Pediatric decision support using adapted Arden Syntax

Vibha Anand, Aaron E. Carroll, Paul G. Biondich, Tamara M. Dugan, Stephen M. Downs

Research output: Contribution to journalArticle

15 Scopus citations


Background: Pediatric guidelines based care is often overlooked because of the constraints of a typical office visit and the sheer number of guidelines that may exist for a patient's visit. In response to this problem, in 2004 we developed a pediatric computer based clinical decision support system using Arden Syntax medical logic modules (MLM). Methods: The Child Health Improvement through Computer Automation system (CHICA) screens patient families in the waiting room and alerts the physician in the exam room. Here we describe adaptation of Arden Syntax to support production and consumption of patient specific tailored documents for every clinical encounter in CHICA and describe the experiments that demonstrate the effectiveness of this system. Results: As of this writing CHICA has served over 44,000 patients at 7 pediatric clinics in our healthcare system in the last decade and its MLMs have been fired 6182,700 times in “produce” and 5334,021 times in “consume” mode. It has run continuously for over 10 years and has been used by 755 physicians, residents, fellows, nurse practitioners, nurses and clinical staff. There are 429 MLMs implemented in CHICA, using the Arden Syntax standard. Studies of CHICA's effectiveness include several published randomized controlled trials. Conclusions: Our results show that the Arden Syntax standard provided us with an effective way to represent pediatric guidelines for use in routine care. We only required minor modifications to the standard to support our clinical workflow. Additionally, Arden Syntax implementation in CHICA facilitated the study of many pediatric guidelines in real clinical environments.

Original languageEnglish (US)
Pages (from-to)15-23
Number of pages9
JournalArtificial Intelligence in Medicine
StatePublished - Nov 2018


  • Arden Syntax
  • Clinical decision support

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Artificial Intelligence

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