M-health infusion by healthcare practitioners in the national health services (NHS)☆
Highlights
► Develops a model to explain an individual's infusion of m-health technologies. ► Task, user and technology characteristics explain infusion of m-health technologies. ► Infusion of m-health technologies improves practitioners' performance. ► Infusing m-health technologies does not directly create knowledge. ► Infusing m-health technologies facilitate medical learning.
Introduction
In healthcare, organisations continually strive to improve patient care [30]. Information Technology (IT) is perceived as being an enabler of more efficient and effective healthcare delivery [15]. Yet, despite substantial research on IT implementation in the Information Systems (IS) and medical informatics fields, the healthcare industry remains a technological laggard [3] with a dearth of research focusing on how to infuse IT technologies into individuals' work practices in order to realise substantial benefits. The underlying premise behind this ‘lag’ is that information technologies are often under-utilised following adoption [19]. For instance, a study conducted in the Geneva University Hospital [48] with mobile handheld devices found that usage of the devices declined after the initial phase of implementation. It is therefore important to investigate post-adoption use of any technological innovation to fully appreciate long term success of IT technologies [41].
Cooper and Zmud [8] identify six stages of IT implementation. Analysis of the literature pertaining to implementation of mobile technologies (Table 1) reveals that extant research predominately focuses on the first five stages. Stage six—namely, infusion—remains one of the least studied facets of IT post-adoption, not only in the mobile literature but also in the generic IS literature ([32], [45]). Infusion is a distinctive feature in the Cooper and Zmud [8] model, which reflects the extent to which an IT technology is fully embedded in an individual's work system [10].
Organisations worldwide invest heavily in the implementation of technological innovations. Engagements in Swedish e-health initiatives cost the healthcare sector approximately €700 million annually [29]. If such technological innovations are not infused within an individual's work practice, technology will ultimately fail, as individuals do not realise the full potential of a technological innovation through comprehensive and integrated use. Consequently, such technological innovations may deliver only limited benefits. These limited benefits, according to [40], may not compensate for what is usually a costly and difficult implementation process.
Section snippets
Infusion of m-health technologies
The application of mobile technologies within healthcare, namely mobile-health or m-health, has revolutionised the delivery of healthcare services as mobile technologies support the provision and capture of patient-related information at the point-of-care [4]. In this study an m-health technology refers to “any mobile handheld device and applications which run on that device to support the user” [34].
The documented potential of m-health technologies is widely purported. These include how
Conceptual model development
In developing a conceptual model to explore determinants and outcomes of m-health infusion, pertaining to individuals, the researchers identified and analysed a number of existing models pertaining to infusion (e.g. [40], [21], [37], [52]). However analysis of existing infusion models revealed their unsuitability for investigating individual infusion, with such models primarily focused on infusion of technologies at an organisational level. For example, organisational readiness, external
Conceptual model and construct definition
An analysis of the m-health infusion literature revealed four key technology characteristics which have an impact on m-health infusion (Table 2). Adapted from [1], [14], technology characteristics refer to specific features, functionality, or usability of a technology that can affect its infusion by target users. These characteristics have been shown to influence other phases of IT implementation but have received little attention in the infusion literature.
Infusion distinguishes itself from
Research methodology
The objective of this research is to explore the infusion of m-health technologies among medical practitioners and the resultant impact of infusion on knowledge creation and individual performance. The case study approach is one of the most commonly used research methods in the IS field ([2], [9]). It aims to obtain an in-depth understanding of the phenomenon and its context [5]. Case studies enable researchers to investigate pre-defined phenomena without explicit control or manipulation of any
Findings and discussions
This section presents the findings of this study and discusses its implications for the a priori conceptual model. Findings reveal that the conceptual model developed from extant literature is limited in explaining infusion of m-health technologies by individuals and by extension individual performance. Therefore, a revised model is derived and presented (Figure 2).
Extant literature characterised the factors which impact upon m-health infusion as being technological characteristics. Analysis
Emergent categories
Two additional categories emerged from the coding process including task characteristics and user characteristics. Table 3 provides an overview of our findings in terms of the emergent determinants and their associated category.
Technology characteristics
Medical practitioners indicate that system quality dimensions such as availability, technology maturity and portability of m-health technologies are pertinent for individual infusion. Each dimension is discussed in more detail in the subsequent sections.
User characteristics
Various medical practitioners interviewed indicate that content quality dimensions such as traceability—considered as “Big Brother like”—is important for delivering healthcare services. Attitudes towards this ‘Big Brother Surveillance’ ranged from “it scares me” (nurse) to “I think when you are looking after people you got to be a bit ‘Big Brother’—you got to be tight” (dietician). Comments from one nurse indicate that the “only thing that makes me as diligent as I am of using it, is a scare
Task characteristics
Three dimensions are discussed in this section namely, time-criticality, interdependence and mobility.
Extent of infusion
This section will discuss integrative and exploratory use (infusion). Analysis revealed that individual users utilise the m-health technology at various levels of sophistication. As a result, the revised model will now merge integrative and exploratory use into ‘extent of infusion’. The following section will discuss our findings relating to infusion.
Results indicate that integrative use is dominant at the infusion phase of m-health technology implementation. Medical practitioners use the
Individual performance
This section will discuss the outcomes of m-health infusion. Analysis revealed that individual performance is significantly improved through the infusion of m-health technologies. However, findings revealed that infusion of m-health technologies did not enhance individual’s knowledge. The following section will discuss our findings relating to these outcomes.
Several categories of benefits emerged from the analysis associated with individual performance through infusion of m-health technologies.
Conclusion
Mobile technologies have been increasingly incorporated into medical practitioners' work practices. Yet actual infusion of such technologies has tended to lag, and the potential benefits of m-health technologies have not been fully realised. This paper develops a model to explain an individual’s infusion of m-health technologies and has implications for both theory and practice. This study identifies three categories (task characteristics, user characteristics and technology characteristics)
Acknowledgement
This research was partially funded by Business Information Systems, Conference Travel Support Scheme, University College Cork, Health Information Systems Research Centre (HISRC), and by the Science Foundation Ireland (SFI) SFI"11/RFP.1/CMS/3338.
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Funding. This research was partially funded by Business Information Systems, Conference Travel Support Scheme, University College Cork, Health Information Systems Research Centre (HISRC), and by the Science Foundation Ireland (SFI) SFI"11/RFP.1/CMS/3338.