New Integrated Model Approach to Understand the Factors That Drive Electronic Health Record Portal Adoption: Cross-Sectional National Survey.

Abstract

The future of health care delivery is becoming more patient-focused, and electronic health record (EHR) portals are gaining more attention from worldwide governments that consider this technology as a valuable asset for the future sustainability of the national health care systems. Overall, this makes the adoption of EHR portals an important field to study. The aim of this study is to understand the factors that drive individuals to adopt EHR portals. We applied a new adoption model that combines 3 different theories, namely, extended unified theory of acceptance and use of technology, health belief model, and the diffusion of innovation; all the 3 theories provided relevant contributions for the understanding of EHR portals. To test the research model, we used the partial least squares causal modeling approach. We executed a national survey based on randomly generated mobile phone numbers. We collected 139 questionnaires. Performance expectancy (beta=.203; t=2.699), compatibility (beta=.530; t=6.189), and habit (beta=.251; t=2.660) have a statistically significant impact on behavior intention (R²=76.0%). Habit (beta=.378; t=3.821), self-perception (beta=.233; t=2.971), and behavior intention (beta=.263; t=2.379) have a statistically significant impact on use behavior (R²=61.8%). In addition, behavior intention (beta=.747; t=10.737) has a statistically significant impact on intention to recommend (R²=69.0%), results demonstrability (beta=.403; t=2.888) and compatibility (beta=.337; t=2.243) have a statistically significant impact on effort expectancy (R²=48.3%), and compatibility (beta=.594; t=6.141) has a statistically significant impact on performance expectancy (R²=42.7%). Our research model yields very good results, with relevant R² in the most important dependent variables that help explain the adoption of EHR portals, behavior intention, and use behavior.