메뉴 건너뛰기




Volumn 16, Issue 7, 2009, Pages 639-645

The impact of injury coding schemes on predicting hospital mortality after pediatric injury

Author keywords

International Classification of Diseases; Predictive value of tests; Survival rate; Trauma severity indices

Indexed keywords

ARTICLE; BAYES THEOREM; CHILD; CHILDHOOD INJURY; DISEASE CLASSIFICATION; DISEASE SEVERITY; FEMALE; HUMAN; INJURY SCALE; LOGISTIC REGRESSION ANALYSIS; MAJOR CLINICAL STUDY; MALE; MORTALITY; PATIENT CODING; PRIORITY JOURNAL;

EID: 67650270944     PISSN: 10696563     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.1553-2712.2009.00446.x     Document Type: Article
Times cited : (12)

References (24)
  • 1
    • 0015962447 scopus 로고
    • The injury severity score: A method for describing patients with multiple injuries and evaluating emergency care
    • Baker SP, O'Neill B, Haddon W Jr, Long WB. The injury severity score: a method for describing patients with multiple injuries and evaluating emergency care. J Trauma. 1974; 14:187-196
    • (1974) J Trauma , vol.14 , pp. 187-196
    • Baker, S.P.1    O'neill, B.2    Haddon Jr., W.3    Long, W.B.4
  • 2
    • 0036237815 scopus 로고    scopus 로고
    • Trauma score systems for quality assessment
    • DOI 10.1007/s00068-002-0170-y
    • Lefering R. Trauma score systems for quality assessment. Eur J Trauma. 2002; 28:52-63. (Pubitemid 34453447)
    • (2002) European Journal of Trauma , vol.28 , Issue.2 , pp. 52-63
    • Lefering, R.1
  • 7
    • 0031782850 scopus 로고    scopus 로고
    • The ICD-9-based illness severity score: A new model that outperforms both DRG and APR-DRG as predictors of survival and resource utilization
    • DOI 10.1097/00005373-199810000-00032
    • Rutledge R, Osler T. The ICD-9-based illness severity score: a new model that outperforms both DRG and APR-DRG as predictors of survival and resource utilization. J Trauma. 1998; 45:791-799 (Pubitemid 28480585)
    • (1998) Journal of Trauma - Injury, Infection and Critical Care , vol.45 , Issue.4 , pp. 791-799
    • Rutledge, R.1    Osler, T.2
  • 9
    • 0348163466 scopus 로고    scopus 로고
    • Independently Derived Survival Risk Ratios Yield Better Estimates of Survival than Traditional Survival Risk Ratios When Using the ICISS
    • DOI 10.1097/01.TA.0000085646.71451.5F
    • Meredith JW, Kilgo PD, Osler TM. Independently derived survival risk ratios yield better estimates of survival than traditional survival risk ratios when using the ICISS. J Trauma. 2003; 55:933-938 (Pubitemid 38004667)
    • (2003) Journal of Trauma - Injury, Infection and Critical Care , vol.55 , Issue.5 , pp. 933-938
    • Meredith, J.W.1    Kilgo, P.D.2    Osler, T.M.3
  • 10
    • 29544437053 scopus 로고    scopus 로고
    • Comparisons of survival predictions using survival risk ratios based on International Classification of Diseases, Ninth Revision and abbreviated injury scale trauma diagnosis codes
    • DOI 10.1097/01.ta.0000177786.86575.c1
    • Clarke JR, Ragone AV, Greenwald L. Comparisons of survival predictions using survival risk ratios based on International Classification of Diseases, Ninth Revision and Abbreviated Injury Scale trauma diagnosis codes. J Trauma. 2005; 59:563-567 (Pubitemid 43014919)
    • (2005) Journal of Trauma - Injury, Infection and Critical Care , vol.59 , Issue.3 , pp. 563-569
    • Clarke, J.R.1    Ragone, A.V.2    Greenwald, L.3    Kilgo, P.4    Bessey, P.Q.5
  • 12
    • 44449138552 scopus 로고    scopus 로고
    • A trauma mortality prediction model based on the anatomic injury scale
    • DOI 10.1097/SLA.0b013e31816ffb3f, PII 0000065820080600000019
    • Osler T, Glance L, Buzas JS, Mukamel D, Wagner J, Dick A. A trauma mortality prediction model based on the anatomic injury scale. Ann Surg. 2008; 247:1041-1048 (Pubitemid 351770426)
    • (2008) Annals of Surgery , vol.247 , Issue.6 , pp. 1041-1048
    • Osler, T.1    Glance, L.2    Buzas, J.S.3    Mukamel, D.4    Wagner, J.5    Dick, A.6
  • 13
  • 14
    • 44049102487 scopus 로고    scopus 로고
