Table 3.
Predictive Validity of Comorbidity Indices in Health Care-Related Behaviors
| Response Variable: Physician Concordance with Care Standard | ||||||
|---|---|---|---|---|---|---|
| Goodness of Fit for overall modela | ||||||
| Predictor of interest | Likelihood ratiob | Deviance | McFadden's Adjusted R2 | AIC | BIC | For 1-unit increase in comorbidity score, % change in physicians' care standard concordance scorec |
| CCI | 202.81 | 32031.18 | 0.14 | 32075.18 | 32233.41 | −0.2, p=0.644 |
| EI | 210.96 | 32023.03 | 0.15 | 32067.03 | 32225.27 | 1.4, p=0.000 |
| CDS | 219.71 | 32014.28 | 0.15 | 32058.28 | 32216.52 | 1.7, p=0.000 |
| HRQL-CI–physical | 209.70 | 32024.29 | 0.15 | 32068.29 | 32226.53 | 0.6, p=0.00 |
| HRQL-CI–mental | 205.23 | 32028.73 | 0.14 | 32072.73 | 32230.97 | 0.4, p=0.015 |
| Response Variable: Patient Oral Antidiabetic Medication Adherence | ||||||
|---|---|---|---|---|---|---|
| Goodness of Fit for overall modela | ||||||
| Predictor of interest | Likelihood ratiob | Deviance | Max-rescaled R2 | AIC | BIC | For 1-unit increase in comorbidity score, % change in the odds of being medication adherentd |
| CCI | 495.94 | 12394.62 | 0.17 | 12430.62 | 12560.08 | 0.6, p=0.7596 |
| EI | 496.77 | 12393.79 | 0.17 | 12429.79 | 12559.25 | 1.7, p=0.3366 |
| CDS | 502.95 | 12387.61 | 0.17 | 12423.61 | 12553.08 | 3.7, p=0.0078 |
| HRQL-CI–physical | 496.23 | 12394.32 | 0.17 | 12430.32 | 12559.79 | −0.5, p=0.5335 |
| HRQL-CI–mental | 506.16 | 12384.40 | 0.19 | 12420.40 | 12549.87 | −2.5, p=0.0013 |
AIC, Akaike's information criterion; BIC, Bayesian information criterion; CCI, Charlson Comorbidity Index; EI, Elixhauser Index; CDS, Chronic Disease Score; HRQL-CI, Health-related Quality of Life Comorbidity Index. aThe variables included in the model were comorbidity score, patient's age, race, sex, type of health plan, type of provider, number of therapeutic classes and number of medications prescribed, diabetes disease severity, and baseline health care-related characteristics (eg, health care costs in pre-index period). b X2 test for the likelihood ratio for each individual model was statistically significant (P=0.000). c The analysis is based on standard Poisson regression, the value in the column was calculated as: 100*b%, where b=beta-coefficient. dThe analysis based on logistic regression, the value in the column was computed by the formula: 100*[exp]c-1]%, where exp(c)=exponentiated coefficient.