insurance: government sponsored

Overview

This model predicts whether a voter has government-sponsored health insurance — primarily Medicare and Medicaid.

Trained on survey data, it uses income-level indicators, age, and neighborhood demographics to identify voters with public coverage.

Organizations can use these scores to focus outreach around government health program protections, funding, and eligibility.

  • approach: deep learning
  • training rows: 5,449
  • last updated: 2026-07-30 20:52:27

Validation

metric value
area under ROC curve 0.84
area under precision-recall curve 0.77
accuracy 0.81
precision 0.79
recall 0.69
f1 score 0.73
mean log loss 0.47
gini coefficient 0.69
brier skill score 0.38

Lift Chart

Each bar shows how much more common the outcome is within a score decile than in the population overall. Bars taller than the dashed line (lift of 1) mean the model’s top-ranked groups concentrate the outcome; a steady decline from decile 1 to 10 indicates the model is ranking effectively.

Calibration Plot

Bars of similar height within each decile indicate well-calibrated predictions. Systematic differences reveal where the model over- or under-predicts.

Cumulative Gains

The further the model curve bows above the diagonal, the better the model concentrates the outcome in its top-ranked predictions.

Decile Analysis Table

decile count mean actual mean predicted mae lift
10 139 0.87 0.90 0.03 2.25
9 138 0.83 0.82 0.009 2.15
8 139 0.73 0.69 0.04 1.88
7 138 0.47 0.48 0.004 1.22
6 139 0.30 0.32 0.03 0.76
5 138 0.21 0.23 0.02 0.54
4 138 0.15 0.16 0.01 0.39
3 139 0.15 0.12 0.03 0.39
2 138 0.07 0.10 0.02 0.19
1 139 0.09 0.07 0.02 0.22

Architecture

This model is a deep neural network trained with TensorFlow.

Network structure

layer units activation
↓ dense 128 relu
↓ dropout (0.20 rate)
↓ dense 91 swish
↓ dropout (0.13 rate)
↓ dense 54

Hyperparameter configuration

  • loss: binary_focal_crossentropy
  • optimizer: nadam
  • batch size: 16
  • activation: sigmoid
  • label smoothing: 0.01
  • learning rate: 0.001

Features

Importance

Sourcing

Agency for Healthcare Research and Quality

  • received snap / food stamps (%)

Attom Property Data API

  • lot size (acres)

Revelio Labs

  • current position salary
  • max salary
  • number of jobs held

State voter files (via TargetSmart)

  • age

TargetSmart

  • double negative downballot gop score
  • double negative gop score
  • early vote / absentee vote score
  • ideology score (enhanced)
  • income rank
  • marriage score
  • midterm general turnout score
  • non-religious score
  • paid leave support score
  • presidential general turnout score
  • pro-choice score
  • recession sensitivity score

U.S. Census American Community Survey

  • block group % black
  • block group % income <$25k
  • tract median income

Verisk (via TargetSmart)

  • home value
  • medical occupation
  • net worth
  • spanish speaker in household

Implementation

Prediction distribution

statistic value
mean 0.40
std dev 0.29
min 0.03
25th 0.14
median 0.30
75th 0.69
max 0.99

Segments

segment lowest score highest score share of records
Most likely 0.54 0.99 32.8%
Somewhat likely 0.18 0.53 34.1%
Least likely 0.03 0.17 33.2%

External validity

Our model indicates that 40% of people with scored records have government-sponsored health insurance (Medicare or Medicaid). As of 2025, 36% of U.S. adults were receiving public health insurance.