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Predict adherence risk โ€” before you even prescribe

H2H predicts the probability that a patient will adhere to a medication before you prescribe it. When that probability is low, our proprietary AI/ML algorithm tells you why โ€” a pharmacy desert, a complex regimen, or another contributing factor โ€” so you can act first.

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What It Predicts

A clearer signal than a fill-rate report

Instead of reacting to a missed refill after the fact, the model reads the pattern building up to it.

1

Adherence probability, before you prescribe

A proprietary AI/ML score estimates how likely a patient is to adhere to a specific medication โ€” calculated before the prescription is sent, not after a fill is missed.

2

The reason behind a low score

When probability is low, H2H surfaces the likely driver โ€” a pharmacy desert, a complex prescription regimen, cost, or another contributing factor.

3

A chance to act first

Choose a different pharmacy, simplify the regimen, or address the barrier before the script ever leaves your hands.

Reasons, Not Just a Score

See the barrier, not just the risk

Our proprietary AI/ML algorithm weighs pharmacy access, regimen complexity, medication class, and other real-world factors to explain a low adherence probability โ€” not just flag one.

That means you can address the actual barrier \u2014 switch pharmacies, simplify dosing, or add support \u2014 before the patient ever leaves with a script they won\u2019t fill.

How Early Intervention Works

From flag to follow-up, in the same workflow

1

Prediction runs at the point of prescribing

The probability and its likely reason appear right in the prescribing workflow, before you send.

2

You see the barrier in plain language

Pharmacy desert, complex regimen, cost, or another factor โ€” named, not just scored.

3

Adjust and prescribe with confidence

Choose a different pharmacy, simplify the regimen, or route to support โ€” all before the script is sent.

Early results

In early pilot practices, prescribers using adherence predictions reported catching likely non-adherence before writing the prescription rather than after a fill was already missed.

*Illustrative pilot feedback formal outcomes data to follow.

Bring AI Adherence into your workflow

Included in EPCS + PDMP DRx, or available as an add-on for enterprise plans.

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