A Governed NL-to-SQL Architecture for Reliable Clinical Data Querying and Outpatient Schedule Monitoring

The deployment of natural-language-to-SQL (NL-to-SQL) systems in primary healthcare requires more than accurate query generation: it also requires governed data access, robustness to local terminology, and reliable handling of ambiguous user requests. This study evaluated a pilot proof-of-concept integrating a Spanish-language NL-to-SQL assistant with a governed, read-only outpatient scheduling repository derived from the Rayen information system used in a Centro de Salud Familiar (CESFAM) setting in Renca, Chile. The data used by the prototype were accessed through an external company responsible for data management in this context. The prototype was implemented with MindsDB as an artificial intelligence (AI)-enabled database layer and operated on anonymized, delayed secondary scheduling data. Evaluation was conducted through a Slack interface using 252 audited interactions from 42 users, with six assigned interactions per user and up to three exchanges per interaction. SQL correctness reached 240/252 (95.2%), whereas both query correctness and answer correctness reached 144/252 (57.1%). These findings suggest that governed pilot deployment for outpatient schedule monitoring may be feasible under controlled institutional conditions, while indicating that the main remaining barriers are semantic rather than purely syntactic, specifically ambiguity handling, institution-specific operational language, and faithful answer verbalization. The study therefore contributes deployment-oriented pilot evidence and clarifies where operational Spanish NL-to-SQL remains fragile under real institutional constraints.