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Introduction

Information and Communication Technology (ICT) has been recognized as an essential tool in enhancing healthcare quality, accessibility and delivery. As a result, both public and private healthcare organizations are investing increasing amounts into the development of healthcare information technology (HIT) [1]. Nevertheless, a number of high-profile failures reveal the problems that arise when end-users will be required to cope with the loss of these systems. It is essential, therefore, to understand the determinants of HIT adoption readiness, as it is consequently necessary to know the theoretical models that have arisen addressing IT adoption [2] in order to determine or reach some normative frameworks, which may be used as guidelines for assessing the HIT adoption readiness of a healthcare facility. HIT readiness refers to the preparedness of healthcare institutions or communities for the anticipated change brought by programs related to ICT [3]. This preparedness was meant to help take stock of all relevant factors that have the potential to influence the outcome of the adoption in anyway.

Broadly, technology adoption and readiness have largely been studied at two levels: the individual [4–9]and the organization [10]. Most empirical studies on IT adoption at firm level are derived from the Diffusion of Innovation (DOI) theory and the Technology-Organization-Environment (TOE) framework and because the TOE framework includes the environment context (not included in the DOI theory), it becomes better able to explain intra-firm innovation adoption; therefore, they consider this model to be more complete [2]. As Ash [11], rightly pointed out, in the context of information technology (IT), whiles organizations can make a decision, the onus, however, lies with individuals within the organization to make independent decisions about adoption and usage; hence the need for health information technology implementers to train in managing organizational issues.

Technologically, TOE illustrates that adoption depends on the collection of technologies inside and outside a firm as well as the application’s perceived relative advantage, compatibility, complexity, trialability and observability [2,12]. These factors are identified based on the DOI theory [13]. Organizational context of TOE covers a firm’s business scope, top management support, organizational culture, complexity of managerial structure measured in terms of centralization, formalization, and vertical differentiation, the quality of human resource, and size related issues such as internal slack resources and specialization [12], [14]. Environmental context relates to facilitating and inhibiting factors in areas of operations [12].

DOI theory by Roger provides an essential theoretical platform for adoption research in several fields [13] and has popularly been used to examine organizational adoption of IS over the last two decades [2], [15]. The DOI found that individual characteristics, internal characteristics of organizational structure, and external characteristics of the organization are important antecedents to organizational innovativeness [2]. No single theory of innovation exists, nor does it seem likely one will emerge [16]. The closest the field has come to producing such theory is Rogers’ classical model of diffusion [13]. DOI is a theory of how, why, and at what rate new ideas and technology spread through cultures, operating at the individual and firm level [2]. It has a long history with contributions from sociologists, communication researchers, economists, organizational researchers, IT researchers, and many others [16]. Several studies including such as [11], [17], [18], [19], and [20] have combined DOI and technology-organization-environment (TOE) by Tornatzky and Fleischer [12].

The main aim of this systematic review was to offer a standard HIT adoption readiness assessment framework by 1) identifying readiness related studies; 2) analyze readiness factors and measuring tools; and 3) propose standard readiness assessment framework and recommendations.

Section snippets

Identification and extraction of data

Articles were searched using Medline/PubMed, Cinahl, Web of Science, PsychInfo, ProQuest and Google scholar. With these databases known for the publication of e-Health related work, all fields provided were searched. The following search phrases were applied in all databases. “e-Health readiness”, “health information technology (HIT) readiness assessment”, “IS/T readiness assessment”, “mHealth readiness assessment”, “readiness and implementation, EHR, EMR, e-Prescription”, “e-Readiness,

Results

The results have been grouped into two tables: Table 3: Readiness assessment factors and Table 4: tools used in measuring HIT/e-Health readiness assessment factors.

Discussion

From the included studies, we synthesized data and concepts/constructs discussed below.

In Table 3, Table 4 respectively below, we presented studies that focused on assessing the readiness of individuals and organizations and the factors used in the assessment. This is unlike the study conducted by Van Dyk [63] that largely based on the studies of Khoja, Scott [3] and Chipps and Mars [43]. There was a range of factors used in assessing readiness, some of which were overlapping with others. For

Conclusion

In this systematic review, we were able to bring together extensive studies relating to HIT readiness through multi-level method from which 63 full-text papers were reviewed in detail. Firstly, we organized a myriad of constructs/readiness assessment factors imaginably due to the evolving and the increasing complexity nature of HIT systems under divergent circumstances. We addressed the existing diverse and fragmentation in the existing literature in which various constructs and their measuring 

Author contribution

Salifu: Conception and Design; Data Extraction; Manuscript Writing; Final Approval of Manuscript.

Abdul: Conception and Design; Data Extraction; Manuscript Writing; Final Approval of Manuscript.

Jeffrey: Conception and Design; Data Extraction; Manuscript Writing; Final Approval of Manuscript.

Declaration of conflict of interest

None.

Summary points

What was known

• •Myriad e-Health readiness studies
• •Existing regular readiness assessment factors

What has been discovered

• •Existing e-Health readiness studies but fragmented literature
• •Lack of reliable measuring tools
• •The need for reliable measuring tools

Acknowledgement

The authors wish to acknowledge the support of the Australian Government Research Training Program (AGRTP).

References (91)