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Items: 1 to 20 of 104

1.

Using the Johns Hopkins Aggregated Diagnosis Groups (ADGs) to predict mortality in a general adult population cohort in Ontario, Canada.

Austin PC, van Walraven C, Wodchis WP, Newman A, Anderson GM.

Med Care. 2011 Oct;49(10):932-9. doi: 10.1097/MLR.0b013e318215d5e2.

3.

Using the Johns Hopkins Aggregated Diagnosis Groups (ADGs) to predict mortality in a population-based cohort of adults with schizophrenia in Ontario, Canada.

Austin PC, Newman A, Kurdyak PA.

Psychiatry Res. 2012 Mar 30;196(1):32-7. doi: 10.1016/j.psychres.2011.09.023. Epub 2012 Feb 25.

PMID:
22364931
4.

Using the Johns Hopkins' Aggregated Diagnosis Groups (ADGs) to predict 1-year mortality in population-based cohorts of patients with diabetes in Ontario, Canada.

Austin PC, Shah BR, Newman A, Anderson GM.

Diabet Med. 2012 Sep;29(9):1134-41. doi: 10.1111/j.1464-5491.2011.03568.x.

5.

Comparative ability of comorbidity classification methods for administrative data to predict outcomes in patients with chronic obstructive pulmonary disease.

Austin PC, Stanbrook MB, Anderson GM, Newman A, Gershon AS.

Ann Epidemiol. 2012 Dec;22(12):881-7. doi: 10.1016/j.annepidem.2012.09.011. Epub 2012 Oct 31.

6.

Comparison of comorbidity classification methods for predicting outcomes in a population-based cohort of adults with human immunodeficiency virus infection.

Antoniou T, Ng R, Glazier RH, Kopp A, Austin PC.

Ann Epidemiol. 2014 Jul;24(7):532-7. doi: 10.1016/j.annepidem.2014.04.002. Epub 2014 Apr 18.

PMID:
24837611
7.

The Elixhauser comorbidity method outperforms the Charlson index in predicting inpatient death after orthopaedic surgery.

Menendez ME, Neuhaus V, van Dijk CN, Ring D.

Clin Orthop Relat Res. 2014 Sep;472(9):2878-86. doi: 10.1007/s11999-014-3686-7. Epub 2014 May 28.

8.

The Kaiser Permanente inpatient risk adjustment methodology was valid in an external patient population.

van Walraven C, Escobar GJ, Greene JD, Forster AJ.

J Clin Epidemiol. 2010 Jul;63(7):798-803. doi: 10.1016/j.jclinepi.2009.08.020. Epub 2009 Dec 11.

PMID:
20004550
9.

Predicting In-Hospital Mortality in Elderly Patients With Cervical Spine Fractures: A Comparison of the Charlson and Elixhauser Comorbidity Measures.

Menendez ME, Ring D, Harris MB, Cha TD.

Spine (Phila Pa 1976). 2015 Jun 1;40(11):809-15. doi: 10.1097/BRS.0000000000000892.

PMID:
25785957
10.

Development and validation of a model that uses enhanced administrative data to predict mortality in patients with sepsis.

Lagu T, Lindenauer PK, Rothberg MB, Nathanson BH, Pekow PS, Steingrub JS, Higgins TL.

Crit Care Med. 2011 Nov;39(11):2425-30. doi: 10.1097/CCM.0b013e31822572e3.

PMID:
22005222
11.

Comparing the performance of the Charlson/Deyo and Elixhauser comorbidity measures across five European countries and three conditions.

Gutacker N, Bloor K, Cookson R.

Eur J Public Health. 2015 Feb;25 Suppl 1:15-20. doi: 10.1093/eurpub/cku221.

PMID:
25690125
12.

Comparison of Rx-defined morbidity groups and diagnosis- based risk adjusters for predicting healthcare costs in Taiwan.

Kuo RN, Lai MS.

BMC Health Serv Res. 2010 May 17;10:126. doi: 10.1186/1472-6963-10-126.

13.

Predictive performance of comorbidity measures in administrative databases for diabetes cohorts.

Lix LM, Quail J, Fadahunsi O, Teare GF.

BMC Health Serv Res. 2013 Aug 17;13:340. doi: 10.1186/1472-6963-13-340.

14.

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.

15.

Performance of comorbidity measures for predicting outcomes in population-based osteoporosis cohorts.

Lix LM, Quail J, Teare G, Acan B.

Osteoporos Int. 2011 Oct;22(10):2633-43. doi: 10.1007/s00198-010-1516-7. Epub 2011 Jan 11.

PMID:
21305268
16.

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
17.

Development and Validation of a Predictive Model to Identify Individuals Likely to Have Undiagnosed Chronic Obstructive Pulmonary Disease Using an Administrative Claims Database.

Moretz C, Zhou Y, Dhamane AD, Burslem K, Saverno K, Jain G, Devercelli G, Kaila S, Ellis JJ, Hernandez G, Renda A.

J Manag Care Spec Pharm. 2015 Dec;21(12):1149-59.

18.

Inpatient mortality after orthopaedic surgery.

Menendez ME, Neuhaus V, Ring D.

Int Orthop. 2015 Jul;39(7):1307-14. doi: 10.1007/s00264-015-2702-1. Epub 2015 Feb 25.

PMID:
25711395
19.

Categorized diagnoses and procedure records in an administrative database improved mortality prediction.

Yamana H, Matsui H, Sasabuchi Y, Fushimi K, Yasunaga H.

J Clin Epidemiol. 2015 Sep;68(9):1028-35. doi: 10.1016/j.jclinepi.2014.12.004. Epub 2014 Dec 18.

PMID:
25596112
20.

A new casemix adjustment index for hospital mortality among patients with congestive heart failure.

Polanczyk CA, Rohde LE, Philbin EA, Di Salvo TG.

Med Care. 1998 Oct;36(10):1489-99.

PMID:
9794342

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