Article Text

other Versions

PDF
Validation of ICDPIC software injury severity scores using a large regional trauma registry
  1. Nathaniel H Greene1,
  2. Mary A Kernic2,
  3. Monica S Vavilala3,4,5,
  4. Frederick P Rivara2,4,5
  1. 1Department of Anesthesiology and Pediatrics, School of Medicine, Duke University, Durham, North Carolina, USA
  2. 2Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington, USA
  3. 3Department of Anesthesiology and Pain Medicine, School of Medicine, University of Washington, Seattle, Washington, USA
  4. 4Department of Pediatrics, School of Medicine, University of Washington, Seattle, Washington, USA
  5. 5Harborview Injury Prevention and Research Center, Harborview Medical Center, Seattle, Washington, USA
  1. Correspondence to Dr Nathaniel H Greene, Department of Anesthesiology and Pediatrics, School of Medicine, Duke University, MD, DUMC Box 3094, Durham, NC 27710, USA; nathaniel.greene{at}dm.duke.edu

Abstract

Background Administrative or quality improvement registries may or may not contain the elements needed for investigations by trauma researchers. International Classification of Diseases Program for Injury Categorisation (ICDPIC), a statistical program available through Stata, is a powerful tool that can extract injury severity scores from ICD-9-CM codes. We conducted a validation study for use of the ICDPIC in trauma research.

Methods We conducted a retrospective cohort validation study of 40 418 patients with injury using a large regional trauma registry. ICDPIC-generated AIS scores for each body region were compared with trauma registry AIS scores (gold standard) in adult and paediatric populations. A separate analysis was conducted among patients with traumatic brain injury (TBI) comparing the ICDPIC tool with ICD-9-CM embedded severity codes. Performance in characterising overall injury severity, by the ISS, was also assessed.

Results The ICDPIC tool generated substantial correlations in thoracic and abdominal trauma (weighted κ 0.87–0.92), and in head and neck trauma (weighted κ 0.76–0.83). The ICDPIC tool captured TBI severity better than ICD-9-CM code embedded severity and offered the advantage of generating a severity value for every patient (rather than having missing data). Its ability to produce an accurate severity score was consistent within each body region as well as overall.

Conclusions The ICDPIC tool performs well in classifying injury severity and is superior to ICD-9-CM embedded severity for TBI. Use of ICDPIC demonstrates substantial efficiency and may be a preferred tool in determining injury severity for large trauma datasets, provided researchers understand its limitations and take caution when examining smaller trauma datasets.

  • Injury Diagnosis
View Full Text

Statistics from Altmetric.com

Request permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.