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Inj Prev. 2015 Oct;21(5):325-30. doi: 10.1136/injuryprev-2014-041524. Epub 2015 May 18.

Validation of ICDPIC software injury severity scores using a large regional trauma registry.

Author information

1
Department of Anesthesiology and Pediatrics, School of Medicine, Duke University, Durham, North Carolina, USA.
2
Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington, USA.
3
Department of Anesthesiology and Pain Medicine, School of Medicine, University of Washington, Seattle, Washington, USA Department of Pediatrics, School of Medicine, University of Washington, Seattle, Washington, USA Harborview Injury Prevention and Research Center, Harborview Medical Center, Seattle, Washington, USA.
4
Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington, USA Department of Pediatrics, School of Medicine, University of Washington, Seattle, Washington, USA Harborview Injury Prevention and Research Center, Harborview Medical Center, Seattle, Washington, USA.

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.

KEYWORDS:

Injury Diagnosis

PMID:
25985974
DOI:
10.1136/injuryprev-2014-041524
[Indexed for MEDLINE]

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