Promoting universal screening and early identification of child adhd via integrated automatic EHR supports in primary care
Ended Project Grant Awarded Last action
- Award ID
- R21MH128585
- Recipient
-
The Johns Hopkins University UEI FTMTDMBR29C7
- Awarding agency
-
National Institute of Mental Health
National Institutes of Health, Department of Health and Human Services
- Obligated
- $925,228
Award facts
- Assistance listing
- 93.242 Mental Health Research Grants
- Completion date
- Originally
- Place of performance
- Maryland, USA
Award details come from USAspending.gov.
Description
- Abstract
- Adhd is among the most common behavioral health conditions presented in pediatric primary care. When left untreated, adhd is associated with negative consequences including suicide, criminal behavior, and serious substance use. The american academy of pediatrics recommends screening for adhd in primary care for children ages 4-18. Unfortunately, compliance with practice guidelines and real-world implementation of behavioral health screening is highly variable. Even with universal behavioral health screening infrastructure in place, screening rates can remain below 50%. Developing an electronic health record (EHR) algorithm to identify children at risk for adhd has the potential to realize universal screening and facilitate early identification and linkage to care. The proposed project will: 1) describe disparities in the frequency of adhd screening, diagnosis, and healthcare utilization for children with adhd, 2) develop an algorithm to predict adhd phenotypes earlier than the typical age of diagnosis using EHR structured and text data, and 3) collaborate with stakeholders to develop an implementation roadmap for the phenotyping algorithm in pediatric primary care. Researchers have successfully applied natural language processing (NLP) techniques to EHR data to identify patients with behavioral health conditions, including suicidal behaviors, autism, and bipolar disorder, but NLP has not been applied to the identification of adhd. The resulting phenotyping algorithm holds potential to be integrated into EHR in pediatric primary care to automatically flag children at risk for adhd in real-time to trigger closer monitoring, reduce disparities in screening and diagnosis, and initiate earlier treatment. The resulting phenotyping algorithm and implementation roadmap will set the stage for a R01 trial to evaluate the clinical utility of an automated EHR phenotyping algorithm in pediatric primary care.
Transactions
| Action | Obligated | Date |
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| Amendment | $0 | |
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| Amendment | -$250,122 | |
| Amendment | $250,122 | |
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| Amendment | $212,492 | |
| Amendment | $212,492 | |
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| Amendment | $0 | |
| Amendment | $250,122 | |
| Original award | $250,122 |
Show all 16
Subawards
| Subrecipient | Amount | Awarded |
|---|---|---|
| Universite Concordia | $59,791 |
Quick answers
Who received award R21MH128585?
R21MH128585 was awarded to The Johns Hopkins University by National Institute of Mental Health (National Institutes of Health) on August 1, 2022.
How much is award R21MH128585 worth?
$925,228 has been obligated on R21MH128585.
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