Developing a diagnosis-based severity classification system for use in emergency medical services for children

Acad Emerg Med. 2012 Jan;19(1):70-8. doi: 10.1111/j.1553-2712.2011.01250.x.

Abstract

Objectives: Lack of adequate risk adjustment methodologies has hindered the progress of emergency medicine health services research. The authors hypothesized that a consensus-derived, diagnosis-based severity classification system (SCS) would be significantly associated with actual measures of emergency department (ED) resource use and could ultimately be used to examine severity-adjusted outcomes across patient populations.

Methods: A panel of subject matter experts used consensus methods to assign severity scores (1 = lowest severity to 5 = highest severity) to 3,041 ED International Classifications of Diseases (ICD), 9th revision, diagnosis codes. SCS scores were assigned to ED visits using the visit diagnosis code with the highest severity. We tested the association between the SCS scores and measures of ED resource use in three data sets: the Pediatric Emergency Care Applied Research Network Core Data Project (PCDP), the National Hospital Ambulatory Medical Care Survey (NHAMCS), and the Connecticut state ED data set.

Results: There was a significant association between the five-level SCS and all six measures of resource use: triage category, disposition, ED resource use, Current Procedural Terminology Evaluation and Management (CPT E&M) codes, ED length of stay, and ED charges within the three ED data sets.

Conclusions: The SCS demonstrates validity in its strong association with actual ED resource use. The use of readily available ICD-9 diagnosis codes makes the SCS useful as a risk adjustment tool for health services research.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adolescent
  • Chi-Square Distribution
  • Child
  • Current Procedural Terminology
  • Delphi Technique
  • Emergency Service, Hospital / statistics & numerical data*
  • Female
  • Health Services Research
  • Humans
  • International Classification of Diseases / statistics & numerical data*
  • Male
  • Severity of Illness Index*
  • Triage