Validation of ICDPIC software injury severity scores using a large regional trauma registry.
dc.contributor.author | Greene, Nathaniel H | |
dc.contributor.author | Kernic, Mary A | |
dc.contributor.author | Vavilala, Monica S | |
dc.contributor.author | Rivara, Frederick P | |
dc.coverage.spatial | England | |
dc.date.accessioned | 2015-05-26T19:00:11Z | |
dc.date.issued | 2015-10 | |
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.identifier | ||
dc.identifier | injuryprev-2014-041524 | |
dc.identifier.eissn | 1475-5785 | |
dc.identifier.uri | ||
dc.language | eng | |
dc.publisher | BMJ | |
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 | |
duke.contributor.orcid | Greene, Nathaniel H|0000-0003-0230-0499 | |
pubs.author-url | ||
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 |
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