Research

Solving the Puzzle

Problem
The origins of childhood and adult diseases often begin in pre- and early postnatal life.

Solution
Identify early risk factors in genes/biology, physical environment, behavioral needs, and socio-economic status to address disease before it manifests.

Impact
Develop preventative strategies, diagnostics and early therapies to promote health in child and adult populations.

The Children's Health & Discovery Initiative is using pediatric health and societal data to improve childhood and lifelong health in the following areas:

Goals:

  • Identify biological factors that contribute to life-long health and disease outcomes using ‘omics’ approaches
  • Develop interventions and therapies that can mitigate or prevent disease.

Strategic Opportunities:

  • Identify special populations in which to explore the association of early-life exposures on long-term health and disease
  • Link existing biospecimens to clinical datasets to leverage unique sample archives for biomarker discovery and validation.

Assisted reproductive technology and association with childhood cancer subtypes ​Gulrajani, N. B., Montes, S., McGough, D., Wimberly, C. E., Khattab, A., Semmes, E. C., Towry, L., Cohen, J. L., Hurst, J. H., Landi, D., Hill, S. N., & Walsh, K. M. (2023). Assisted reproductive technology and association with childhood cancer subtypes. Cancer medicine12(3), 3410–3418. https://doi.org/10.1002/cam4.5114​

Maternal Fc-mediated non-neutralizing antibody responses correlate with protection against congenital human cytomegalovirus infection​
Semmes, E. C., Miller, I. G., Wimberly, C. E., Phan, C. T., Jenks, J. A., Harnois, M. J., Berendam, S. J., Webster, H., Hurst, J. H., Kurtzberg, J., Fouda, G. G., Walsh, K. M., & Permar, S. R. (2022). Maternal Fc-mediated non-neutralizing antibody responses correlate with protection against congenital human cytomegalovirus infection. The Journal of clinical investigation, 132(16), e156827. https://doi.org/10.1172/JCI156827​

Accelerated epigenetic aging in newborns with Down syndrome​
Xu, K., Li, S., Muskens, I. S., Elliott, N., Myint, S. S., Pandey, P., Hansen, H. M., Morimoto, L. M., Kang, A. Y., Ma, X., Metayer, C., Mueller, B. A., Roberts, I., Walsh, K. M., Horvath, S., Wiemels, J. L., & de Smith, A. J. (2022). Accelerated epigenetic aging in newborns with Down syndrome. Aging cell21(7), e13652. https://doi.org/10.1111/acel.13652​)

Goals:

  • Assess how income, occupation, family/social support, community networks, and public policy influence child and community health. 
  • Inform systems-level strategies to improve equitable access to care and support systems for all children.

Strategic Opportunities:

  • Identify social and economic factors at the family and community level that influence short- and long-term child health outcomes.
  • Evaluate how organizations that provide support to children and families interact in order to optimize service provision.

Systematic review and meta-analysis of the effect of adverse childhood experiences (ACEs) on brain-derived neurotrophic factor (BDNF) levels​
Vyas, N., Wimberly, C. E., Beaman, M. M., Kaplan, S. J., Rasmussen, L. J. H., Wertz, J., Gifford, E. J., & Walsh, K. M. (2023). Systematic review and meta-analysis of the effect of adverse childhood experiences (ACEs) on brain-derived neurotrophic factor (BDNF) levels. Psychoneuroendocrinology151, 106071. Advance online publication. https://doi.org/10.1016/j.psyneuen.2023.106071​

Defining suspected child maltreatment using International Classification of Diseases codes: A scoping literature review ​
Liu, Y., Terrell, L., Joyce, B., Black, J., Kaplan, S. J., & Gifford, E. J. (2023). Defining suspected child maltreatment using International Classification of Diseases codes: A scoping literature review. Children and Youth Services Review, 106907. https://doi.org.10.1016/j.childyouth.2023.106907​

Do children evaluated for maltreatment have higher subsequent emergency department and inpatient care utilization compared to a general pediatric sample?  ​
Liu, Y., Shepherd-Banigan, M., Evans, K. E., Stilwell, L., Terrell, L., Hurst, J. H., & Gifford, E. J. (2022). Do children evaluated for maltreatment have higher subsequent emergency department and inpatient care utilization compared to a general pediatric sample?. Child abuse & neglect134, 105938. https://doi.org/10.1016/j.chiabu.2022.105938​

