1 |
Kim HY. Relationship between Hospital Volume and Risk-Adjusted Mortality Rate Following Percutaneous Coronary Intervention [dissertation]. Seoul: Korea University; 2007. (Korean)
|
2 |
Lee KS, Lee SI. Does a higher coronary artery bypass graft surgery volume always have a low in-hospital mortality rate in Korea? J Prev Med Public Health 2006; 39(1): 13-20. (Korean)
과학기술학회마을
ScienceOn
|
3 |
Preen DB, Holman CD, Spilsbury K, Semmens JB, Brameld KJ. Length of comorbidity lookback period affected regression model performance of administrative health data. J Clin Epidemiol 2006; 59(9): 940-946
DOI
ScienceOn
|
4 |
Stukenborg GJ, Wagner DP, Connors AF Jr. Comparison of the performance of two comorbidity measures, with and without information from prior hospitalization. Med Care 2001; 39(7): 727-739
DOI
ScienceOn
|
5 |
Sundararajan V, Henderson T, Perry C, Muggivan A, Quan H, Ghali WA. New ICD-10 version of the Charlson comorbidity index predicted in-hospital mortality. J Clin Epidemiol 2004; 57(12): 1288-1294
DOI
ScienceOn
|
6 |
Alidoosti M, Salarifar M, Zeinali AM, Kassaian SE, Dehkordi MR. Comparison of outcomes of percutaneous coronary intervetion on proximal versus non-proximal left anterior descending coronary artery, proximal left circumflex, and proximal right coronary artery: A corss-sectional study. BMC Cardiovacs Disord 2007; 7: 7
DOI
PUBMED
|
7 |
Zavascki AP, Fuchs SC. The need for reappraisal of AIDS score weight of Charlson comorbidity index. J Clin Epidemiol 2007; 60(9): 867-868
DOI
ScienceOn
|
8 |
Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care 1998; 36(1): 8-27
DOI
ScienceOn
|
9 |
Quan H, Sundararajan V, Halfon P, Fong A, Burnand B, Luthi JC, et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 2005; 43(11): 1130-1139
DOI
ScienceOn
|
10 |
Zhang JX, Iwashyna TJ, Christakis NA. The performance of different lookback periods and sources of information for Charlson comorbidity adjustment in medicare claims. Med Care 1999; 37(11): 1128-1139
DOI
ScienceOn
|
11 |
Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J Chronic Dis 1987; 40(5): 373-383
DOI
ScienceOn
|
12 |
Epstein AJ, Rathore SS, Krumholz HM, Volpp KG. Volume-based referral for cardiovascular procedures in the United States: A crosssectional regression analysis. BMC Health Serv Res 2005; 5: 42
DOI
PUBMED
ScienceOn
|
13 |
Li B, Evans D, Faris P, Dean S, Quan H. Risk adjustment performance of Charlson and Elixhauser comorbidities in ICD-9 and ICD-10 administrative databases. BMC Health Serv Res 2008; 8: 12
DOI
PUBMED
ScienceOn
|
14 |
Halfon P, Eggli Y, van Melle G, Chevalier J, Wasserfallen JB, Burnand B. Measuring potentially avoidable hospital readmissions. J Clin Epidemiol 2002; 55(6): 573-587
DOI
ScienceOn
|
15 |
Schneeweiss S, Wang PS, Avorn J, Glynn RJ. Improved comorbidity adjustment for predicting mortality in medicare populations. Health Serv Res 2003; 38(4): 1103-1120
DOI
ScienceOn
|
16 |
Birim O, Maat AP, Kappetein AP, van Meerbeeck JP, Damhuis RA, Bogers AJ. Validation of the Charlson comorbidity index in patients with operated primary non-small cell lung cancer. Eur J Cardiothorac Surg 2003; 23(1): 30-34
DOI
ScienceOn
|
17 |
Southern DA, Quan H, Ghali WA. Comparison of the Elixhauser and Charlson/ Deyo methods of comorbidity measurement in administrative data. Med Care 2004; 42(4): 355-360
DOI
ScienceOn
|
18 |
Carey JS, Danielsen B, Gold JP, Rossiter SJ. Procedure rates and outcomes of coronary revascularization procedures in California and New York. J Thorac Cardiovasc Surg 2005; 129(6): 1276-1282
DOI
PUBMED
ScienceOn
|
19 |
Harjai KJ, Berman AD, Grines CL, Kahn J, Marsalese D, Mehta RH, et al. Impact of interventionalist volume, experience, and board certification on coronary angioplasty outcomes in the era of stenting. Am J Cardiol 2004; 94(4): 421-426
DOI
ScienceOn
|
20 |
Burton KR, Slack R, Oldroyd KG, Pell AC, Flapan AD, Starkey IR, et al. Hosptial volume of throughput and periprocedural and mediumterm adverse events after percutaneous coronary intervention: Retrospective cohort study of all 17,417 procedures undertaken in Scotland, 1997-2003. Heart 2006; 92(11): 1667-1672
DOI
PUBMED
ScienceOn
|
21 |
Lee DS, Donovan L, Austin PC, Gong Y, Liu PP, Rouleau JL, et al. Comparison of coding of heart failure and comorbidities in administrative and clinical data for use in outcomes research. Med Care 2005; 43(2): 182-188
DOI
ScienceOn
|
22 |
Klabunde CN, Potosky AL, Legler JM, Warren JL. Development of a comorbidity index using physician claims data. J Clin Epidemiol 2000; 53(12): 1258-1267
DOI
ScienceOn
|
23 |
Birim O, Kappetein AP, Bogers AJ. Charlson comorbidity index as a predictor of long-term outcome after surgery for nonsmall cell lung cancer. Eur J Cardiothorac Surg 2005; 28(5): 759-762
DOI
ScienceOn
|
24 |
Agency for Healthcare Research and Quality. AHRQ Quality Indicators-Guide to Inpatient Quality Indicators: Quality of Care in Hospitals-Volume, Mortality, and Utilization. Rockville: Agency for Healthcare Research and Quality; 2002. Report No.: AHRQ Pub. No. 02-RO204
|
25 |
Sundararajan V, Quan H, Halfon P, Fushimi K, Luthi J, Burnand B, et al. Cross-national comparative performance of three versions of the ICD-10 Charlson index. Med Care 2007; 45(12): 1210-1215
DOI
ScienceOn
|
26 |
Kim JY, Kim HY, Im JH. Development of Risk Adjustment and Prediction Methods for Care Episodes using National Health Insurance Database. Seoul: Health Insurance Review & Assessment Service; 2007. (Korean)
|
27 |
Cleves MA, Sanchez N, Draheim M. Evaluation of two competing methods for calculating Charlson s comorbidity index when analyzing short-term mortality using administrative data. J Clin Epidemiol 1997; 50(8): 903-908
DOI
ScienceOn
|