Rogers’ Adoption Theory: Understanding New Technology Integration

The present report outlines the use of Rogers’ (2003) theory during an upcoming meeting with a group of nurses that is aimed at facilitating the implementation of a new electronic health records system (EHR) in their hospital. The nurses are reported to be rather reluctant to adopt the new EHR, but the specifics of their concerns are not clear yet. It is planned to assess nurses’ perceptions, provide nurses with the information on the specifics of the new EHR and future training, and involve nurses in scheduling the training while managing the attributes of innovation as suggested by Rogers (2003) to improve the process of adoption.

The Application of Rogers’ Theory

In the development of the future meeting, the theory of innovation diffusion by Rogers (2003) is going to be used. In particular, Rogers (2003) suggests that people can perceive innovations as possessing certain attributes, which can be grouped into the features of relative advantage, compatibility, complexity (simplicity), trialability, and observability (pp. 15-16). Evidence shows that relative advantage, observability, and trialability have a statistically significant impact on one’s attitude towards a change; compatibility, complexity, observability, and trialability were proved to affect the process of the adoption of innovation, predicting its outcome (Pashaeypoor, Ashktorab, Rassouli, & Alavi-Majd, 2016). Thus, the framework appears to be valid in the context of current change.

Attribute Analysis and Action Planning

The first attribute suggested by Rogers (2003) is that of relative advantage, which defines the perceived value of the new EHR as compared to the previously employed one. Rogers (2003) points out that the advantages can be determined from different perspectives, including those related to saved costs, convenience, prestige, and others. In this respect, it appears logical to provide the nurses with an extensive overview of the specifics of the new EHR. The advantages (or instance, improved coordination or more extensive provider support) need to be emphasized. However, if the system has disadvantages, they should not be omitted because the knowledge of issues may be useful for managing other attributes.

The second attribute is the perceived compatibility of change, which depends on its consistency with “the existing values, past experiences, and needs of potential adopters” (Rogers, 2003, p. 15). It is noteworthy that the use of an EHR should be in line with nurses’ values since the primary reason for its adoption is the improvement of care and patient safety (Bates, 2010; Boswell, 2011). However, there can be other compatibility problems, including those related to personal characteristics (Hsiao, Chang, & Chen, 2011), which is why it is important to gather nurses’ perspectives and concerns and address them directly.

It may be not possible to complete the assessment during one meeting, but the meeting can be used to launch the process. For example, it might be discovered that the nurses are concerned with using a different interface. This problem can be addressed through the demonstration of the advantages of the new interface or by scheduling a training session devoted to the investigation of the changes.

A similar strategy would help to manage the third attribute, simplicity (complexity). Rogers (2003) suggests that innovations that are perceived as difficult are likely to be adopted slower. As a result, nurses’ perceptions should be assessed again to discover their view of the complexity or simplicity of the innovation and its features. During the meeting, the assessment is unlikely to be completed, but it can be used to offer the nurses an opportunity to be engaged in managing the training schedule. As a result, the schedule will be modified in the process of the work with more time allocated for the features that are described by the nurses as difficult to learn.

Such a step can make the process of training more collaborative, which increases its chances to be successful (Boswell, 2011). The reasons for the perceived difficulty can be discussed as well: for instance, if the nurses are not very self-sufficient computer users, this factor can increase the perceived complexity of the innovation (Hsiao et al., 2011), but additional training in computer literacy might help to reduce it. Thus, the nurse facilitator needs to determine and address perceived issues rather than neglect them.

Apart from that, the innovation’s trialability can be used to manage nurses’ concerns. Rogers (2003) defines trialability as the possibility of experimenting with the innovation, that is, applying it to a limited extent. Rogers (2003) explains that high trialability reduces uncertainty and, therefore, decreases resistance and facilitates adoption. Indeed, the nurses would be expected to be uncertain about the specific features of the innovation, which may affect their perceptions and concerns. However, the promise of a trial period for the use of EHR can ease the nurses’ anxiety and resistance to change, especially if they are worried about any aspects that require some time to get used to (for example, the interface).

Observability of an innovation depends on the visibility of its results. In other words, if the nurses can witness the positive outcomes of adopting the new EHR in the process of adoption, this process is likely to speed up (Rogers, 2003). While the results of the adoption of the new EHR cannot be visible before its implementation, there exists substantial evidence that EHR is capable of improving quality and safety and reducing costs (Bates, 2010; Boswell, 2011).

Therefore, if the facilitator offers sufficient proof that the EHR has shown positive results in another hospital or that it is expected to do so in this one because of its advantageous features, the nurses might consider this innovation observable. Thus, by highlighting EHR’s positive features and addressing perceived disadvantages, which are to be determined through the assessment of nurses’ perceptions, the meeting can be used to reduce uncertainty and resistance and improve the nurses’ attitudes to the innovation.

Nurses’ Role in Leading Change: A Conclusion

All the activities that are proposed for the meeting can be theoretically explained. Indeed, the assessment of the nurses’ perceptions is crucial because, as Rogers’ (2003) theory suggests, perceived attributes of innovation affect the attitudes of the nurses and the success of the future adoption process. The availability of relevant materials and information improves the nurses’ perceptions of innovation, which justifies the educational measures of the proposed plan (Hsiao et al., 2011).

Also, Boswell (2011) points out that collaboration is typically perceived as an important activity for successful implementation of innovation (including EHR), which justifies the engagement of the nurses in the scheduling process. Moreover, Hughes (2017) suggests that nursing leadership is inclusive, shared, which means that nurse engagement should empower them to take the lead in the innovation. Hughes (2017) suggests that nurses are particularly suited for the roles of change agents and leaders since they have the necessary skills and competence while being the most numerous group in the healthcare community (p. 83).

As a result, the empowerment of nurses to lead mobilizes a significant amount of resources and applies them to the adoption process, which should predict its success. Thus, the upcoming meeting is very important, and if it is managed successfully, it can significantly improve the attitudes of the nurses, which should positively affect the results of the future training and the adoption of the new EHR.

References

Bates, D. W. (2010). Getting in step: Electronic health records and their role in care coordination. Journal of General Internal Medicine, 25(3), 174–176.

Boswell, R. A. (2011). A physician group’s movement toward electronic health records: A case study using the transtheoretical model for organizational change. Consulting Psychology Journal: Practice and Research, 63(2), 138–148.

Hsiao, J., Chang, H., & Chen, R. (2011). A study of factors affecting acceptance of hospital information systems: A nursing perspective. Journal of Nursing Research, 19(2), 150–160.

Hughes, F. (2017). Nurses are the voice to lead. Journal of Nursing Management, 25(2), 83-84.

Pashaeypoor, S., Ashktorab, T., Rassouli, M., & Alavi-Majd, H. (2016). Predicting the adoption of evidence-based practice using “Rogers’ diffusion of innovation model”. Contemporary nurse, 52(1), 85-94.

Rogers, E.M. (2003). Diffusion of innovations (5th ed.). New York, NY: Free Press.

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