Validation of ICDPIC software injury severity scores using a large regional trauma registry.
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.
Type
Journal articleSubject
Injury DiagnosisAbbreviated Injury Scale
Area Under Curve
Female
Forms and Records Control
Humans
Injury Severity Score
International Classification of Diseases
Male
Outcome Assessment (Health Care)
Quality Improvement
Registries
Retrospective Studies
Software
Wounds and Injuries
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https://hdl.handle.net/10161/10182Published Version (Please cite this version)
10.1136/injuryprev-2014-041524Publication Info
Greene, Nathaniel H; Kernic, Mary A; Vavilala, Monica S; & Rivara, Frederick P (2015). Validation of ICDPIC software injury severity scores using a large regional trauma
registry. Inj Prev, 21(5). pp. 325-330. 10.1136/injuryprev-2014-041524. Retrieved from https://hdl.handle.net/10161/10182.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Nathaniel Howard Greene
Assistant Professor of Anesthesiology

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