatrics, and Dr. Malaz Boustani, director of the Center for Health Innovation and Implementation Science, both from the IU School of Medicine.

“This tool is highly scalable because it leverages data already present in EHRs, requiring no additional time from clinical staff,” noted Dr. Boustani. “Such innovations in pediatrics offer tremendous potential to improve public health outcomes for future generations.”

The study analyzed data from nearly 70,000 children born between 2010 and 2017, sourced from the Indiana Network for Patient Care. Findings showed that the new passive digital marker outperformed the traditional Pediatric Asthma Risk Score in predicting asthma diagnoses between ages 4 and 11.

Dr. Owora emphasized that although clinicians are generally skilled at identifying asthma risk, the new tool can streamline the process by summarizing a patient’s medical history more efficiently. Earlier, more accurate predictions can lead to timely preventive actions—like minimizing exposure to asthma triggers, starting controller medications, or offering education and personalized treatment plans.

The research team’s next step is to conduct a randomized clinical trial to assess whether the tool increases early diagnosis rates among high-risk children and reduces the time from meeting diagnostic criteria to receiving an official diagnosis.

“If the trial proves successful, we hope to scale the implementation of this tool across the state and potentially nationwide to ensure more children benefit from early asthma detection,” said Dr. Owora.