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

dc.contributor.author Greene, Nathaniel Howard
dc.contributor.author Kernic, MA
dc.contributor.author Rivara, FP
dc.contributor.author Vavilala, MS
dc.coverage.spatial England
dc.date.accessioned 2015-05-26T19:00:11Z
dc.date.issued 2015-10
dc.identifier http://www.ncbi.nlm.nih.gov/pubmed/25985974
dc.identifier injuryprev-2014-041524
dc.identifier.uri http://hdl.handle.net/10161/10182
dc.description.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.
dc.language eng
dc.relation.ispartof Inj Prev
dc.relation.isversionof 10.1136/injuryprev-2014-041524
dc.subject Injury Diagnosis
dc.subject Abbreviated Injury Scale
dc.subject Area Under Curve
dc.subject Female
dc.subject Forms and Records Control
dc.subject Humans
dc.subject Injury Severity Score
dc.subject International Classification of Diseases
dc.subject Male
dc.subject Outcome Assessment (Health Care)
dc.subject Quality Improvement
dc.subject Registries
dc.subject Retrospective Studies
dc.subject Software
dc.subject Wounds and Injuries
dc.title Validation of ICDPIC software injury severity scores using a large regional trauma registry.
dc.type Journal article
pubs.author-url http://www.ncbi.nlm.nih.gov/pubmed/25985974
pubs.begin-page 325
pubs.end-page 330
pubs.issue 5
pubs.organisational-group Anesthesiology
pubs.organisational-group Anesthesiology, Pediatrics
pubs.organisational-group Clinical Science Departments
pubs.organisational-group Duke
pubs.organisational-group School of Medicine
pubs.publication-status Published
pubs.volume 21
dc.identifier.eissn 1475-5785


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