Identifying Novel Signatures of Pediatric chronic pain in Real-world Environments (INSPiRE)
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Abstract
One in four children experience chronic pain worldwide. Primary chronic pain is the most common type of chronic pain in childhood and is associated with negative impact on physical, psychological, and social functioning. Many children have mental health symptoms (e.g., anxiety, depression, insomnia) which impact on their pain experience and are associated with poor prognosis. Identification and treatment of pediatric chronic pain is unequal across groups distinguished by gender, race, ethnicity, language of care, insurance status, and disability status. To date, little is known about how chronic pain is identified and treated across the continuum of care (primary care to tertiary care) and how treatments can be prioritized to address complex mental health comorbidities.
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One in five children worldwide experience chronic primary pain (i.e., pain longer than 3 months without another underlying condition), with the most common types being musculoskeletal pain, abdominal pain, and headaches. Pediatric chronic pain is associated with significant functional impairment for 5 to 8% of children with pain symptoms, including poorer school attendance, reduced participation in daily activities, and increased risk of anxiety and depression. These early impacts have been shown persist into adulthood, as children with chronic pain have a higher likelihood of persistent pain, disability, and mental health challenges, highlighting the importance of early and effective intervention. Research documents the lower likelihood of receiving adequate pain care and higher burden of chronic pain in children from historically marginalized populations. With the advancements of machine learning and rule-based algorithms, This project aims to leverage the electronic health record (EHR) to phenotype children and identify those at greatest risk for poor outcomes and develop screening and treatment approaches.
Study Aims
- Create and validate an EHR-based computable phenotype of pediatric chronic primary pain.
- Identify disparities in receipt of effective pain care related to clinical (e.g., pain type, treatment history) and sociodemographic characteristics of children with chronic primary pain across the continuum of care.
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