Nicholas P Giangreco1, Sulieman Lina2, Jun Qian2, Aymone Kuoame3, Vignesh Subbian4, Eric Boerwinkle5, Mine Cicek6, Cheryl R Clark7, Elizabeth Cohen8, Kelly A Gebo9, Roxana Loperena-Cortes3, Kelsey Mayo3, Stephen Mockrin10, Lucila Ohno-Machado11, Sheri D Schully10, Nicholas P Tatonetti1, Andrea H Ramirez10. 1. Department of Biomedical Informatics, Columbia University, New York, New York, USA. 2. Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA. 3. Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA. 4. Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona, USA. 5. School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA. 6. Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA. 7. Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA. 8. Hunter-Bellevue School of Nursing, Hunter College City University of New York, New York, New York, USA. 9. Bloomberg School of Public Health, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. 10. All of Us Research Program, National Institutes of Health, Bethesda, Maryland, USA. 11. Department of Biomedical Informatics, UCSD Health, La Jolla, California, USA.
Abstract
OBJECTIVE: To describe and demonstrate use of pediatric data collected by the All of Us Research Program. MATERIALS AND METHODS: All of Us participant physical measurements and electronic health record (EHR) data were analyzed including investigation of trends in childhood obesity and correlation with adult body mass index (BMI). RESULTS: We identified 19 729 participants with legacy pediatric EHR data including diagnoses, prescriptions, visits, procedures, and measurements gathered since 1980. We found an increase in pediatric obesity diagnosis over time that correlates with BMI measurements recorded in participants' adult EHRs and those physical measurements taken at enrollment in the research program. DISCUSSION: We highlight the availability of retrospective pediatric EHR data for nearly 20 000 All of Us participants. These data are relevant to current issues such as the rise in pediatric obesity. CONCLUSION: All of Us contains a rich resource of retrospective pediatric EHR data to accelerate pediatric research studies. Published by Oxford University Press on behalf of the American Medical Informatics Association 2021. This work is written by a US Government employee and is in the public domain in the US.
OBJECTIVE: To describe and demonstrate use of pediatric data collected by the All of Us Research Program. MATERIALS AND METHODS: All of Us participant physical measurements and electronic health record (EHR) data were analyzed including investigation of trends in childhood obesity and correlation with adult body mass index (BMI). RESULTS: We identified 19 729 participants with legacy pediatric EHR data including diagnoses, prescriptions, visits, procedures, and measurements gathered since 1980. We found an increase in pediatric obesity diagnosis over time that correlates with BMI measurements recorded in participants' adult EHRs and those physical measurements taken at enrollment in the research program. DISCUSSION: We highlight the availability of retrospective pediatric EHR data for nearly 20 000 All of Us participants. These data are relevant to current issues such as the rise in pediatric obesity. CONCLUSION: All of Us contains a rich resource of retrospective pediatric EHR data to accelerate pediatric research studies. Published by Oxford University Press on behalf of the American Medical Informatics Association 2021. This work is written by a US Government employee and is in the public domain in the US.
Entities:
Keywords:
electronic health records; medical informatics; pediatrics; public health informatics; retrospective studies
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