    • Bayesian logistic injury severity score: A method for predicting mortality using International Classification of Disease-9 codes
    • Burd RS, Ouyang M, Madigan D. Bayesian logistic injury severity score: a method for predicting mortality using International Classification of Disease-9 codes. Acad Emerg Med. 2008; 15:466-475
    • (2008) Acad Emerg Med , vol.15 , pp. 466-475
    • Burd, R.S.1    Ouyang, M.2    Madigan, D.3
  • 15
    • 49949090127 scopus 로고    scopus 로고
    • Improving the predictive ability of the ICD-based Injury Severity Score
    • Davie G, Cryer C, Langley J. Improving the predictive ability of the ICD-based Injury Severity Score. Inj Prev. 2008; 14:250-255
    • (2008) Inj Prev , vol.14 , pp. 250-255
    • Davie, G.1    Cryer, C.2    Langley, J.3
  • 16
    • 33751164062 scopus 로고    scopus 로고
    • Healthcare Cost and Utilization Project (HCUP), Rockville, MD. Available at: Accessed Dec 30, 2008
    • Healthcare Cost and Utilization Project (HCUP). HCUP Kids' Inpatient Database (KID). 2003. Agency for Health Care Research and Quality, Rockville, MD. Available at: http://www.hcup-us.ahrq.gov/kidoverview.jsp. Accessed Dec 30, 2008.
    • (2003) HCUP Kids' Inpatient Database (KID)
  • 17
    • 34548105186 scopus 로고    scopus 로고
    • Large-scale bayesian logistic regression for text categorization
    • DOI 10.1198/004017007000000245
    • Genkin A, Lewis DD, Madigan D. Large-scale Bayesian logistic regression for text categorization. Technometrics. 2007; 49:291-304. (Pubitemid 47292487)
    • (2007) Technometrics , vol.49 , Issue.3 , pp. 291-304
    • Genkin, A.1    Lewis, D.D.2    Madigan, D.3
  • 18
    • 0036594326 scopus 로고    scopus 로고
    • An introduction to the Barell body region by nature of injury diagnosis matrix
    • Barell V, Aharonson-Daniel L, Fingerhut LA, et al. An introduction to the Barell body region by nature of injury diagnosis matrix. Inj Prev. 2002; 8:91-96
    • (2002) Inj Prev , vol.8 , pp. 91-96
    • Barell, V.1    Aharonson-Daniel, L.2    Fingerhut, L.A.3
  • 19
    • 0035375750 scopus 로고    scopus 로고
    • Validation of the ICD/AIS MAP for pediatric use
    • Durbin DR, Localio AR, MacKenzie EJ. Validation of the ICD/AIS MAP for pediatric use. Inj Prev. 2001; 7:96-99
    • (2001) Inj Prev , vol.7 , pp. 96-99
    • Durbin, D.R.1    Localio, A.R.2    MacKenzie, E.J.3
  • 20
    • 33645907514 scopus 로고    scopus 로고
    • Estimating injury severity using the Barell matrix
    • Clark DE, Ahmad S. Estimating injury severity using the Barell matrix. Inj Prev. 2006; 12:111-116
    • (2006) Inj Prev , vol.12 , pp. 111-116
    • De Clark1    Ahmad, S.2
  • 21
    • 34548720539 scopus 로고    scopus 로고
    • Mortality in adolescent girls vs boys following traumatic shock: An analysis of the national pediatric trauma registry
    • DOI 10.1001/archsurg.142.9.875
    • Haider AH, Efron DT, Haut ER, Chang DC, Paidas CN, Cornwell EE III. Mortality in adolescent girls vs boys following traumatic shock: an analysis of the National Pediatric Trauma Registry. Arch Surg. 2007; 142:875-880 (Pubitemid 47437309)
    • (2007) Archives of Surgery , vol.142 , Issue.9 , pp. 875-879
    • Haider, A.H.1    Efron, D.T.2    Haut, E.R.3    Chang, D.C.4    Paidas, C.N.5    Cornwell III, E.E.6
  • 23
    • 0031334221 scopus 로고    scopus 로고
    • Selection of relevant features and examples in machine learning
    • PII S0004370297000635
    • Blum AL, Langley P. Selection of relevant features and examples in machine learning. Artificial Intelligence. 1997; 97:245-271 (Pubitemid 127401106)
    • (1997) Artificial Intelligence , vol.97 , Issue.1-2 , pp. 245-271
    • Blum, A.L.1    Langley, P.2
  • 24
    • 0031381525 scopus 로고    scopus 로고
    • Wrappers for feature subset selection
    • Kohavi R, John GH. Wrappers for feature subset selection. Artificial Intelligence. 1997; 97:273-324
    • (1997) Artificial Intelligence , vol.97 , pp. 273-324
    • Kohavi, R.1    John, G.H.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.