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1.
Inj Prev ; 26(4): 330-333, 2020 08.
Artigo em Inglês | MEDLINE | ID: mdl-31300467

RESUMO

BACKGROUND: The study objective was to compare the ISS manually assigned by hospital personnel and those generated by the ICDPIC software for value agreement and predictive power of length of stay (LOS) and mortality. METHODS: We used data from the 2010-2016 trauma registry of a paediatric trauma centre (PTC) and 2014 National Trauma Data Bank (NTDB) hospitals that reported manually coded ISS. Agreement analysis was performed between manually and computer assigned ISS with severity groupings of 1-8, 9-15, 16-25 and 25-75. The prediction of LOS was compared using coefficients of determination (R2) from linear regression models. Mortality predictive power was compared using receiver operating characteristic (ROC) curves from logistic regression models. RESULTS: The proportion of agreement between manually and computer assigned ISS in PTC data was 0.84 and for NTDB was 0.75. Analysing predictive power for LOS in the PTC sample, the R2=0.19 for manually assigned scores, and the R2=0.15 for computer assigned scores (p=0.0009). The areas under the ROC curve indicated a mortality predictive power of 0.95 for manually assigned scores and 0.86 for computer assigned scores in the PTC data (p=0.0011). CONCLUSIONS: Manually and computer assigned ISS had strong comparative agreement for minor injuries but did not correlate well for critical injuries (ISS=25-75). The LOS and mortality predictive power were significantly higher for manually assigned ISS when compared with computer assigned ISS in both PTC and NTDB data sets. Thus, hospitals should be cautious about transitioning to computer assigned ISS, specifically for patients who are critically injured.


Assuntos
Centros de Traumatologia , Ferimentos e Lesões , Criança , Computadores , Humanos , Escala de Gravidade do Ferimento , Modelos Logísticos , Valor Preditivo dos Testes , Curva ROC
2.
Clin Pediatr (Phila) ; 56(9): 845-853, 2017 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-28516800

RESUMO

Although trauma undertriage has been widely discussed in the literature, undertriage in the pediatric trauma population remains understudied. Using the 2009-2013 Nationwide Emergency Department Sample, we assessed the national undertriage rate in pediatric major trauma patients (age ≤16 years and injury severity score [ISS] >15), and identified factors associated with pediatric trauma undertriage. Nationally, 21.7% of pediatric major trauma patients were undertriaged. Children living in rural areas were more likely to be undertriaged ( P = .02), as were those without insurance ( P = .00). Children with life-threatening injuries were less likely to be undertriaged ( P < .0001), as were those with chronic conditions ( P < .0001). Improving access to specialized pediatric trauma care through innovative service delivery models may reduce undertriage and improve outcomes for pediatric major trauma patients.


Assuntos
Triagem/estatística & dados numéricos , Ferimentos e Lesões/epidemiologia , Ferimentos e Lesões/terapia , Adolescente , Distribuição por Idade , Criança , Pré-Escolar , Doença Crônica , Bases de Dados Factuais/estatística & dados numéricos , Serviço Hospitalar de Emergência/estatística & dados numéricos , Feminino , Humanos , Lactente , Escala de Gravidade do Ferimento , Masculino , Pessoas sem Cobertura de Seguro de Saúde/estatística & dados numéricos , População Rural/estatística & dados numéricos , Centros de Traumatologia/estatística & dados numéricos , Estados Unidos/epidemiologia , População Urbana/estatística & dados numéricos
3.
Am J Emerg Med ; 33(9): 1158-65, 2015 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-26066772

RESUMO

BACKGROUND: Prior studies of undertriage have not made comparisons across multiple trauma levels. METHODS: Emergency department data was extracted from the Nationwide Emergency Department Sample for major trauma patients. We considered patients with moderate injuries (Injury Severity Score, ISS=16-24) and severe injuries (ISS=25-75) separately. Conditional logistic regression modeling was used to compare the odds of ED mortality for level I trauma centers (TC I) vs. nontrauma centers (NTC) and level II trauma centers (TC II) vs. NTC. An innovative 1:1:1 optimal matching (an extension of the traditional pair matching) was used to balance patient characteristics in three groups. To facilitate matching of all NTC patients, 3 subgroups were developed for ISS=16-24 and 2 subgroups for ISS=25-75. Sensitivity analyses were performed to assess the strength of the association between trauma center designation and ED mortality. RESULTS: For ISS=16-24, 2 of 3 subgroups had marginally significant reduced odds of ED mortality when properly triaged (TC I vs. NTC [T1:OR=0.63; 95%CI: 0.45 - 0.89, T2:OR=0.71;95%CI:0.51-0.99]). For ISS=25-75, both subgroups had significantly reduced odds of emergency department mortality when properly triaged (H1: TC I vs. NTC [OR=0.61; 95%CI: 0.50-0.74]; TC II vs. NTC [OR=0.49; 95%CI: 0.38 - 0.63]; H2: TC I vs. NTC [OR=0.50; 95%CI: 0.41 - 0.60]; TC II vs. NTC [OR=0.42; 95%CI: 0.33 - 0.53]). Conclusions for ISS 25-75 were robust to a hypothesized unobserved confounding variable as shown in sensitivity analysis. CONCLUSIONS: Trauma patients with ISS≥25 received most benefit from proper triage. Efforts to reduce undertriage should focus on this population.


