Enhancing medical information retrieval: Re-engineering the tala-med search engine for improved performance and flexibility.

Abstract

Objective: Accessing reliable medical information online in Germany is often hindered by misinformation and low health literacy. Tala-med, an ad-free search engine, was developed to provide curated, expert-reviewed content with filters for trustworthiness, recency, user-friendliness, and comprehensibility. This study re-engineered the original system to overcome technical limitations while maintaining result consistency. Methods: A modular architecture was designed using Elasticsearch, a fastText-based synonym system, and a subZero-powered admin interface. The system was evaluated using 214 unique queries to compare performance and result similarity with the legacy version. Results: The new implementation improved query processing speed while preserving result consistency. Synonym handling was enhanced using fastText, and system maintainability increased via a centralized database and modular backend. The administrative interface simplified data updates and configuration tasks. Conclusion: The re-engineered tala-med search engine maintains the original system's strengths while enabling greater scalability, flexibility, and future extensibility. The open-source platform offers a foundation for advancing domain-specific search systems and supports applications beyond the medical field.