Background: Multiple attempts aimed at highlighting the relationship between big data analytics and benefits for healthcare organizations have been raised in the literature. The big data impact on health organization management is still not clear due to the relationship’s multi-disciplinary nature. This study aims to answer three research questions: a) What is the state of art of big data analytics adopted by healthcare organizations? b) What about the benefits for both health managers and healthcare organizations? c) What about future directions on big data analytics research in healthcare? Methods: Through a systematic literature review the impact of big data analytics on healthcare management has been examined. The study aims to map extant literature and present a framework for future scholars to further build on, and executives to be guided by. Results: The positive relationship between big data analytics and healthcare organization management has emerged. To find out common elements in the studies reviewed, 16 studies have been selected and clustered into 4 research areas: 1) Potentialities of big data analytics. 2) Resource management. 3) Big data analytics and management of health surveillance systems. 4) Big data analytics and technology for healthcare organization. Conclusions: In conclusion is identified how the big data analytics solutions are considered a milestone for managerial studies applied to healthcare organizations, although scientific research needs to investigate standardization and integration of the devices as well as the protocol in data analysis to improve the performance of the healthcare organization.

The integration of artificial intelligence (AI) in healthcare management marks a significant advance in technological innovation, promising transformative effects on healthcare processes, patient care, and the efficacy of emergency responses. The scientific novelty of the study lies in its integrated approach, combining systematic review and predictive algorithms to provide a comprehensive understanding of AI’s role in improving healthcare management across different contexts. Covering the period between 2019 and 2023, which includes the global challenges posed by the COVID-19 pandemic, this research investigates the operational, strategic, and emergency response implications of AI adoption in the healthcare sector. It further examines how the impact of AI varies across temporal and geographical contexts. The study addresses two main research objectives: to explore how AI influences healthcare management in operational, strategic, and emergency response domains, and to identify variations in the impact of AI on healthcare management based on temporal and geographical contexts. Utilizing an integrated approach, we compared various prediction algorithms, including logistic regression, and interpreted the results through SHAP (SHapley Additive exPlanations) analysis. The findings reveal five key thematic areas: AI’s role in enhancing quality assurance, resource management, technological innovation, security, and the healthcare response to the COVID-19 pandemic. The study highlights AI’s positive influence on operational efficiency and strategic decision making, while also identifying challenges related to data privacy, ethical considerations, and the need for ongoing technological integration. These insights provide opportunities for targeted interventions to optimize AI’s impact in current and future healthcare landscapes. In conclusion, this work contributes to a deeper understanding of the role of AI in healthcare management and provides insights for policymakers, healthcare professionals, and researchers, offering a roadmap for addressing both the opportunities and challenges posed by AI integration in the healthcare sector.

Background: Despite growing support for the private sector involvement in the provision of public health services in Low- and Middle-Income Countries (LMICs), a lack of clear information on the future of the provision of such services restricts the ability of managers and policy-makers to assess how feasible integration between public and private actors may be in these countries. This paper presents a systematic literature review which traces the dynamics and boundaries of public-private partnerships for the healthcare sector in LMICs. Methods: A total of 723 articles indexed in Scopus were initially submitted to bibliometric analysis. Finally, 148 articles published in several academic journals were selected for independent full-text review by two researchers. Content analysis was made in order to minimise mistakes in interpreting the findings of studies in the sample. Results: Public-private partnerships identified through the content analysis were categorised into four research areas: 1) Transfer of resources; 2) Co-production of health goods and services; 3) Governance networks; 4) Criteria for successful partnership development. Conclusions: The four main research areas supply suggestions for a future research agenda, and managerial and policy implications for partnerships in LMICs.

The concept of sustainable healthcare is the subject of an increasingly intense, captivating, forward-looking, yet sometimes still overly theoretical debate. The aim of this contribution is to analyze the current scenarios of ecological and digital transition in the healthcare sector, considering its high energy consumption. In particular, we adopt a holistic and convergent vision of the energy mix and its infrastructure, moving beyond the ideological dichotomy of energy sources. Renewable sources, digital innovations, and the circular economy are seen as playing key roles in the future of the energy sector. In this research, a mixed methodology was employed, combining a questionnaire consisting of 31 questions with semi-structured interviews conducted with the top management of a major player in the private healthcare sector located in southern Italy in 2023. Consequently, we examine the main macro-guidelines of technological development, encompassing enabling technologies, new business models, roles, and professional skills. Based on the analyses conducted, we provide some insights to inform governmental policies and industrial strategies in the near future. Digitalization represents an opportunity to enhance the efficiency of healthcare services, reducing waste and ensuring quality. For instance, digital healthcare solutions enable personalized care on a global scale and offer decision support systems that can enhance overall healthcare performance. However, to maximize the benefits of digital transformation, it is essential to integrate new technologies effectively and sustainably into the existing healthcare ecosystem. A promising example is telemedicine, which can help reduce carbon emissions by decreasing healthcare workers’ travel.