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Due to its ability to support well-informed decision-making, business intelligence (BI) has grown in popularity among executives across a range of industries. However, given the volume of data collected in health-care organizations, there is a lack of exploration concerning its implementation. Consequently, this research paper aims to investigate the key factors affecting the acceptance and use of BI in healthcare organizations.

Leveraging the theoretical lens of the “unified theory of acceptance and use of technology” (UTAUT), a study framework was proposed and integrated with three context-related factors, including “rational decision-making culture” (RDC), “perceived threat to professional autonomy” (PTA) and “medical–legal risk” (MLR). The variables in the study framework were categorized as follows: information systems (IS) perspective; organizational perspective; and user perspective. In Jordan, 434 healthcare professionals participated in a cross-sectional online survey that was used to collect data.

The findings of the “structural equation modeling” revealed that professionals’ behavioral intentions toward using BI systems were significantly affected by performance expectancy, social influence, facilitating conditions, MLR, RDC and PTA. Also, an insignificant effect of PTA on PE was found based on the results of statistical analysis. These variables explained 68% of the variance (R²) in the individuals’ intentions to use BI-based health-care systems.

To promote the acceptance and use of BI technology in health-care settings, developers, designers, service providers and decision-makers will find this study to have a number of practical implications. Additionally, it will support the development of effective strategies and BI-based health-care systems based on these study results, attracting the interest of many users.

To the best of the author’s knowledge, this is one of the first studies that integrates the UTAUT model with three contextual factors (RDC, PTA and MLR) in addition to examining the suggested framework in a developing nation (Jordan). This study is one of the few in which the users’ acceptance behavior of BI systems was investigated in a health-care setting. More specifically, to the best of the author’s knowledge, this is the first study that reveals the critical antecedents of individuals’ intention to accept BI for health-care purposes in the Jordanian context.

The study aims to explore the utilisation of Clinical Decision Support (CDS) tools in Tanzanian healthcare facilities by identifying the tools used, the challenges encountered and the adaptive strategies employed by healthcare practitioners. It utilises an Activity Theory (AT) approach to understand the dynamic interactions between healthcare providers, CDS tools and the broader healthcare system.

The research adopts a qualitative approach in two prominent regions of Tanzania, Dar es Salaam and Dodoma. It involves semi-structured interviews with 26 healthcare professionals and key stakeholders across ten healthcare facilities, supplemented by document reviews. The study employs AT to analyse the interactions between healthcare professionals, CDS tools and the broader healthcare system, identifying best practices and providing recommendations for optimising the use of CDS tools.

The study reveals that Tanzanian healthcare practitioners predominantly rely on non-computerised CDS tools, such as clinical guidelines prepared by the Ministry of Health. Despite the availability of Health Information Systems (HIS), these systems often lack comprehensive decision-support functionalities, leading practitioners to depend on traditional methods and their professional judgement. Significant challenges include limited accessibility to updated clinical guidelines, unreliable infrastructure and inadequate training. Adaptive strategies identified include using non-standardised tools like Medscape, professional judgement and reliance on past experiences and colleagues’ opinions.

The investigation was constrained by access limitations because it was challenging to get some respondents to share information. However, a sufficient number of individuals participated in the interviews, and their knowledge was very beneficial in understanding the procedures and tools for clinical decision support.

This study contributes to AT by extending its application to a low-resource healthcare setting, uncovering new dimensions of the theory related to socio-cultural and technological constraints in healthcare facilities in Tanzania. It provides valuable insights into the practical barriers and facilitators of HIS and CDS tool implementation in developing countries, emphasising the need for context-specific adaptations, robust training programs and user-centred designs. The findings highlight the resilience and imagination of healthcare practitioners in adapting to systemic limitations, offering recommendations to enhance clinical decision-making and improve patient care outcomes in Tanzania.

This qualitative case study aims to identify and analyse the factors influencing the implementation and effectiveness of electronic health record systems (EHRS) in primary health-care (PHC) facilities in Tanzania. This study aims to explore ways to optimize the use of EHRS for better health-care service delivery.

