Medical

Prescription Fill Records

Buy and sell prescription fill records data. NDC codes, fill dates, refill patterns, therapeutic switches — prescription data maps real-world drug usage at scale.

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Overview

What Is Prescription Fill Records Data?

Prescription fill records data captures the complete lifecycle of medication dispensing—from NDC codes and fill dates to refill patterns and therapeutic switches. This data reflects real-world drug usage at pharmacy and patient level, linking electronic health record prescriptions with actual pharmacy dispensing records. The data includes demographic context, timing metrics, and adherence indicators that show whether prescribed medications were actually filled and when. Pharmacy dispensing records are reconciled daily with patient charts and integrated into health systems through networks like Surescripts, which as of 2020 connects 96.5% of pharmacies in North Carolina and facilitates electronic prescription transmission. Researchers and commercial buyers use fill records to study medication adherence, identify patient-level factors affecting prescription completion, and track population-level drug utilization patterns across therapeutic categories.

Market Data

96.5%

Pharmacy Network Coverage (North Carolina)

Source: JMIR Medical Informatics

86%

Primary Health Care Provider Coverage (Durham, NC)

Source: JMIR Medical Informatics

1,254 patients

Study Population (Recent Psychotropic Analysis)

Source: JMIR Medical Informatics

Who Uses This Data

What AI models do with it.do with it.

01

Pharmacoepidemiology Research

Researchers link EHR prescribing data with pharmacy dispensing records to identify patient-level factors associated with medication receipt and adherence patterns, distinguishing between prescribed and actually-filled medications.

02

Medication Adherence Studies

Academic and health system researchers use prescription claims data to estimate refill adherence through cumulative medication acquisition and cumulative medication gap calculations, measuring both primary and secondary adherence.

03

Population Drug Utilization Tracking

Health plans, public health agencies, and pharmaceutical researchers track prescription-filling behavior patterns across populations to understand medication persistence, therapeutic switches, and real-world usage trends.

What Can You Earn?

What it's worth.worth.

Academic Research Access

Varies

Institutional researchers typically access through health system data agreements or pharmacy networks; pricing depends on data scope and exclusivity.

Commercial Dataset Licensing

Varies

Pharmacy networks and claims aggregators license dispensing data; pricing reflects patient volume, therapeutic coverage, and time period.

Real-Time Integration Access

Varies

Daily-updated pharmacy dispensing records integrated into EHR systems command premium pricing for timeliness and operational integration.

What Buyers Expect

What makes it valuable.valuable.

01

NDC Code Accuracy

Precise mapping of RxCUIs to NDCs accounting for package size, manufacturer, and strength variations; multiple NDCs for the same drug must be correctly reconciled.

02

Temporal Precision

Accurate fill dates with clear cutoff definitions for valid prescription-fill matches; data must capture the relationship between prescription date and actual dispensing date.

03

Demographic Context

Patient-level variables including age, sex, race/ethnicity, insurance status, and clinical indicators (BMI, deprivation indices) to enable stratified analysis of fill patterns.

04

Refill Pattern Documentation

Complete record of prescription refills, gaps between fills, and persistence metrics; data must support calculations of cumulative medication acquisition and cumulative medication gap.

Companies Active Here

Who's buying.buying.

Duke University Health System / DUHS

Operates research datamart reconciling EHR prescriptions with Surescripts pharmacy dispensing data; conducts pharmacoepidemiology studies linking prescribing with actual medication receipt across pediatric clinics.

Surescripts

Operates the largest US electronic prescription transmission network, collecting and aggregating daily pharmacy dispense data from major pharmacies and pharmacy benefit managers; provides reconciled fill records to health systems and researchers.

Kaiser Permanente

Conducts medication adherence and persistence research using prescription claims databases and electronic health record dispensing data for population health studies.

FAQ

Common questions.questions.

How do prescription fill records differ from prescription data alone?

Prescription data from EHR systems shows what doctors ordered, but fill records prove whether patients actually obtained the medication from a pharmacy. By linking both datasets using NDC codes and fill dates, researchers can identify primary adherence (whether initial prescriptions were filled) and secondary adherence (whether patients refilled ongoing medications).

What is an NDC code and why does it matter?

An NDC (National Drug Code) is a unique identifier for drug products including strength, form, and package size. Multiple NDCs can represent the same active ingredient from different manufacturers or package sizes, so accurate NDC-to-RxCUI mapping is critical for correctly matching prescriptions with pharmacy dispensing records.

How are prescription fill records updated?

Most major pharmacy networks like Surescripts receive daily pharmacy dispensing reports and integrate them into EHR systems for patient record matching. Data updates occur automatically upon scheduling of clinical encounters, enabling near-real-time reconciliation of prescriptions with fills.

What metrics can be calculated from fill records?

Key metrics include cumulative medication acquisition (total drug acquired over time), cumulative medication gap (periods without medication supply), refill intervals, therapeutic switches between drugs, and primary/secondary adherence rates. These enable detailed studies of medication persistence and real-world usage patterns.

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