The use of computer decision support for pediatric obstructive sleep apnea detection in primary care

Sarah M. Honaker, Ashley Street, Ameet S. Daftary, Stephen M. Downs

Research output: Contribution to journalArticle

Abstract

Study Objectives: To (1) describe outcomes from a computer decision support system (CDSS) for pediatric obstructive sleep apnea (OSA) detection in primary care; and (2) identity the prevalence of children meeting criteria for an OSA referral. Methods: A CDSS for OSA was implemented in two urban primary care clinics. Parents of children (age 2 to 11 years) presenting to the clinic were asked if their child snored regularly, with a positive response resulting in six additional OSA screening items. Primary care providers (PCPs) received a prompt for all snoring children, listing applicable OSA signs and symptoms and recommending further evaluation and referral for OSA. Results: A total of 2,535 children were screened for snoring, identifying 475 snoring children (18.7%). Among snoring children, PCPs referred 40 (15.4%) for further evaluation. The prevalence of additional OSA signs and symptoms ranged from 3.5% for underweight to 43.7% for overweight. A total of 74.7% of snoring children had at least one additional sign or symptom and thus met American Academy of Pediatrics guidelines criteria for an OSA referral. Conclusions: A CDSS can be used to support PCPs in identifying children at risk for OSA. Most snoring children met criteria for further evaluation. It will be important to further evaluate this referral threshold as well as the readiness of the sleep medicine field to meet this need.

Original languageEnglish (US)
Pages (from-to)453-462
Number of pages10
JournalJournal of Clinical Sleep Medicine
Volume15
Issue number3
DOIs
StatePublished - 2019

Keywords

  • Computer decision support
  • Obstructive sleep apnea
  • Pediatrics
  • Primary care
  • Sleep disorders
  • Snoring

ASJC Scopus subject areas

  • Pulmonary and Respiratory Medicine
  • Neurology
  • Clinical Neurology

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