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Improving Online Pharmacy Refills Through Data-Driven Patient Engagement

A large regional hospital network sought to modernize its pharmacy refill process and reduce reliance on manual phone requests. Leadership recognized that to promote patient use of the existing online refill portal, they needed to consolidate fragmented prescription data and establish a reliable analytics foundation. With cleaner, trusted data, the organization aimed to streamline patient outreach, encourage digital self-service, and improve overall medication continuity.

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Improving Online Pharmacy Refills Through Data-Driven Patient Engagement
Business Challenges

Business Challenges

The organization operated on a fragmented, legacy ERP environment that hindered real-time visibility, created excessive manual workloads, and blocked scalability needed to support continued growth.

Fragmented Legacy Data : Prescription, inventory, and patient communication systems were disconnected, making it difficult to provide real-time, unified information to the web portal.
High Operational Burden : Pharmacy teams were spending significant time managing routine refill calls, limiting availability for clinical consultation and higher-value tasks.
Patient Hesitancy Toward Digital Tools : Past inconsistencies in online data created mistrust among some patients and slowed adoption of digital refills.
Gaps in Adherence Support : Without timely prompts or reminders, some patients missed optimal refill windows, impacting medication adherence.
Success Metrics
Success Metrics

Success Metrics

increase in web-based refill requests
reduction in administrative phone call volume
improvement in measured medication adherence indicators
Key Highlights

Highlights & Technology Stack

Key Highlights
Data Engineering
Cloud Data Warehousing
Data Analytics
Technology Stack
Snowflake
dbt (data build tool)
dbt (data build tool)
Apache Airflow
Python
Solutions

Solutions

We built a modernized data platform centered on Snowflake to store and manage high-volume pharmacy and prescription data. Apache Airflow was used to orchestrate ingestion pipelines from multiple legacy systems, ensuring consistent and dependable data flow. Using dbt, we implemented transformation and validation layers that standardized prescription data and calculated patient-level metrics such as days of supply remaining and refill readiness. These curated models powered automated outreach workflows that nudged patients ahead of refill lapses, along with Looker dashboards that gave leadership visibility into digital adoption, call volumes, refill timing, and patient engagement trends. This framework enabled both operational staff and patient-facing teams to make data-informed decisions and support patients more proactively.

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