The study uses a qualitative case study design. Data were collected through interviews and focus groups conducted with health-care workers and information and communication technology officers at the PHC facilities in Tanzania. Purposive sampling and data source triangulation were used to address potential biases and limitations associated with the study’s small sample size.

This study identifies several key findings related to the implementation and effectiveness of EHRS in Tanzanian PHC facilities. The primary obstacles include inadequate technical infrastructure, poor internet connectivity and insufficient financial resources. The study suggests a comprehensive strategy for improving EHRS, emphasizing patient and health-care professional involvement in system design, investments in technical infrastructure and connectivity, data quality and accuracy and ongoing technical support and training.

This research contributes to the existing body of knowledge by offering a nuanced understanding of the Tanzanian health-care context. It emphasizes the need for tailored solutions and strategies specific to the region’s challenges and opportunities. The study’s originality lies in its focus on EHRS in the Tanzanian context, providing valuable insights for future initiatives. A key policy implication underscores the importance of a supportive regulatory framework, dedicated resources and consistent stakeholder communication for successful EHRS implementation.

Online health question-and-answer (Q&A) forums have developed a new business model whereby listeners (peer patients) can pay to read health information derived from consultations between askers (focal patients) and answerers (physicians). However, research exploring the mechanism behind peer patients' purchase decisions and the specific nature of the information driving these decisions has remained limited. This study aims to develop a theoretical model for understanding how peer patients make such decisions based on limited information, i.e. the first question displayed in each focal patient-physician interaction record, considering argument quality (interrogative form and information details) and source credibility (patient experience of focal patients), including the contingent role of urgency.

The model was tested by text mining 1,960 consultation records from a popular Chinese online health Q&A forum on the Yilu App. These records involved interactions between focal patients and physicians and were purchased by 447,718 peer patients seeking health-related information until this research.

Patient experience embedded in focal patients' questions plays a significant role in inducing peer patients to purchase previous consultation records featuring exchanges between focal patients and physicians; in particular, increasingly detailed information is associated with a reduced probability of making a purchase. When focal patients demonstrate a high level of urgency, the effect of information details is weakened, while the interrogative form is strengthened.

The originality of this study lies in its exploration of the monetization mechanism forming the trilateral relationship between askers (focal patients), answerers (physicians) and listeners (peer patients) in the business model “paying to view others' answers” in the online health Q&A forum and the moderating role of urgency in explaining the mechanism of how first questions influence peer patients' purchasing behavior.

Artificial intelligence (AI) has received much attention due to its promethean-like powers to transform the management and delivery of public sector services. Due to the proliferation of research articles in this context, research to date is fragmented into research streams based on different types of AI technologies or a specific government function of the public sector (e.g. health, education). The purpose of this study is to synthesize this literature, identify challenges and opportunities, and offer a research agenda that guides future inquiry.

This paper aggregates this fragmented body of knowledge by conducting a systematic literature review of AI research in public sector organisations in the Chartered Association of Business Schools (CABS)-ranked journals between 2012 and 2023.

The search strategy resulted in the retrieval of 2,870 papers, of which 61 were identified as primary papers relevant to this research. These primary papers are mapped to the ten classifications of the functions of government as classified by the Organisation for Economic Co-operation and Development (OECD), and the reported challenges and benefits aggregated.

This study advances knowledge by providing a state-of-the-art of AI research based the OECD classifications of government functions, reporting of claimed benefits and challenges and providing a research agenda for future research.

In the recent post-pandemic era, the globe has been anxious for the sustainable disposal of healthcare waste to protect public health, protect the environment and enhance future preparedness. Developing countries, in particular, have struggled to dispose of healthcare waste (HCW) to eradicate the hazardous effects of medical waste generated during and after the deadly COVID-19 pandemic. Hence the purpose of the research paper is to develop a hybrid decision-making framework to identify various barriers for sustainable disposal of healthcare waste use of Grey-Decision Making Trial and Evaluation Laboratory (G-DEMATEL) and Analytical Network Process (ANP).

