Factors related to the adoption of the Brazilian National Immunization Program Information System

BACKGROUND: One way to optimize the adoption and use of technological innovations is to understand how those involved perceive, assess and decide to use them. This study aims to analyze the attributes that influence the adoption and use of the Brazilian National Immunization Program Information System (NIPIS) from the perspective of vaccination room workers. METHODS: This is a mixed method research, and a quantitative cross-sectional analytical study, with concomitant triangulation of data, carried out in a region of Brazil by using the Diffusion of Innovation Theory. We used a questionnaire with 183 nursing professionals who work at vaccination rooms in 12 municipalities. To test the research model, partial least squares structural equation modeling (PLS-SEM) and SmartPLS 2.3.0 have been applied to estimate the model. The qualitative research had a descriptive-exploratory character, using interviews (n = 18) analyzed through thematic analysis. RESULTS: The model proposed showed a mean correlation between the perceived attributes in the adoption and use of NIPIS. The results of the multiple regression indicated that the attributes “relative advantage” and “image” have a significant effect at 5% level (T > 1.97), positively influence the adoption and use of NIPIS; the attribute “voluntary use” negatively influences the adoption and use of the system; the attributes “experimentation”, “compatibility”, “profitability”, and “ease of use” did not influence the adoption and use of NIPIS. Emphasis has been placed on aspects that weaken the adoption and use of NIPIS such as lack of good quality internet and resistance to use the technology by some professionals. Workers perceive the importance of NIPIS for the municipality and point out that technological innovation provides data at an individual level, inserted in real time, which makes it possible to assess vaccination coverage. Lack of an unstable internet compromises data release due to system slowness. CONCLUSIONS: The mixed method allowed an in-depth analysis of the adoption and use of NIPIS in the Western Health Macroregion of Minas Gerais State, and similarities were observed in the results. The attribute “relative advantage” is the one that most influences the adoption and use of NIPIS, which is the strongest predictor of innovation adoption rate.