What Do Child Abuse and Neglect Medical Evaluation Consultation Notes Tell Researchers and Clinicians? ​
Golonka, M., Liu, Y., Rohrs, R., Copeland, J., Byrd, J., Stilwell, L., Crew, C., Kuehn, M., Snyder-Fickler, E., Hurst, J. H., Evans, K. E., Terrell, L., & Gifford, E. J. (2022). What Do Child Abuse and Neglect Medical Evaluation Consultation Notes Tell Researchers and Clinicians?. Child maltreatment, 10775595221134537. Advance online publication. https://doi.org/10.1177/10775595221134537​

Electronic Health Record Tools to Identify Child Maltreatment: Scoping Literature Review and Key Informant Interviews​
Stilwell, L., Golonka, M., Ankoma-Sey, K., Yancy, M., Kaplan, S., Terrell, L., & Gifford, E. J. (2022). Electronic Health Record Tools to Identify Child Maltreatment: Scoping Literature Review and Key Informant Interviews. Academic pediatrics22(5), 718–728. https://doi.org/10.1016/j.acap.2022.01.017​

Goals:

  • Provide analytic support for CHDI sponsored projects.
  • Develop data resources to support ongoing and future projects.
  • Promote data science research on children’s health.

Strategic Opportunities:

  • Develop new methods to characterize common child health conditions and events.
  • Link electronic health records data to other data resources in order to understand

Development of an electronic health records datamart to support clinical and population health research
Hurst, J. H., Liu, Y., Maxson, P. J., Permar, S. R., Boulware, L. E., & Goldstein, B. A. (2020). Development of an electronic health records datamart to support clinical and population health research. Journal of clinical and translational science5(1), e13. https://doi.org/10.1017/cts.2020.499

Combining adult with pediatric patient data to develop a clinical decision support tool intended for children: leveraging machine learning to model heterogeneity
Sabharwal, P., Hurst, J. H., Tejwani, R., Hobbs, K. T., Routh, J. C., & Goldstein, B. A. (2022). Combining adult with pediatric patient data to develop a clinical decision support tool intended for children: leveraging machine learning to model heterogeneity. BMC medical informatics and decision making22(1), 84. https://doi.org/10.1186/s12911-022-01827-4

Using Electronic Health Records to understand the population of local children captured in a large health system in Durham County, NC, USA, and implications for population health research
Stolte, A., Merli, M. G., Hurst, J. H., Liu, Y., Wood, C. T., & Goldstein, B. A. (2022). Using Electronic Health Records to understand the population of local children captured in a large health system in Durham County, NC, USA, and implications for population health research. Social science & medicine (1982)296, 114759. https://doi.org/10.1016/j.socscimed.2022.114759

Well-Child Care Attendance and Risk of Asthma Exacerbations
Lang, J. E., Tang, M., Zhao, C., Hurst, J., Wu, A., & Goldstein, B. A. (2020). Well-Child Care Attendance and Risk of Asthma Exacerbations. Pediatrics146(6), e20201023. https://doi.org/10.1542/peds.2020-1023

Environmental and clinical data utility in pediatric asthma exacerbation risk prediction models
Hurst, J. H., Zhao, C., Hostetler, H. P., Ghiasi Gorveh, M., Lang, J. E., & Goldstein, B. A. (2022). Environmental and clinical data utility in pediatric asthma exacerbation risk prediction models. BMC medical informatics and decision making22(1), 108. https://doi.org/10.1186/s12911-022-01847-0

Goals:

  • Identify and support research on environmental factors that contribute to life-long health and disease outcomes in children.
  • Develop interventions and recommendations that can help mitigate exposures and improve population health.

Strategic Opportunities:

  • Develop methods to capture individual exposome measures
  • Develop new approaches to address big data challenges in environmental health
  • Identify methods to reduce exposure to harmful environmental factors and mitigate health impacts
  • Contribute to policies to promote child health.

Goals:

  • Evaluate the impact of learning, behavior, healthcare access, and health behaviors on physical and mental well-being. 
  • Identify areas of inequitable access to care and determine how to modify healthcare provision to improve service provision.

