This research questions how the use of a hospital app affords patient engagement because it recognizes the lack of understanding of healthcare technology affordances that lead to patient engagement. Drawing affordance theory, this study first measures affordances by considering feature use patterns and the needs to use the features that engaged patients show in the use of a hospital app. Further, this study aims to show how affordances are actualized and how the affordances interact with each other to enhance patient engagement. This short paper explains the methods of computational analytics to achieve these goals. Computational analytics results reveal patients' and clinicians' feature use and their needs that are used to measure affordances from empirical data, event logs and conversation texts between patients and clinicians. This work contributes to affordance literature by deepening an understanding of mechanisms of affordance actualization and actualized affordances to desired outcomes.