RxLocate AI: Smart Address Resolver – An AI-Powered Patient Identity Resolution Framework for Pharmacy Contact Centers
RxLocate AI is an original AI-assisted decision support framework designed to improve patient identity resolution within pharmacy contact center workflows. The framework introduces a non-invasive AI overlay capable of intelligently identifying the most likely patient address associated with an active prescription by combining prescription history, recency, confidence scoring, business rules, and Large Language Model (LLM) assisted reasoning. Unlike traditional approaches requiring modifications to legacy pharmacy systems, RxLocate AI operates as an intelligent browser-side assistant that integrates with existing workflows without backend changes. The concept demonstrates significant operational improvements including: • Up to 80% faster patient identity resolution• Approximately 20% reduction in Average Handle Time (AHT)• Higher First Call Resolution (FCR)• Improved Patient Satisfaction (CSAT)• Increased address selection accuracy• Enterprise-scale operational savings exceeding $500K annually for a 250-agent deployment The presentation also describes the conceptual architecture, AI workflow, technology stack, operational KPIs, deployment strategy, and future enhancement roadmap. This publication serves as a public disclosure of the original concept and establishes a timestamped record of authorship and prior art.
Authors
- Narayan Sonulkar (ORCID: https://orcid.org/0009-0007-2918-8309)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-06-27
- DOI
- https://doi.org/10.5281/zenodo.20990307
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00