Impact of technology on healthcare workers

These innovative technologies are geared towards improving patient care, lowering healthcare costs, easing workflow as well as digitalization of health records. The implementation of these technologies has been faced with a myriad of challenges including complexity in the usage of some of the devices, both by the healthcare practitioners and the patients. From the healthcare workers perspective, implementation of technology is expected to reduce workload and improve data recording and retrieval of information. The healthcare workers are critical players in the healthcare sector and they have a central role to play in the implementation of new technology such as the responsibility to input patients’ data into a digital system. Kash et al. This study will be significant to the business practice, positive social change as well as a basis for future research.

Firstly, the policymakers and healthcare organizations will improve their understanding of how to best introduce and implement technology in order to get a positive responsive approach from the healthcare workers. The leaders will also have an evidence-based approach of handling challenges associated with negative impact of change initiative and how best align the organisation’s practices with the interests of the employees. Consequently, the well-being of the workers which is attributable to the technology use may be improved. On the other hand, future research might use this study as a resource on understanding the challenges or success factors associated with technology implementation not only for the healthcare industry but all sectors. For instance, Hall, Fottrell, Wilkinson and Byass (2014) reviewed the effect of mobile-based technology, mHealth, implementation in the medium and low-income while considering the perceptions of the key stakeholders such as the patients and the healthcare workers.

They study findings revealed a positive association between the health intervention and improved patients’ outcomes, more accurate data gathering and improved support to the healthcare workers. The results support the findings of Aranda-Jan, Mohutsiwa-Dibe and Loukanova (2014) study which systematically reviewed the SWOT analysis of healthcare technology adoption in Africa. The study however cited a myriad of challenges such as poor assessment and cost and logistics issues as some of the factors that may hinder successful implementation of technology. Another critical innovation in the healthcare industry is the wearable technology. These assertions are supported by Greenlalgh et al. (2015) who concluded that lack of knowledge or limited awareness of the technology among the healthcare practitioners as one of the key hindrance to successful implementation of technology.

Healthcare workers are also often overwhelmed by the complexities of some technologies. Some cite lack of requisite skills as hindrances to technology implementation (Aranda-Jan et al. In addition, some technologies may not be adaptable or flexible which makes them prone to human error. (2015) points out that UTAUT applies four paradigms for understanding acceptance behaviours of individuals. These are facilitating conditions, social influence, effort expectancy and performance. Therefore, UTAUT provides a platform for leaders and policymakers to understand the psychology behind acceptance of technology in order to assess the likelihood of success when introducing new technologies in the workplace. On the other hand, Every Rogers’ 1995 innovation diffusion theory (IDT) aims at exploring how innovative ideas and technological advancements are absorbed and spread within the society (Wani and Ali, 2015).

Therefore, IDT is commonly used to test the rate of innovation uptake within the society. In addition, researchers address complex research questions by using the mixed methods approach, a combination of qualitative and quantitative (Taguchi, 2018). The limitations of the quantitative method make the mixed methods inappropriate for this study. Data Collection and Analysis The researcher will use secondary data relevant to the research problem to answer the research questions. According to Silverman (2016), secondary research involves the collection and analysis of already existing data to address the research objectives. This includes published research reports available in libraries, websites, government and non-government reports and already filled surveys. Qualitative methods are limited to a smaller sample size which may make the research findings not generalizable to different regions or sectors.

Therefore, the study is unlikely to provide solutions that may be generalized in other sectors outside the healthcare industry or even different stakeholders beyond the healthcare workers. In addition, secondary research is limited to the shortcomings of credibility of the readily available data which means that the success of the research will be based on the quality of the primary research. Furthermore, some reports may contain out-dated date, which may be accurate but not updated to the current setting. Timescale The researcher expects to complete the entire project and present within 4 months. Systematic Review on What Works, What does not Work and Why of Implementation of Mobile Health (mHealth) Projects in Africa. BMC Public Health, 14(1), pp. doi:10. 1186/1471-2458-14-188 Gao, Y.

, Li, H. What is Quality in Assisted Living Technology? The ARCHIE Framework for Effective Telehealth and Telecare services. BMC Medicine, 13(1), pp. doi:10. 1186/s12916-015-0279-6 Guérin, A. , Lebel, D. , Wilkinson,S. andByass, P.  (2014) Assessing the Impact of mHealth Interventions in Low- and Middle-income Countries – What has been shown to Work?.  Global Health Action, 7(1), pp.  doi: 10. IEEE Access, 3, pp. doi: 10. 1109/ACCESS. 2437951 Kash, B. A. , Sprenger, M. and Winter, R. Service Robots in Hospitals: New Perspectives on Niche Evolution and Technology Affordances. European Journal of Information Systems, 26(5), pp. doi:10. Assessing Scale-up of mHealth Innovations Based on Intervention Complexity: Two Case Studies of Child Health Programmes in Malawi and Zambia. Journal of Health Communication, 1, pp. Pyrczak, F. & Bruce, R. R. A. ,Nowakowski, E.