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Table 2 Statistical performance of Alternative Predictive Models using U.S./Spanish weights.

From: Applying diagnosis and pharmacy-based risk models to predict pharmacy use in Aragon, Spain: The impact of a local calibration

 

Alternative Predictive Models

 

Dx-PM

Rx-PM

DxRx-PM

 

U.S. Weights

Spanish Weights

U.S. Weights

Spanish Weights

U.S. Weights

Spanish Weights

Variance explained. R 2

18.9%

29.4%

22.2%

40.6%

23.5%

42.6%

Area Under ROC Curve*

.868

.902

.900

.941

.903

.949

Sensitivity*

30.6%

39.4%

27.5%

52.3%

31.2%

53.2%

Specificity*

96.3%

96.8%

96.2%

97.5%

96.4%

97.5%

Mean pharmacy expenditure Year-2 (€)*

      

   True positives

3,059

3,076

3,244

3,236

3,248

3,244

   True negatives

233

233

236

234

235

234

  1. *Outcomes refer to top 5% Year-2 pharmacy cost group. The Area Under ROC Curve ranges from 0.5 (model no better than the flip of a coin) to 1.0 (perfect true positive and true negative classification).
  2. Dx: physician assigned diagnosis. Rx: pharmacy prescriptions filled by physicians. PM: predictive model.