In this study, the concept of electronic health records is used to describe applications for manipulating and processing any information, of an individual, that resides in electronic systems for the purpose of providing health care and health related services [1
]. Based on this, some examples of information systems that might have an impact on the improvement of health services and that can be considered as electronic health records are: computerized physician prescription, computerized physician order entry, electronic medical records, electronic alerts, automated decision support, and electronic capture of clinical data that enables service quality improvement. Physicians have a central role in the use of electronic health records, as they are who provide much of the information that the systems handle in their automated processes.
These systems have been widely diffused in the medical domain, not only for the reduction in costs of information and communication technology, but also for supporting physicians tasks in three directions: 1) reducing medical error rates [2
]; 2) supporting decision making activities [2
]; and 3) incrementing cost-benefit ratio and improving the quality of health services [2
]. Nevertheless, it has been reported that low adoption levels of electronic health records exist [2
]. Based on Rogers [9
], the term adoption refers to making the decision to make full use of an innovation (in this case electronic health records) as the best course of action available, in this paper we will use the term in that sense. The problem with the adoption of electronic health records is dramatic, for example, for 2010 it has been projected for the USA a value close to 50% in their adoption rate [2
]. Such rate might negatively affect the quality and cost of the health services in this country.
Adoption studies can be grouped in a more general theory called diffusion of innovations, as proposed by Rogers [9
], which helps to explore and explain why some new technologies spread faster and wider than others. In this theory, an innovation is an idea, practice, or object that is perceived as new by an adoption unit (e.g. an individual or an organization). The existing literature on adoption studies is mainly oriented towards two aspects: 1) the identification of the perceptions and attitudes towards information and communication technology, and 2) the identification of the characteristics of technology and its adopters. From our literature review, we found very few proposals [11
] intended to support and promote, in an automatic manner by means of proactive technology, the adoption of electronic health records; furthermore, some of the proposed solutions were not related to the medical domain [12
]. Since we want to provide automated means to support and promote the adoption of electronic health records in the latter domain, the last aspect is very important because the medical domain has a very particular organizational culture concerning the use of information systems; for instance, the habit of physicians continuously accessing information, or the way in which they request assistance to solve problems related to the use of technology. Like in other innovations, the adoption-decision process of electronic health records is based on knowledge; therefore in this paper we propose a knowledge-based taxonomy of the critical factors for adopting these systems. The proposed taxonomy is intended to be a guide for supporting the adoption process of the electronic health records with the assistance of information and communication technology. Our review differs from previous studies [13
] regarding the following elements:
• Domain: our main interest is the medical domain; the taxonomy is focused on this and takes into account its culture in the use of information systems. Some studies facilitate the understanding of successful adoption and the use of information systems, but such studies are not focused on the adoption of electronic health records [13
• Approach: our taxonomy is aimed towards a knowledge-based technology approach. Some studies propose critical factors for adopting electronic health records, but they do not recommend the elements for supporting their adoption by automatic means [15
• Study subjects: our taxonomy does address physician personnel. However, some work is oriented toward the medical domain, and is not focused on physicians, i.e. it is aimed at patients [16
], nurses [19
], or nations [17
The innovation-decision process, showed in Figure , is composed of five stages [9
]: the first stage is called knowledge, in which an individual, or a different adoption unit, has the first knowledge of an innovation; in the second stage, also known as persuasion, an individual forms an attitude towards the innovation; the third stage is called decision, this is critical because in this stage an individual decides, based on knowledge acquired in previous stages, to adopt or reject an innovation; in the fourth stage, implementation, an adoption unit implements an innovation; finally, in the stage of confirmation, an individual ratifies his decision to adopt or reject an innovation. As Rogers states [9
], knowledge is a critical element in the innovation-decision process, this process is an information-seeking and information-processing activity in which an adoption unit is motivated to reduce uncertainty about the advantages and disadvantages of an innovation.
Figure 1 The innovation-diffusion process proposed by Rogers .
On the other hand, technology can be used for creating, storing, distributing, and applying knowledge. Each one of these knowledge processes can be implemented with information and communication technology roles [20
] such as those presented in table ; e.g., data mining can be used for creating knowledge, whereas electronic bulletin boards can be utilized for knowledge distribution. Therefore, technology is an instrument that could be used to reduce uncertainty about an innovation [9
Information and communication technology roles in the knowledge management processes
According to all the latter, the aim of this review is to provide a taxonomy to identify the critical adoption factors of electronic health records, that can be supported by information and communication technology, in a proactive form, to assist the users of these systems during their adoption process. This taxonomy is based on a list of critical adoption factors of electronic health records, classified from a knowledge point of view (Figure ); where, as mentioned earlier, knowledge is an important element for decreasing the uncertainty towards them.
Using knowledge for supporting adoption of clinical information systems.
In this way, every critical adoption factor could be associated with one or several of the information and communication technology roles of the knowledge management processes (creation, storage, and/or distribution) to apply such knowledge for assisting the adoption of the electronic health records (Figure ).
Use of the critical adoption factors of clinical information systems to inform the development of systems for supporting its adoption process.