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

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

Peter C Austin  1 , Matthew B Stanbrook, Geoffrey M Anderson, Alice Newman, Andrea S Gershon
Affiliations
Comparative Study

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

Peter C Austin et al. Ann Epidemiol. 2012 Dec.

Abstract

Purpose: Administrative healthcare databases are used for health services research, comparative effectiveness studies, and measuring quality of care. Adjustment for comorbid illnesses is essential to such studies. Validation of methods to account for comorbid illnesses in administrative data for patients with chronic obstructive pulmonary disease (COPD) has been limited. Our objective was to compare the ability of the Charlson index, the Elixhauser method, and the Johns Hopkins' Aggregated Diagnosis Groups (ADGs) to predict outcomes in patients with COPD.

Methods: Retrospective cohorts constructed using population-based administrative data of patients with incident (n = 216,735) and prevalent (n = 638,926) COPD in Ontario, Canada, were divided into derivation and validation datasets. The primary outcome was all-cause death within 1 year. Secondary outcomes included all-cause hospitalization, COPD-specific hospitalization, non-COPD hospitalization, and COPD exacerbations.

Results: In both the incident and prevalent COPD cohorts, the three methods had comparable discrimination for predicting mortality (c-statistics in the validation sample of incident patients of 0.819 for the Charlson method versus 0.822 for the Elixhauser method versus 0.830 for the ADG method). All three methods had lower predictive accuracy for predicting nonfatal outcomes.

Conclusions: In a disease-specific cohort of COPD patients, all three methods allowed for accurate prediction of mortality, with the Johns Hopkins ADGs having marginally higher discrimination.

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Conflict of interest statement

Conflicts of interest: The authors have no conflicts of interest to report.

Figures

Figure 1
Figure 1
Receiver Operating Characteristic (ROC) curves of the three regression models in the incident and prevalent populations: Incident population (left panel) and prevalent population (right panel).
Figure 2
Figure 2
Calibration plots in the incident COPD population: Comparison of observed vs. predicted mortality in 50 strata of risk.
Figure 3
Figure 3
Calibration plots in the prevalent COPD population: Comparison of observed vs. predicted mortality in the centiles of risk.
See this image and copyright information in PMC

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References

    1. Almagro P, Calbo E, Ochoa de Echaguen A, et al. Mortality after hospitalization for COPD. Chest. 2002;121:1441–1448. - PubMed
    1. Anthonisen NR, Skeans MA, Wise RA, Manfreda J, Kanner RE, Connett JE Lung Health Study Research Group. The effects of a smoking cessation intervention on 14. 5-year mortality: a randomized clinical trial. Annals of Internal Medicine. 2005;142:233–239. - PubMed
    1. Austin PC, Newman A, Kurdyak PM. Using the Johns Hopkins Aggregated Diagnosis Groups (ADGs) to predict mortality in a population-based cohort of subjects with schizophrenia in Ontario, Canada. Psychiatry Research. 2012;196(1):32–37. - PubMed
    1. Austin PC, Shah BR, Newman A, Anderson GM. Using the Johns Hopkins Aggregated Diagnosis Groups (ADGs) to predict mortality in a population-based cohort of patients with diabetes in Ontario, Canada. Diabetic Medicine. 2012 - PubMed
    1. Austin PC, van Walraven C. The Mortality Risk Score and the ADG Score: Two Points-Based Scoring Systems for the Johns Hopkins Aggregated Diagnosis Groups to Predict Mortality in a General Adult Population Cohort in Ontario, Canada. Medical Care. 2011;49(10):940–947. - PMC - PubMed

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