Background Significant efforts have been made to develop artificial intelligence (AI) solutions for health care improvement. Despite the enthusiasm, health care professionals still struggle to implement AI in their daily practice. Objective This paper aims to identify the implementation frameworks used to understand the application of AI in health care practice. Methods A scoping review was conducted using the Cochrane, Evidence Based Medicine Reviews, Embase, MEDLINE, and PsycINFO databases to identify publications that reported frameworks, models, and theories concerning AI implementation in health care. This review focused on studies published in English and investigating AI implementation in health care since 2000. A total of 2541 unique publications were retrieved from the databases and screened on titles and abstracts by 2 independent reviewers. Selected articles were thematically analyzed against the Nilsen taxonomy of implementation frameworks, and the Greenhalgh framework for the nonadoption, abandonment, scale-up, spread, and sustainability (NASSS) of health care technologies. Results In total, 7 articles met all eligibility criteria for inclusion in the review, and 2 articles included formal frameworks that directly addressed AI implementation, whereas the other articles provided limited descriptions of elements influencing implementation. Collectively, the 7 articles identified elements that aligned with all the NASSS domains, but no single article comprehensively considered the factors known to influence technology implementation. New domains were identified, including dependency on data input and existing processes, shared decision-making, the role of human oversight, and ethics of population impact and inequality, suggesting that existing frameworks do not fully consider the unique needs of AI implementation. Conclusions This literature review demonstrates that understanding how to implement AI in health care practice is still in its early stages of development. Our findings suggest that further research is needed to provide the knowledge necessary to develop implementation frameworks to guide the future implementation of AI in clinical practice and highlight the opportunity to draw on existing knowledge from the field of implementation science.
Background Artificial intelligence (AI) for healthcare presents potential solutions to some of the challenges faced by health systems around the world. However, it is well established in implementation and innovation research that novel technologies are often resisted by healthcare leaders, which contributes to their slow and variable uptake. Although research on various stakeholders’ perspectives on AI implementation has been undertaken, very few studies have investigated leaders’ perspectives on the issue of AI implementation in healthcare. It is essential to understand the perspectives of healthcare leaders, because they have a key role in the implementation process of new technologies in healthcare. The aim of this study was to explore challenges perceived by leaders in a regional Swedish healthcare setting concerning the implementation of AI in healthcare. Methods The study takes an explorative qualitative approach. Individual, semi-structured interviews were conducted from October 2020 to May 2021 with 26 healthcare leaders. The analysis was performed using qualitative content analysis, with an inductive approach. Results The analysis yielded three categories, representing three types of challenge perceived to be linked with the implementation of AI in healthcare: 1) Conditions external to the healthcare system; 2) Capacity for strategic change management; 3) Transformation of healthcare professions and healthcare practice. Conclusions In conclusion, healthcare leaders highlighted several implementation challenges in relation to AI within and beyond the healthcare system in general and their organisations in particular. The challenges comprised conditions external to the healthcare system, internal capacity for strategic change management, along with transformation of healthcare professions and healthcare practice. The results point to the need to develop implementation strategies across healthcare organisations to address challenges to AI-specific capacity building. Laws and policies are needed to regulate the design and execution of effective AI implementation strategies. There is a need to invest time and resources in implementation processes, with collaboration across healthcare, county councils, and industry partnerships.
PurposeThe purpose of this paper is to contribute to the understanding of how talent management (TM) unfolds in practice in a public organization.Design/methodology/approachAn exploratory single case study was conducted of a Swedish public hospital, based on interviews, observations and documents.FindingsThe findings illustrate that despite a highly egalitarian and collectivist context, the hospital adopted an exclusive approach to TM, and a talent was not considered or identified through formal performance appraisals, but through informal criteria. The rationale behind this approach is influenced by the surrounding context, including the implementation of an innovative and strategically important practice, and the highly professionalized context.Research limitations/implicationsThe study offered a rich view of how TM unfolds in practice, which may not always be possible using large sample, survey studies; however, it limited the generalizability.Practical implicationsThe study points to important issues when designing TM.Originality/valueThe paper addresses two main shortcomings in the TM literature: the under-researched context of public organizations and the lack of contextual awareness. The empirically driven analysis constitutes an important step for further theory development regarding exclusive/inclusive approaches in TM.
Talent Management (TM) is a hot topic among both practitioners and scholars, but it still has to overcome some important limitations. Studies have been overly unitarist and managerialist in their orientation, and we still know little about how local contextual factors relate to TM, especially with regards to one of the most critical aspects of any TM system, i.e. talent identification. This research, which adopted a qualitative case study including data from interviews, observations and documents, studied how talent identification unfolded in practice at both the headquarters (HQ) and a subsidiary of a large Swedish organization. By drawing on the institutional logics perspective, we suggest that the way in which organizational actors conduct their talent identification is grounded in the logic they enact and make use of. Attention is thus focused on how the cultural norms, symbols and practices of different institutional orders are incorporated into the identification of talent. Having identified competing institutional logics at the HQ and the subsidiary, we also suggest that this is a credible explanation for the discrepancy between intended and actual HR practices. The findings are in contrast with previous research, which suggests that self-interest, ad hoc approaches, and a lack of skills nested in talent identification are underlying causes of differences in how talent identification is conducted. ARTICLE HISTORY
PurposeTwo research questions are asked in this paper: RQ1. How does line management involvement in PA work unfold in practice? RQ2. How does line management involvement contribute toward any divergence arising between intended and implemented PA work?Design/methodology/approachAn in-depth case study from a multi-actor perspective based on interviews with HR managers, line managers and employees, and organizational documents.FindingsThe findings illustrate how line managers faced three types of complexities during implementation, i.e. dilemmas, understandings, and local adaptations. These jointly contributed to a divergence arising between the PA as intended and the PA as implemented. This divergence became associated with how line management involvement was restricted to the local context and the initial stages of the PA process, highlighting how HR practices can contain both devolved and non-devolved elements.Originality/valueWe respond to calls for more in-depth qualitative studies of how line managers are involved in HR work; this is done specifically by conceptualizing the complexities line managers face in practice when implementing HR practices. As such, we add to the understanding of HR practices as relational and social in nature. We also contribute to the processual understanding of HRM by highlighting how HR practices can contain both devolved and non-devolved elements. By stressing the limitations of binary conceptualizations of HR devolution, we add to the understanding of HR devolution as more complex and multifaceted than traditionally assumed.
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