Abstract
In the healthcare system, operations managers (OMs) are leaders expected to ensure the services provided to healthcare users are comprehensive, efficient, cost-effective, and delivered in an equitable manner. Their leadership roles also entail driving the use and adoption of the latest healthcare technology to improve the services rendered.
Artificial intelligence (AI) has various benefits and is changing practice perspectives in public hospitals, compelling the health system to transform and merge with the digital world. The OMs must drive AI’s implementation in public hospitals as they are the unit leaders in this context. Thus, it was imperative to determine their understanding and acceptance of AI as it became evident that OMs in public hospitals still relapsed to manual paper-based systems. The main research question was: What are the most effective leadership strategies to facilitate the implementation of AI in a public healthcare system?
The researcher adopted a qualitative, exploratory, descriptive, contextual research design and a postmodern constructivist phenomenological research approach to answer the research question. The research strategy comprised six phases: (i) explored the concept of AI and its application and practices in healthcare systems from existing literature on AI, and how it is applied and practised in healthcare; (ii) explored various theories and models to facilitate change; (iii) explored and described the lived experience of OMs in applying their leadership strategies to implement AI using phenological inquiry; (iv) contrasted and evaluated the leadership strategies OMs applied to implement AI; (v) developed a conceptual framework as outlined by Dickoff et al., which acted as a point of reference for developing the most effective leadership strategies that OMs can apply to facilitate the implementation of AI; and (vi) evaluated the most effective leadership strategies using a panel of experts.
For phase three, a purposive sampling method was applied, seeking OMs permanently employed in the public hospital; qualified and registered as professional nurses with the South African Nursing Council; who were in a leadership role for two years or longer; who was responsible for a specific unit and had staff members
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reporting to them, and had exposure with AI in their various units. Twelve in-depth individual phenomenological interviews were conducted until data saturation was reached. To contrast and evaluate the leadership strategies (phase five), two focus groups were formed, selecting OMs who did not partake in the open in-depth individual phenomenological interviews. Focus group one comprised 14 participants, and focus group two had 13 participants. The most effective leadership strategies were also evaluated by a panel of management, research, and AI experts (12 experts participated).
A descriptive phenomenological data analysis process was followed for both open in-depth individual phenomenological interviews and focus groups. Findings suggested there is ambivalence in embracing AI in units, and three main themes emerged: i) positive experiences related to AI, ii) management and leadership processes in AI’s facilitation, and iii) challenges related to AI. The leadership strategies applied by OMs to implement AI were: use AI technologies to develop and sustain therapeutic working relationships; effective facilitation of the implementation of AI in the units to augment the existing processes and systems; and constructive management of challenges related to AI. Relevant literature was used to support the findings, from which a conceptual framework to facilitate the implementation of AI, and the most effective leadership strategies was developed.
A major contribution of the study is the conceptual framework to facilitate the implementation of AI developed from this study. It reflects the study’s significance and its original contribution. Ultimately, the most effective leadership strategies to facilitate the implementation of AI in a public hospital were developed.
The conceptual framework also outlines a clear pathway and trajectory, guiding how the most effective leadership strategies to facilitate the implementation of AI were developed and how they should be implemented and sustained to improve the healthcare system in a public hospital. The original contribution of this study and the recommendations for nursing practice, policy, research and nursing practice were also discussed in the last chapter of the study.