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At the beginning of the 21st century, multiple and diverse social entities, including the public (consumers), private and nonprofit healthcare institutions, government (public health) and other industry sectors, began to recognize the limitations of the current fragmented healthcare system paradigm. Primary stakeholders, including employers, insurance companies, and healthcare professional organizations, also voiced dissatisfaction with unacceptable health outcomes and rising costs. Grand challenges and wicked problems threatened the viability of the health sector. American health systems responded with innovations and advances in healthcare delivery frameworks that encouraged shifts from intra- and inter-sector arrangements to multi-sector, lasting relationships that emphasized patient centrality along with long-term commitments to sustainability and accountability. This pathway, leading to a population health approach, also generated the need for transformative business models. The coproduction of health framework, with its emphasis on cross-sector alignments, nontraditional partner relationships, sustainable missions, and accountability capable of yielding return on investments, has emerged as a unique strategy for facing disruptive threats and challenges from nonhealth sector corporations. This chapter presents a coproduction of health framework, goals and criteria, examples of boundary spanning network alliance models, and operational (integrator, convener, aggregator) strategies. A comparison of important organizational science theories, including institutional theory, network/network analysis theory, and resource dependency theory, provides suggestions for future research directions necessary to validate the utility of the coproduction of health framework as a precursor for paradigm change.

Health in low-income countries has become associated with the provision of minimum guaranteed public health services though Essential Health Packages (EHPs). How far do EHPs deliver the human right to health for all? This study addresses this question through qualitative research into access to health care for vulnerable communities, using Malawi as a case study. This study shows that there are significant accountability gaps and perceptions of weak service provision in Malawi’s EHP in relation to some particularly marginalised (and stigmatised) groups that limit the right to health and the promise of “health for all”.

This study extends the body of qualitative work on EHPs in general and on Malawi in particular by exploring the perceptions of key stakeholders in relation to inclusivity and the delivery of health policies to particularly vulnerable groups. To do so, this study adopted an approach based on interpretive epistemologies (Scott, 2014). This study conducted largely unstructured interviews with a range of health stakeholders, speaking to stakeholders individually, rather than through focus groups due to the potentially sensitive nature of the topic.

The findings of this study are as follows: limited inclusion of civil society actors and local communities; local communities and local policymakers feel frustration with the gap between the promises of consultation in the EHP and the reality, and the difficulties of not having effective channels of communication; and exclusionary health practices for particularly vulnerable groups.

There are limitations based on the qualitative methodology, and in terms of the particularly vulnerable groups – the authors studied two such groups (people with disabilities and those who identify as LBTQ) but a wider survey of vulnerable groups is needed to extend and confirm the findings.

Greater attention to the health rights of vulnerable groups would improve access and services, even in the context of resource restrictions. This study suggests that a deeper engagement with human rights-based approaches would pay dividends in terms of increasing access to health in Malawi, even within the constraints of the EHP process. Furthermore, without this, there is the risk that discrimination and exclusion will become more embedded in health policies, rather than progressively minimised.

Without addressing these issues, there is the risk that discrimination and exclusion will become more embedded in health policies, rather than progressively minimised.

This paper makes an important contribution to the growing literatures on EHP in sub-Saharan Africa and Malawi in particular and to the importance of listening to stakeholder perceptions. It provides original data on stakeholder perspectives of the challenges associated with universalising health care in resource-constrained countries. To the best of the authors’ knowledge, it is one of the first papers to focus on the rights of disabled and LBTQ people in relation to EHPs.

The purpose of this study is to examine the corruption prevalent in the distribution of COVID-19 palliatives during the lockdown and movement restrictions in the country. This study seeks to analyse the current state of corruption in the distribution of COVID-19 palliatives and public health facilities in Nigeria while also providing a legal insight and strategic blueprint to combat corruption. To this end, this study will address the current legal framework for combating corruption and build upon this to formulate a working strategy for tackling corruption in the future.

Using a doctrinal legal research methodology, this study draws upon existing literature, tertiary data sources and information from the Nigeria Centre for Disease Control. The collected data is analysed and compared with current literature to identify key findings. Rent-seeking and utilitarian theories of the law were examined to guide this study. This study offers useful insights into combating corruption. The use of this method is justified, as it enhances the credibility of the findings on the importance of strategies for future emergencies. This legal research approach is consistent with the law and can be easily verified. The empirical aspect of this study involved a survey of multidimensional health-care and economic data set of 36 states in Nigeria plus the Federal Capital Territory on COVID-19 in Nigeria. A survey linearised regression model was estimated to determine the influence of government revenue and public health-care facilities in the control of the virus spread in Nigeria.

This study reveals the need for emphasis on the imperative of combating corruption in the distribution of COVID-19 palliatives and establishing economic resilience through transparent and accountable practices, supported by legal frameworks.

Rent-seeking and utilitarian theories of law are evaluated because of their impacts on combating corruption. The limitation of this study is the intricacy of gathering data on COVID-19 palliatives corruption in Nigeria because of secrecy and the absence of reliable data on the subject.

Estimating the exact number of stolen palliatives and their fiscal impact on Nigeria's economy proves to be a formidable task because of the covert nature of corruption. This study equips policymakers in Nigeria with a better understanding of the legal challenges posed by corruption in the health care sector and provides an effective strategy to combat it.

