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Within the context of a research program on the most relevant discourse types in chronic care medical encounters, this contribution reports on a qualitative study on the role caregivers play within the process of shared understanding occurring between health-care professionals and elderly patients. The purpose of the paper is to highlight one dimension of such complexity, by bringing to light the challenges connected to the achievement of shared understanding between health-care professionals and elderly patients when caregivers are involved in the conversation.

The paper reports on a two-step analysis of a corpus of transcripts of interactions in diabetes and hypertension settings. In the first step, caregivers’ contributions to deliberative sequences have been analyzed. In the second step, the analysis was extended to caregivers’ contributions to the whole encounter.

The results show that professionals’ ability to engage caregivers in deliberations during the encounter and, more generally, to assign a role to caregivers as legitimate participants in the consultation may favor the smooth development of the interaction and an effective process of shared understanding among all participants.

The paper further develops original research about the functions of the argumentative component in dialogues occurring in clinical settings.

The aim of this paper is to understand if service innovation (Helkkula et al., 2018), based on artificial intelligence (AI) systems, may guarantee healthcare service ecosystem (H-SES) well-being (Frow et al., 2019; Beirão et al., 2017), taking into account that many doubts relieved in terms of transparency may compromise the patients' perceived quality of health services provided through AI systems.

A literature review on service innovation, detected in terms of value co-creation, and service ecosystem, investigated in terms of well-being, is drawn. To analyze the implications of service innovation on a H-SES well-being, through the technology acceptance degree and predisposition to use by actors, a case study based on TAM-model 3 determinants as categories is carried out.

AI-based service innovation archetypes in healthcare may be considered as antecedents of the service ecosystem well-being conditions as long as they enable actors to co-create value. To make it possible, a patient-driven service innovation is necessary in order to mitigate the risks of its inactivity due to fears in terms of transparency.

Service innovation and service ecosystem well-being may be studied in an integrated way, with a multidisciplinary approach, and are linked by value co-creation, because only thanks a patient-driven service innovation is possible to foster service ecosystem well-being in healthcare.

Society is critically dependent on an adequate supply of hospital doctors to ensure optimal health care. Voluntary turnover amongst hospital doctors is, however, an increasing problem for hospitals. The aim of this study was to systematically review the extant academic literature to obtain a comprehensive understanding of the current knowledge base on hospital doctor turnover and retention. In addition to this, we synthesise the most common methodological approaches used before then offering an agenda to guide future research.

Adopting the PRISMA methodology, we conducted a systematic literature search of four databases, namely CINAHL, MEDLINE, PsycINFO and Web of Science.

We identified 51 papers that empirically examined hospital doctor turnover and retention. Most of these papers were quantitative, cross-sectional studies focussed on meso-level predictors of doctor turnover.

Selection criteria concentrated on doctors who worked in hospitals, which limited knowledge of one area of the healthcare environment. The review could disregard relevant articles, such as those that discuss the turnover and retention of doctors in other specialities, including general practitioners. Additionally, being limited to peer-reviewed published journals eliminates grey literature such as dissertations, reports and case studies, which may bring impactful results.

Globally, hospital doctor turnover is a prevalent issue that is influenced by a variety of factors. However, a lack of focus on doctors who remain in their job hinders a comprehensive understanding of the issue. Conducting “stay interviews” with doctors could provide valuable insight into what motivates them to remain and what could be done to enhance their work conditions. In addition, hospital management and recruiters should consider aspects of job embeddedness that occur outside of the workplace, such as facilitating connections outside of work. By resolving these concerns, hospitals can retain physicians more effectively and enhance their overall retention efforts.

Focussing on the reasons why employees remain with an organisation can have significant social repercussions. When organisations invest in gaining an understanding of what motivates their employees to stay in the job, they are better able to establish a positive work environment that likely to promote employee well-being and job satisfaction. This can result in enhanced job performance, increased productivity and higher employee retention rates, all of which are advantageous to the organisation and its employees.

The review concludes that there has been little consideration of the retention, as opposed to the turnover, of hospital doctors. We argue that more expansive methodological approaches would be useful, with more qualitative approaches likely to be particularly useful. We also call on future researchers to consider focussing further on why doctors remain in posts when so many are leaving.

Building upon the practice-based framework, this paper aims to focus on working practices for understanding how knowledge is transferred among health-care professionals within hospitals.

Using an ethnographic and interpretative approach, the authors conducted preliminary research based on a quali-quantitative methodology within one of the largest hospitals in Southern Italy.

This study allowed to achieve several results that could be significant and relevant within the health-care sector. First, this paper identified some of the main working practices and their associated activities in health care. Moreover, this paper identified the main organizational forms and/or tools enabling hospital personnel to share and learn the various types of knowledge for each of the prior identified practices.

Hospital managers should develop strategies and policies that take into account the nature and typology of knowledge-sharing processes among health-care professionals in terms of practices.

The paper contributes to practice-based studies identifying identified some of the main working practices, as well as the main tools for sharing and learning of the various types of knowledge.

The purpose of this study is to examine the role of artificial intelligence (AI) in transforming the healthcare sector, with a focus on how AI contributes to entrepreneurship and value creation. This study also aims to explore the potential of combining AI with other technologies, such as cloud computing, blockchain, IoMT, additive manufacturing and 5G, in the healthcare industry.

Exploratory qualitative methodology was chosen to analyze 22 case studies from the USA, EU, Asia and South America. The data source was public and specialized podcast platforms.

The findings show that combining technologies can create a competitive advantage for technology entrepreneurs and bring about transitions from simple consumer devices to actionable healthcare applications. The results of this research identified three main entrepreneurship areas: 1. Analytics, including staff reduction, patient prediction and decision support; 2. Security, including protection against cyberattacks and detection of atypical cases; 3. Performance optimization, which, in addition to reducing the time and costs of medical procedures, includes staff training, reducing capital costs and working with new markets.

This study demonstrates how AI can be used with other technologies to cocreate value in the healthcare industry. This study provides a conceptual framework, “AI facilitators – AI achievers,” based on the findings and offer several theoretical contributions to academic literature in technology entrepreneurship and technology management and industry recommendations for practical implication.