Strategic Opportunities:

  • Understand how health behaviors in early life influence long-term health and well-being.
  • Develop new strategies and care models to improve access to healthcare.

Featured Research Projects

Project HOPE 1000 – an observational study of mother-infant health during the first 1000 days of life. In collaboration with the Department of Obstetrics and Gynecology, CHDI is developing a cohort of 1000 mother-infant dyads, which will provide a collection of birth samples and be studied long-term — from pregnancy through early childhood — to help identify early life factors that influence lifelong health and disease. Study enrollment began in November 2018. Project HOPE 1000 serves as a backbone protocol that can support additional research initiatives.

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Duke Clinical Research Datamart – The CHDI partnered with Duke Health Technology Solutions (DHTS) and the Duke Clinical and Translational Sciences Institute to build a curated electronic health records datamart, which provides a subset of consistently defined data elements used to investigate patient intrinsic and extrinsic factors that affect the health and well-being of individuals served by Duke University Health System. The CRDM is currently in use for over 50 projects across Duke University.

Duke Biospecimens from Respiratory Virus-Exposed Kids (BRAVE Kids) – Duke BRAVE Kids is an ongoing observational cohort study of over 500 infants, children, adolescents, and young adults exposed to or infected with SARS-CoV-2, the etiological agent of COVID-19. The study collects data and biospecimens, including nasopharyngeal swabs, blood, saliva, and stool, and is conducted through a combination of in-home study visits and research clinic visits at the Duke Pickett Road site. 

CHDI-CTSI Child Health Equity Program – The goal of this program is to identify and develop strategies to mitigate disparities and inequities in child health outcomes and healthcare access through the coordinated efforts of Duke investigators, DUHS providers, patients and families, and community partners. Further, this program will build research capacity for health equity research and improve access to and quality of care.

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Child Maltreatment Prevention Lab – A partnership between the Department of Pediatrics Child Abuse and Neglect Medical Evaluation Clinic (CANMEC), the Center for Child and Family Policy, and the Durham Social Services, the Child Maltreatment Prevention Lab leverages administrative and health records data to identify family- and community-level factors associated with suspected child maltreatment cases.

North Carolina Integrated Care for Kids  – The NC Integrated Care for Kids (NC InCK) is a Centers for Medicaid and Medicare Services (CMS) model that is serving children in 5 central North Carolina counties (Alamance, Durham, Granville, Orange, and Vance) who are insured by Medicaid or CHIP (NC Health Choice) from birth up through age 20. A coalition of families and children in our NC InCK counties, Duke University, University of North Carolina at Chapel Hill (UNC), NC DHHS, and community partners are leading the model work. Development of the North Carolina Integrated Care for Kids Program is helping to identify new ways to efficiently coordinate care, reduce healthcare costs, and improve health outcomes for children in central North Carolina. CHDI led the development of the CMS application and is providing administrative and project management support for the model.

Linkage of Early Life Biospecimens to the Electronic Health Record – The Carolinas Cord Blood Bank (CCBB), led by Joanne Kurtzberg, MD (Pediatrics), has over 40,000 mother-infant cord blood donors, a significant proportion of whom were enrolled in the Duke University Health System. The CHDI has linked Duke CCBB donors to their electronic health records (EHRs), thereby establishing a unique cohort of patients with well-documented long-term health records and perinatal biospecimens.

Path4CNC – Children’s Complex Care Coalition of North Carolina Stakeholder Convenings - a series of convenings held January-March 2021, led by representatives from Duke Children’s, UNC Health Children’s, CHDI, Legal Aid of North Carolina, North Carolina Integrated Care for Kids, and sponsored by the National Center for Complex Health & Social Needs. The goal of these stakeholder convenings was to engage state and local agencies, health professionals, community organizations, and families of children with complex health needs (CCHN) to identify challenges and strengths in current systems of care and generate actionable recommendations for systems improvement to address the needs and priorities of CCHN, their families, and care providers.

CHDI-CTSI Child Health Equity Programs  – In partnership with Duke’s Clinical and Translational Sciences Institute, Duke investigators, and community partners this program identifies and develops strategies to mitigate disparities and inequities in child healthy outcomes and healthcare access.

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