Reporting health data in waiting rooms with mobile technology: Patient expectation and confirmation

Hospitals and medical staff use digital devices such as mobile phones and tablets to treat patients. Prior research has examined patient-reported outcomes, and the use of medical devices to do diagnosis and prognosis of patients, but not whether patients like using, and intend to use in future, mobile devices to self-report medical data. We address this research gap by developing a theoretical model based on the expectancy confirmation model (ECM) and testing it in an empirical study of patients using mobile technology to self-report data.

This study adopts a non-interventional cross-sectional research design. Randomly-selected patients provided data via survey and physical measurements. The target population comprises adults visiting a healthcare laboratory to get their blood drawn.

We surveyed 190 randomly-selected patients waiting for treatment in the clinic. They were surveyed at two points in time - before and after their blood was drawn - on their demographic characteristics, research variables concerning their use of mobile devices to provide medical information, and perceived clinical data (blood pressure, height and weight). The research model was tested using structural equation modeling.

The study found strong support for the research model, with seven of eight hypotheses being supported. Both self-disclosure effort and feedback expectation positively affect both perceived feedback quality and confirmation. Contrary to expectations, perceived feedback quality was not found to affect confirmation. Perceived feedback quality, along with confirmation, was found to positively affect satisfaction, which was found to affect intention to disclose medical data through mobile technology.

The study's findings support the proposed path from feedback expectation and self-disclosure effort to confirmation to satisfaction to disclosure intention. Although perceived feedback does not affect confirmation, it affects satisfaction. Overall, we believe the results provide novel insights to both scientific research community and practitioners about using mobile technologies for self-reporting medical data.