Patient-reported outcome measures (PROMs) are essential tools for capturing patients’ perceptions of their health status. However, these questionnaires can be lengthy and cumbersome, as multiple assessments are required to evaluate various domains of a patient’s well-being.

The aim of this study is to develop a prediction model that uses free-text data to predict scores across multiple existing validated questionnaires. A representative sample of the Singapore population will be recruited, and free-text responses will be analyzed using machine learning techniques and mapped to their corresponding questionnaire scores.