A hybrid framework of Grey-Decision Making Trial and Evaluation Laboratory (G-DEMATEL) and Analytical Network Process (ANP) has been used to rank barriers and sub-barriers in the disposal of healthcare waste.

The study’s findings suggest that lack of segregation practices, absence of green procurement policy, obsolete technologies and resistance to adopting change management are the topmost causal barriers influencing the remaining barriers. Lack of commitment among healthcare administrations, lack of standard performance measures and resistance to adopting change appear to be the topmost crucial barriers.

The study’s finding enables all stakeholders to prioritize the barriers systematically for better performance and save resources during the process. The policymakers can use the results to design a clear regulatory framework.

The literature has highlighted the factors and their association with the disposal of healthcare waste mainly in isolation. The results are validated against the Grey-Analytical Hierarchy Process (G-AHP) to ensure the robustness of the proposed framework. This paper is one of the preliminary attempts to propose a framework of the interrelationships of the factors that have a direct role in survival for management education.

Health care organizations’ decision-making for the future relies on anticipating changes. Reliable predictions are becoming increasingly difficult, creating anxiety and requires long-term adaptive planning to cope with unforeseen circumstances. The purpose of this study is to gain insights into the awareness of uncertainties that decision makers in healthcare have, particularly when making long-term investments.

This is a qualitative study with an explorative purpose. The data were collected through semi-structured and open interviews with board members of long-term care organizations.

The study revealed that respondents are most uncertain about the future financing of their real estate system. Another concern revealed is about the shortage of care professionals combined with an increasing demand for future care. Despite most decision makers do recognize uncertainties during the decision-making process, decision makers hardly address the level of these uncertainties. Although this study did find that some decision makers are aware of deep uncertainties, in terms of “unknown unknowns,” they have no actual approaches for dealing with such situations.

Decision makers at healthcare organizations are uncertain as to their ability to anticipate technological, economic, social and political developments, as well as predict future healthcare system transformations. Some decision makers are aware of deep uncertainties, in terms of “unknown unknowns” and “unidentified unknowns,” but they lack an actual approach to deal with such situations. This study examines how strategies adapt to unforeseen developments or how to deal with deep uncertainties in healthcare as complex adaptive system.

The purpose of this paper is to understand how digital interventions are mediating the identity work of community health workers (CHWs) in the context of two African countries.

This paper analyzes the everyday work of CHWs in two low- and middle-income country (LMIC) contexts (Uganda and Malawi) and seeks to understand changes in collective identity and the role of Information and Communication Technologies (ICTs) in mediating this “identity work”. As CHWs conduct their everyday tasks of care giving, data reporting and maintaining social interactions, they play two primary roles. One is the care giving role oriented towards the community, and two, is reporting and administrative work by virtue of them being affiliated with the Ministry of Health, either in formal or voluntary capacity. The ambivalence which they experience as they move back and forth between these two worlds of work is significantly now mediated through ICTs. The paper analyzes these dynamics and identifies three key sets of ambivalence in identity work: (1) role embracing-institutional distancing; (2) conformist-resistant and (3) dramaturgical-transformative. The paper makes unique contributions to information systems (IS) and ICT for development (ICT4D) studies in that it focuses on a nonprofessional group, which plays a fundamental role in providing care to underserved populations and also conducts data work which provides the foundation of the national health information system. This contrasts with dominant research in the field which focuses on professional groups, largely based in Western business organizations.

The paper identifies identity related tensions that emerge with the mediation of digital technologies in the work world of CHWs. These include tensions of conformist-resistant; and (3) dramaturgical-transformative. These findings are relevant and unique to the field of IS and ICT4D studies in that it focuses on a nonprofessional group, which plays a fundamental role in providing care to underserved populations and also conducts data work which provides the foundation of the national health information system.

