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Items: 1 to 20 of 112

1.
2.

Use of a self-report-generated Charlson Comorbidity Index for predicting mortality.

Chaudhry S, Jin L, Meltzer D.

Med Care. 2005 Jun;43(6):607-15.

PMID:
15908856
3.
4.
5.

Risk adjustment for older hospitalized persons: a comparison of two methods of data collection for the Charlson index.

van Doorn C, Bogardus ST, Williams CS, Concato J, Towle VR, Inouye SK.

J Clin Epidemiol. 2001 Jul;54(7):694-701.

PMID:
11438410
6.

Risk adjustment performance of Charlson and Elixhauser comorbidities in ICD-9 and ICD-10 administrative databases.

Li B, Evans D, Faris P, Dean S, Quan H.

BMC Health Serv Res. 2008 Jan 14;8:12. doi: 10.1186/1472-6963-8-12.

7.

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

Sundararajan V, Quan H, Halfon P, Fushimi K, Luthi JC, Burnand B, Ghali WA; International Methodology Consortium for Coded Health Information (IMECCHI)..

Med Care. 2007 Dec;45(12):1210-5.

PMID:
18007172
8.

Comparison of different comorbidity measures for use with administrative data in predicting short- and long-term mortality.

Chu YT, Ng YY, Wu SC.

BMC Health Serv Res. 2010 May 27;10:140. doi: 10.1186/1472-6963-10-140.

9.

Are comorbidity indices useful in predicting all-cause mortality in Type 2 diabetic patients? Comparison between Charlson index and disease count.

Monami M, Lambertucci L, Lamanna C, Lotti E, Marsili A, Masotti G, Marchionni N, Mannucci E.

Aging Clin Exp Res. 2007 Dec;19(6):492-6.

PMID:
18172372
10.

Length of comorbidity lookback period affected regression model performance of administrative health data.

Preen DB, Holman CD, Spilsbury K, Semmens JB, Brameld KJ.

J Clin Epidemiol. 2006 Sep;59(9):940-6.

PMID:
16895817
11.

The importance of laboratory data for comparing outcomes and detecting 'outlier' wards in the treatment of patients with pneumonia.

Maor Y, Rubin HR, Gabbai U, Mozes B.

J Health Serv Res Policy. 1998 Jan;3(1):39-43.

PMID:
10180388
12.

A prospective evaluation of the Charlson Comorbidity Index for use in long-term care patients.

Bravo G, Dubois MF, H├ębert R, De Wals P, Messier L.

J Am Geriatr Soc. 2002 Apr;50(4):740-5.

PMID:
11982678
13.

Selecting a patient characteristics index for the prediction of medical outcomes using administrative claims data.

Melfi C, Holleman E, Arthur D, Katz B.

J Clin Epidemiol. 1995 Jul;48(7):917-26.

PMID:
7782800
14.

Stroke: the Elixhauser Index for comorbidity adjustment of in-hospital case fatality.

Zhu H, Hill MD.

Neurology. 2008 Jul 22;71(4):283-7. doi: 10.1212/01.wnl.0000318278.41347.94.

PMID:
18645167
15.

Comorbidity measurement in elderly female breast cancer patients with administrative and medical records data.

Newschaffer CJ, Bush TL, Penberthy LT.

J Clin Epidemiol. 1997 Jun;50(6):725-33.

PMID:
9250271
16.

Comorbidity indices to predict mortality from Medicare data: results from the national registry of atrial fibrillation.

Yan Y, Birman-Deych E, Radford MJ, Nilasena DS, Gage BF.

Med Care. 2005 Nov;43(11):1073-7.

PMID:
16224299
17.

Validity of information on comorbidity derived rom ICD-9-CCM administrative data.

Quan H, Parsons GA, Ghali WA.

Med Care. 2002 Aug;40(8):675-85.

PMID:
12187181
18.

Evaluation of comorbidity indices for inpatient mortality prediction models.

Martins M, Blais R.

J Clin Epidemiol. 2006 Jul;59(7):665-9.

PMID:
16765268
19.

Predicting 1 year mortality in an outpatient haemodialysis population: a comparison of comorbidity instruments.

Miskulin DC, Martin AA, Brown R, Fink NE, Coresh J, Powe NR, Zager PG, Meyer KB, Levey AS; Medical Directors, Dialysis Clinic, Inc..

Nephrol Dial Transplant. 2004 Feb;19(2):413-20.

20.

Searching for an improved clinical comorbidity index for use with ICD-9-CM administrative data.

Ghali WA, Hall RE, Rosen AK, Ash AS, Moskowitz MA.

J Clin Epidemiol. 1996 Mar;49(3):273-8.

PMID:
8676173
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