Development and testing of a systemic lupus-specific risk adjustment index for in-hospital mortality

Journal of Rheumatology

Volumn 27, Issue 6, 2000, Pages 1408-1413

  Ward, Michael M ^a,b  

^a VA PALO ALTO HEALTH CARE SYSTEM   (United States)

^b STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Comorbid conditions; Quality of care; Risk adjustment; Systemic lupus erythematosus

Indexed keywords

ADULT; ARTICLE; CLINICAL TRIAL; CONTROLLED CLINICAL TRIAL; CONTROLLED STUDY; DIAGNOSTIC VALUE; HOSPITAL PATIENT; HUMAN; HUMAN CELL; HUMAN TISSUE; MAJOR CLINICAL STUDY; MORTALITY; PRIORITY JOURNAL; RANDOMIZED CONTROLLED TRIAL; REGRESSION ANALYSIS; RISK ASSESSMENT; SCORING SYSTEM; SYSTEMIC LUPUS ERYTHEMATOSUS; UNITED STATES;

ADOLESCENT; ADULT; AGED; COMORBIDITY; HOSPITAL MORTALITY; HOSPITALS; HUMANS; LOGISTIC MODELS; LUPUS ERYTHEMATOSUS, SYSTEMIC; MEDICAL RECORDS; MIDDLE AGED; MULTIVARIATE ANALYSIS; PREDICTIVE VALUE OF TESTS; RISK ADJUSTMENT; SEVERITY OF ILLNESS INDEX;

EID: 0034045273     PISSN: 0315162X     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (17)

1. Iezzoni LI, editor. Risk adjustment for measuring healthcare outcomes. 2nd edition. Chicago: Health Administration Press; 1997.
2. Ward MM. Hospital experience and mortality in patients with systemic lupus erythematosus. Arthritis Rheum 1999;42:891-8.
3. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chron Dis 1987;40:373-83.
4. Wray NP, Hollingsworth JC, Petersen NJ, Ashton CM. Case-mix adjustment using administrative databases: a paradigm to guide future research. Med Care Res Rev 1997;54:326-56.
5. Romano PS, Roos LL, Jollis JG. Further evidence concerning the use of a clinical comorbidity index with ICD-9-CM administrative data. J Clin Epidemiol 1993;46:1085-90.
6. Ghali WA, Hall RE, Rosen AK, Ash AS, Moskowitz MA. Searching for an improved clinical comorbidity index for use with ICD-9-CM administrative data. J Clin Epidemiol 1996;49:273-8.
7. Polanczyk CA, Rohde LEP, Philbin EA, DiSalvo TG. A new case mix adjustment index for hospital mortality among patients with congestive heart failure. Med Care 1998;36:1489-99.
8. The International Classification of Diseases, 9th Revision, Clinical Modification: ICD-9-CM. 10th edition. Baltimore: HCIA; 1993.
9. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 1992;45:613-9.
10. Hanley JA, McNeil BJ. A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology 1983;148:839-43.
11. Lemeshow S, Hosmer DW Jr. A review of goodness of fit statistics for use in the development of logistic regression models. Am J Epidemiol 1982;115:92-106.
12. Roos LL, Sharp SM, Cohen MM, Wajda A. Risk adjustment in claims-based research: the search for efficient approaches. J Clin Epidemiol 1989;42:1193-206.
13. Alemi F, Rice J, Hankins R. Predicting in-hospital survival of myocardial infarction. A comparative study of various severity measures. Med Care 1990;28:762-75.
14. Iezzoni LI, Ash AS, Coffman GA, Moskowitz MA. Predicting inhospital mortality. A comparison of severity measurement approaches. Med Care 1992;30:347-59.
15. Hannan EL, Kilburn H, Lindsey ML, Lewis R. Clinical versus administrative data hases for CABG surgery. Does it matter? Med Care 1992;30:892-907.
16. Pine M, Norusis M, Jones B, Rosenthal GE. Predictions of hospital mortality rates: A comparison of data sources. Ann Intern Med 1997;126:347-54.
17. Iezzoni LI. Assessing quality using administrative data. Ann Intern Med 1997;127:666-74.