The aim of this study was to construct a model for patient engagement integration in perinatal eHealth development and quality assurance. The model was developed in four phases. The first three phases produced evidence for the development of a model. In the final phase, a qualitative interpretive synthesis was conducted using grounded theory to articulate a patient engagement model composed of three steps.

The first phase was a scoping review aimed at describing the nature and range of patient engagement from the perspective of access, personalization, commitment, and therapeutic alliance within perinatal eHealth. A narrative synthesis was used to describe findings. Phase two consisted of two studies exploring engagement practices of pregnant users during their use of a self-monitoring health promotion eHealth system. A descriptive comparative analysis was completed to understand user engagement patterns based on physical use of the wearable device. A mixed-methods convergence evaluation was conducted to understand the process of accessing the health promotion eHealth system. In phase three a process evaluation tool for parent participation and collaboration (in the neonatal intensive care unit) was developed and psychometrically tested.

For the interpretive synthesis, articles from the first three phases of this study were purposively sampled. A deductive codebook was developed using Donabedian’s model, and an adapted version of Lewin’s Action Research Cycle. Donabedian’s model consists of quality assurance through the examination of structure, process, and outcomes. Lewin’s Action Research Cycle informs iterative steps in development and implementation of health systems. Phase four resulted in a model for patient engagement integration in perinatal eHealth development and quality assurance. Three steps of the model were identified as being: Person-centered Perinatal eHealth program mapping; Process evaluation through monitoring of patient engagement processes; and Co-creation of perinatal eHealth programs through real-life testing of perinatal eHealth systems.