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1 – 3 of 3Salifu Yusif, Abdul Hafeez-Baig and Jeffrey Soar
This paper aims to validate an initially developed e-Health readiness assessment model.
Abstract
Purpose
This paper aims to validate an initially developed e-Health readiness assessment model.
Design/methodology/approach
The authors thematically analysed an initial qualitative data collected and used the outcome to develop survey instruments for this study. To collect the quantitative data, the authors used the drop and collect survey approach given the research setting. The quantitative data was analysed using factor and regression analyses of SPSS 23 in which hypotheses formulated were tested.
Findings
The results suggest that the model [R2 = 0.971; F (5, 214) = 1414.303], which is made up of readiness assessment factors (constructs) and measuring tools explain about 97% of the variance of the overall health information technology/e-Health adoption readiness at Komfo Anokye Teaching Hospital. The measuring tools were reliable for assessing the composite variables (constructs): technology readiness; operational resource readiness; organizational and cultural readiness; regulatory and policy readiness; and core readiness, which have significant influence on eHealth adoption readiness assessment..
Originality/value
This study has successfully validated empirically developed eHealth readiness assessment model with complete reliable indicators given that existing eHealth readiness assessment models have not been effective due to a general lack of standard indicators for measuring assessment factors. The study also contributes to the growing research on the adoption of information technology/systems in health-care environment using the Technology–Organization–Environment framework.
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Salifu Yusif, Abdul Hafeez-Baig and Jeffrey Soar
In Ghana, as with other developing countries, there are several health information technology (HIT) initiatives as interventions to improve healthcare delivery. HIT implementation…
Abstract
In Ghana, as with other developing countries, there are several health information technology (HIT) initiatives as interventions to improve healthcare delivery. HIT implementation undoubtedly results in change. However, most studies relating to HIT implementation readiness have constantly neglected the role of change in successfully implementing HIT. This study intends to identify factors affecting successful change management as part of preparation towards successfully implementing HIT in public hospital in Ghana. To carry out this study, we conducted in-depth interviews with a matrix of HIT senior managers and thematically analyzed the data. The data was transcribed and uploaded into a Nvivo 11 software for analysis using thematic analysis techniques. Five (5) themes were discovered. They are: 1) Stakeholder participation; 2) Proof of experience in similar project; 3) Availability of committed change agents/all-levels-change representatives; 4) Clearly articulated change implementation strategy; and 5) Training and improvement mechanism (post-implementation). A fresh call is made for more attention to be paid to change as part of preparatory measures towards the adoption of HIT in Ghana using the five cardinal approaches identified as a guide.
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Dana Abdullah Alrahbi, Mehmood Khan, Shivam Gupta, Sachin Modgil and Charbel Jose Chiappetta Jabbour
Health-care knowledge is dispersed among different departments in a health care organization, which makes it difficult at times to provide quality care services to patients…
Abstract
Purpose
Health-care knowledge is dispersed among different departments in a health care organization, which makes it difficult at times to provide quality care services to patients. Therefore, this study aims to identify the main challenges in adopting health information technology (HIT).
Design/methodology/approach
This study surveyed 148 stakeholders in 4 key categories [patients, health-care providers, United Arab Emirates (UAE) citizens and foresight experts] to identify the challenges they face in adopting health care technologies. Responses were analyzed using exploratory (EFA) and confirmatory factor analysis (CFA).
Findings
EFA revealed four key latent factors predicting resistance to HIT adoption, namely, organizational strategy (ORGS); technical barriers; readiness for big data and the internet of things (IoT); and orientation (ORI). ORGS accounted for the greatest amount of variance. CFA indicated that readiness for big data and the IoT was only moderately correlated with HIT adoption, but the other three factors were strongly correlated. Specific items relating to cost, the effectiveness and usability of the technology and the organization were strongly correlated with HIT adoption. These results indicate that, in addition to financial considerations, effective HIT adoption requires ensuring that technologies will be easy to implement to ensure their long-term use.
Research limitations/implications
The results indicate that readiness for big data and the IoT-related infrastructure poses a challenge to HIT adoption in the UAE context. Respondents believed that the infrastructure of big data can be helpful in more efficiently storing and sharing health-care information. On the technological side, respondents felt that they may experience a steep learning curve. Regarding ORI, stakeholders expected many more such initiatives from health-care providers to make it more knowledge-specific and proactive.
Practical implications
This study has implications for knowledge management in the health -care sector for information technologies. The HIT can help firms in creating a knowledge eco-system, which is not possible in a dispersed knowledge environment. The utilization of the knowledge base that emerged from the practices and data can help the health care sector to set new standards of information flow and other clinical services such as monitoring the self-health condition. The HIT can further influence the actions of the pharmaceutical and medical device industry.
Originality/value
This paper highlights the challenges in HIT adoption and the most prominent factors. The conceptual model was empirically tested after the collection of primary data from the UAE using stakeholder theory.
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