While acknowledging identity construction and negotiation is a function of both work and social lives, in this paper we could only focus on the work lives.

As digital interventions in the health sector of low and middle income countries is becoming increasingly widespread, often the focus is more on the supply side (the supply of the technology) rather than on the demand side (users experiences and aspirations). Identity becomes a lens to understand these demand side dynamics, which helps provides practical guidance on implementation approaches to ensure that the technology adds value to user work processes and there is a seamless and not a disruptive transition.

CHWs are the most neglected cadre in the health system of low and middle income countries, even though they provide the cutting edge in care provision work to the most marginalized populations, living in rural and underserved areas. By focusing on how technologies can be more effectively implemented to support these care processes, the paper provides important social implications both for practice and research.

Analysis of identity construction and negotiation of informal groups in the unorganized sector of low and middle income countries has not received adequate attention in IS research. The paper seeks to fill this important gap.

The study explores how Taiwan’s electronic health data systems can be used to build algorithms that reduce or eliminate medical errors and to advance precision medicine.

This study is a narrative review of the literature.

The body of medical knowledge has grown far too large for human clinicians to parse. In theory, electronic health records could augment clinical decision-making with electronic clinical decision support systems (CDSSs). However, computer scientists and clinicians have made remarkably little progress in building CDSSs, because health data tend to be siloed across many different systems that are not interoperable and cannot be linked using common identifiers. As a result, medicine in the USA is often practiced inconsistently with poor adherence to the best preventive and clinical practices. Poor information technology infrastructure contributes to medical errors and waste, resulting in suboptimal care and tens of thousands of premature deaths every year. Taiwan’s national health system, in contrast, is underpinned by a coordinated system of electronic data systems but remains underutilized. In this paper, the authors present a theoretical path toward developing artificial intelligence (AI)-driven CDSS systems using Taiwan’s National Health Insurance Research Database. Such a system could in theory not only optimize care and prevent clinical errors but also empower patients to track their progress in achieving their personal health goals.

While research teams have previously built AI systems with limited applications, this study provides a framework for building global AI-based CDSS systems using one of the world’s few unified electronic health data systems.

Artificial intelligence (AI) can help in defining preventive strategies in taking decisions in complex situations. This paper aims to research how workers might deal with intervening AI tools, with the goal of improving their daily working decisions and movements. We contribute to deepening how workers might deal with intervening AI tools aiming at improving their daily working decisions and movements. We investigate these aspects within a field, which is growing in importance due to environmental sustainability issues, i.e. waste management (WM).

This manuscript intends to (1) investigate if AI allows better performance in WM by reducing social security costs and by guaranteeing a better continuity of service and (2) examine which structural change is required to operationalize this predictive risk model in the real working context. To achieve these goals, this study developed a qualitative inquiry based on face-to-face interviews with highly qualified experts.

There is a positive impact of AI schemes in helping to detect critical operating issues. Specifically, AI potentially represents a tool for an alignment of operational behaviours to business strategic goals. Properly elaborated information, obtained through wearable digital infrastructures, allows to take decisions to streamline the work organization, reducing potential loss due to waste of time and/or physical resources.

Being a qualitative study, and the limited extension of data, it is not possible to guarantee its replication and generalizability. Nevertheless, the prestige of the interviewees makes this research an interesting pilot, on such an emerging theme as AI, thus eliciting stimulating insights from a deepening of information coming from respondents’ knowledge, skills and experience for implementing valuable AI schemes able to an align operational behaviours to business strategic goals.

The most critical issue is represented by the “quality” of the feedback provided to employees within the business environment, specifically when there is a transfer of knowledge within the organization.

The study focuses on a less investigated context, the role of AI in internal decision-making, particularly, for what regards the interaction between managers and workers as well as the one among workers. Algorithmically managed workers can be seen as the players of summarized results of complex algorithmic analyses offered through simpleminded interfaces, which they can easily use to take good decisions.