Identifying Novel Signatures of Pediatric chronic pain in Real-world Environments (INSPiRE)


dc.contributorNational Institutes of Health
dc.contributor.authorPalermo, Tonya
dc.contributor.otherSeattle Children's Hospital
dc.date.accessioned2026-04-21T14:16:56Z
dc.descriptionOne 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 1. Create and validate an EHR-based computable phenotype of pediatric chronic primary pain. 2. 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.
dc.description.abstractOne 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.
dc.identifier.urihttps://hdl.handle.net/20.500.14642/1591
dc.language.isoen_US
dc.publisherPEDSnet
dc.rightsa CC-BY 4.0 Attribution license.
dc.rights.urihttps://creativecommons.org/licenses/by-sa/4.0/
dc.subjectFederally-Funded Research
dc.subjectFeasibility Query
dc.subjectPEDSnet Data Source
dc.subjectInvestigator-Led Study
dc.subjectObservational Study
dc.subjectNIH UC2
dc.subject.meshPediatrics
dc.subject.meshHealth Care Quality, Access, and Evaluation
dc.subject.meshPain
dc.subject.meshPain Measurement
dc.subject.meshPathological Conditions, Signs and Symptoms
dc.subject.meshChronic Pain
dc.subject.meshHealthcare Disparities
dc.titleIdentifying Novel Signatures of Pediatric chronic pain in Real-world Environments (INSPiRE)
dspace.entity.typeStudy
local.admin.notePM: Ellen McQuaid; Lauren Koenigsburg; DS: Advancing Patient Centered Assessment to Reduce Disparities in Pediatric Primary Chronic Pain across the Continuum of Care
local.contributor.grantRFA-AR-24-007
local.contributor.siteLeadPEDSnet Data Coordinating Center
local.contributor.siteSponsorSeattle Children's Hospital
local.contributor.sitesChildren's Hospital Colorado
local.contributor.sitesChildren's National Hospital
local.contributor.sitesChildren's Hospital of Philadelphia
local.contributor.sitesAnn & Robert H. Lurie Children's Hospital of Chicago
local.contributor.sitesNationwide Children's Hospital
local.contributor.sitesNemours Children's Health
local.contributor.sitesSeattle Children's Hospital
local.contributor.sitesTexas Children's Hospital
local.description.analyticsConceptually, the rule-based algorithm computable phenotype will be applied to patients in the full PEDSnet databas fulfill the following criteria: <br> **Inclusion Criteria:** 1) had ambulatory office encounter 2) aged 8 to 17.9 years old at the initial encounter 3) pain duration > 3 months **Exclusion Criteria:** 1) no diagnoses of health conditions associated with pain (e.g., cancer, inflammatory bowel disease, cerebral palsy, congenital malformations of the spinal cord, inflammatory polyarthropathies, pancreatitis).
local.identifier.pedsnetid2025.PALT.NIH.SCH
project.endDatePresent
project.startDate2025
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