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Volumn 45, Issue 12, 2007, Pages 1210-1215

Cross-national comparative performance of three versions of the ICD-10 charlson index

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; COMORBIDITY; COMPARATIVE STUDY; HUMAN; INTERNATIONAL CLASSIFICATION OF DISEASES; LANGUAGE; MIDDLE AGED; MORTALITY; ORGANIZATION AND MANAGEMENT; PREDICTION AND FORECASTING; RISK ASSESSMENT;

EID: 36248968660     PISSN: 00257079     EISSN: None     Source Type: Journal    
DOI: 10.1097/MLR.0b013e3181484347     Document Type: Article
Times cited : (197)

References (13)
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  • 2
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    • Adapting a clinical comorbidity index for use with ICD-9-CM administrative data: Differing perspectives
    • discussion 1081-1090
    • Romano PS, Roos LL, Jollis JG. Adapting a clinical comorbidity index for use with ICD-9-CM administrative data: differing perspectives. J Clin Epidemiol. 1993;46:1075-1079; discussion 1081-1090.
    • (1993) J Clin Epidemiol , vol.46 , pp. 1075-1079
    • Romano, P.S.1    Roos, L.L.2    Jollis, J.G.3
  • 4
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    • Risk adjustment in outcome assessment: The Charlson comorbidity index
    • D'Hoore W, Sicotte C, Tilquin C. Risk adjustment in outcome assessment: the Charlson comorbidity index. Methods Inf Med. 1993;32:382-387.
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  • 6
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    • New ICD-10 version of the Charlson comorbidity index predicted in-hospital mortality
    • Sundararajan V, Henderson T, Perry C, et al. New ICD-10 version of the Charlson comorbidity index predicted in-hospital mortality. J Clin Epidemiol. 2004;57:1288-1294.
    • (2004) J Clin Epidemiol , vol.57 , pp. 1288-1294
    • Sundararajan, V.1    Henderson, T.2    Perry, C.3
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    • Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data
    • Quan H, Sundararajan V, Halfon P, et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care. 2005;43:1130-1139.
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    • Quan, H.1    Sundararajan, V.2    Halfon, P.3
  • 8
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    • Quality of diagnosis and procedure coding in ICD-10 administrative data
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.