Pharma Screening Strategy Calculator

Compare a predictive model vs random screening for patient identification. Visualize hit rates, confusion matrices, and financial impact in real time.

Population & Financial Parameters

%
=real positives

Model Parameters

%
%

Model 1

21.03%

Hit Rate (PPV)

Patients screened19,660
% of population screened39.32%
Positives found (TP)4,135
Positives missed (FN)865
False positives (FP)15,525
Sensitivity82.70%

Random (coin flip Se=Sp=50%)

10.00%

Hit Rate (= Prevalence always)

Patients screened25,000
% of population screened50.00%
Positives found (TP)2,500
Positives missed (FN)2,500
False positives (FP)22,500
Sensitivity50.00%

Visual Comparison

Hit Rate (of those screened, what % are truly positive)

Model 1
21.03%
Random
10.00%

Sensitivity (what % of real positives each strategy captures)

Model 1
82.70%
Random
50.00%

Fair comparison: same number of patients screened

Model 1
4,135 TP
Random (same N) (N=19,660)
1,966 TP
Model 1: +110.3% Hit Rate

Confusion Matrix — Model 1

Real +
Real −
Pred +
4,135
TP
15,525
FP
Pred −
865
FN
29,475
TN

Confusion Matrix — Random

Real +
Real −
Pred +
2,500
TP
22,500
FP
Pred −
2,500
FN
22,500
TN

Financial Analysis — Costs and Revenue by Strategy

StrategyScreenedScreening CostPositives CapturedGross RevenueNet ResultCost per positive captured
Model 119,660$19,660,0004,135$4,135,000,000$4,115,340,000$4,755
Random (50%)25,000$25,000,0002,500$2,500,000,000$2,475,000,000$10,000

Model 1 advantage vs random

$1,640,340,000

Model 1 ROI

20,933%

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