Assuntos
Serviço Hospitalar de Emergência , Centros de Traumatologia , Triagem , Ferimentos e Lesões/mortalidade , Adolescente , Adulto , Feminino , Humanos , Escala de Gravidade do Ferimento , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Fatores de Risco , Estados Unidos/epidemiologia , Adulto Jovem
4.
Brain Inj ; 28(4): 431-7, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-24564802

RESUMO

OBJECTIVE: To evaluate the definition of traumatic brain injury (TBI) in the National Electronic Injury Surveillance System (NEISS) and compare TBI case ascertainment using NEISS vs. ICD-9-CM diagnosis coding. METHODS: Two data samples from a NEISS participating emergency department (ED) in 2008 were compared: (1) NEISS records meeting the recommended NEISS TBI definition and (2) Hospital ED records meeting the ICD-9-CM CDC recommended TBI definition. The sensitivity and positive predictive value were calculated for the NEISS definition using the ICD-9-CM definition as the gold standard. Further analyses were performed to describe cases characterized as TBIs in both datasets and to determine why some cases were not classified as TBIs in both datasets. RESULTS: There were 1834 TBI cases captured by the NEISS and 1836 TBI cases captured by the ICD-9-CM coded ED record, but only 1542 were eligible for inclusion in NEISS. There were 1403 cases classified as TBIs by both the NEISS and ICD-9-CM diagnosis codes. The NEISS TBI definition had a sensitivity of 91.0% (95% CI = 89.6-92.4%) and positive predictive value of 76.5% (95% CI = 74.6-78.4%). CONCLUSIONS: Using the NEISS TBI definition presented in this paper would standardize and improve the accuracy of TBI research using the NEISS.


Assuntos
Lesões Encefálicas/classificação , Serviço Hospitalar de Emergência/estatística & dados numéricos , Hospitalização/estatística & dados numéricos , Classificação Internacional de Doenças , Sistema de Registros , Adolescente , Lesões Encefálicas/epidemiologia , Criança , Pré-Escolar , Reações Falso-Negativas , Reações Falso-Positivas , Feminino , Humanos , Lactente , Modelos Logísticos , Masculino , Vigilância da População , Sensibilidade e Especificidade , Estados Unidos
5.
Clin Pediatr (Phila) ; 43(4): 335-42, 2004 May.
Artigo em Inglês | MEDLINE | ID: mdl-15118776

RESUMO

Ninety-six children were admitted during a 9-year period to a pediatric level 1 trauma center for treatment of farm-related injuries. The age range was from 6 weeks to 17 years (median, 7.5 years; mean, 7.6 years; standard deviation, 4.4). Thirty-nine patients (40.6%) had an animal-related injury, including 36 children (37.5%) who had an injury associated with a horse. Amish children had an increased risk of horse-related injury when compared with non-Amish children (p=0.04; RR=2.09, 95% CI: 1.18

Assuntos
Agricultura/estatística & dados numéricos , Ferimentos e Lesões/epidemiologia , Acidentes por Quedas/estatística & dados numéricos , Adolescente , Fatores Etários , Agricultura/instrumentação , Animais , Criança , Pré-Escolar , Traumatismos Craniocerebrais/epidemiologia , Feminino , Cavalos , Hospitalização/estatística & dados numéricos , Humanos , Lactente , Tempo de Internação/estatística & dados numéricos , Masculino , Traumatismos Maxilofaciais/epidemiologia , Ohio/epidemiologia , Estudos Retrospectivos , Fatores de Risco , Fatores Sexuais , Fraturas Cranianas/epidemiologia , Ferimentos e Lesões/etnologia , Ferimentos e Lesões/mortalidade
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