| Sumario: | The secondary use of clinical data has been widely studied, addressing many challenges in conducting observational studies. However, the complexity of dataset structures and detailed data requirements has led researchers to develop user-friendly query builders, enabling medical researchers to define cohorts more efficiently across the datasets. Although these tools simplify the workflow, their learning curve can sometimes be steep. Motivated by improving the usability to conducted observational studies, we propose a modular conversational assistant framework that would address these limitations. It can be integrated in any web application as an javascript component, improving the system usability. Additionally, the proposed framework would employ deterministic algorithms to reduce computational overhead. The system would enable integration into existing medical information systems through configuration files rather than code modifications. Validation within the OHDSI ecosystem would demonstrate practical applicability for real-world observational research scenarios.
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