The lack of reliable data on the extent of palliative theft hinders the ability of lawmakers to enact effective legislation and strategies for combating corruption in the distribution of COVID-19 palliatives and addressing future emergencies in Nigeria. The policy implications of this study can assist policymakers in Nigeria and other countries in formulating measures to combat corruption in the distribution of COVID-19 palliatives and other future emergencies. Furthermore, it recommends the overhaul of anti-corruption laws and mechanisms in Nigeria to ensure effective measures against corruption.

In conclusion, this study contributes to knowledge by proposing a legal model centred on people's participation to enhance transparency and accountability in future palliative distribution processes. This study recommends legal strategies that can effectively address corruption in future emergencies or shocks. This study proposes a strategic blueprint to tackle corruption in the future. This blueprint includes an analysis of existing laws and regulations, as well as potential policy changes and legislative reform. This study also includes recommendations for improved enforcement and oversight mechanisms and for improved public awareness and education. As part of this, this study considers the potential for public–private partnerships to increase transparency and accountability in public health and health-care services.

This paper aims to explore the intricate relationship between artificial intelligence (AI) and health information literacy (HIL), examining the rise of AI in health care, the intersection of AI and HIL and the imperative for promoting AI literacy and integrating it with HIL. By fostering collaboration, education and innovation, stakeholders can navigate the evolving health-care ecosystem with confidence and agency, ultimately improving health-care delivery and outcomes for all.

This paper adopts a conceptual approach to explore the intricate relationship between AI and HIL, aiming to provide guidance for health-care professionals navigating the evolving landscape of AI-driven health-care delivery. The methodology used in this paper involves a synthesis of existing literature, theoretical analysis and conceptual modeling to develop insights and recommendations regarding the integration of AI literacy with HIL.

Impact of AI on health-care delivery: The integration of AI technologies in health-care is reshaping the industry, offering unparalleled opportunities for improving patient care, optimizing clinical workflows and advancing medical research. Significance of HIL: HIL, encompassing the ability to access, understand and critically evaluate health information, is crucial in the context of AI-driven health-care delivery. It empowers health-care professionals, patients and the broader community to make informed decisions about their health and well-being. Intersection of AI and HIL: The convergence of AI and HIL represents a critical juncture, where technological innovation intersects with human cognition. AI technologies have the potential to revolutionize how health information is generated, disseminated and interpreted, necessitating a deeper understanding of their implications for HIL. Challenges and opportunities: While AI holds tremendous promise for enhancing health-care outcomes, it also introduces new challenges and complexities for individuals navigating the vast landscape of health information. Issues such as algorithmic bias, transparency and accountability pose ethical dilemmas that impact individuals’ ability to critically evaluate and interpret AI-generated health information. Recommendations for health-care professionals: Health-care professionals are encouraged to adopt strategies such as staying informed about developments in AI, continuous education and training in AI literacy, fostering interdisciplinary collaboration and advocating for policies that promote ethical AI practices.

To enhance AI literacy and integrate it with HIL, health-care professionals are encouraged to adopt several key strategies. First, staying abreast of developments in AI technologies and their applications in health care is essential. This entails actively engaging with conferences, workshops and publications focused on AI in health care and participating in professional networks dedicated to AI and health-care innovation. Second, continuous education and training are paramount for developing critical thinking skills and ethical awareness in evaluating AI-driven health information (Alowais et al., 2023). Health-care organizations should provide opportunities for ongoing professional development in AI literacy, including workshops, online courses and simulation exercises focused on AI applications in clinical practice and research.

This paper lies in its exploration of the intersection between AI and HIL, offering insights into the evolving health-care landscape. It innovatively synthesizes existing literature, proposes strategies for integrating AI literacy with HIL and provides guidance for health-care professionals to navigate the complexities of AI-driven health-care delivery. By addressing the transformative potential of AI while emphasizing the importance of promoting critical thinking skills and ethical awareness, this paper contributes to advancing understanding in the field and promoting informed decision-making in an increasingly digital health-care environment.

A large number of studies indicate that coercive forms of organizational control and performance management in health care services often backfire and initiate dysfunctional consequences. The purpose of this article is to discuss new approaches to performance management in health care services when the purpose is to support innovative changes in the delivery of services.

The article represents cross-boundary work as the theoretical and empirical material used to discuss and reconsider performance management comes from several relevant research disciplines, including systematic reviews of audit and feedback interventions in health care and extant theories of human motivation and organizational control.

An enabling approach to performance management in health care services can potentially contribute to innovative changes. Key design elements to operationalize such an approach are a formative and learning-oriented use of performance measures, an appeal to self- and social-approval mechanisms when providing feedback and support for local goals and action plans that fit specific conditions and challenges.

The article suggests how to operationalize an enabling approach to performance management in health care services. The framework is consistent with new governance and managerial approaches emerging in public sector organizations more generally, supporting a higher degree of professional autonomy and the use of nonfinancial incentives.

The objective of this study is to examine developments in the discursive practice of non-financial reporting in the public healthcare sector. In doing so, the authors investigate how the main reform foci of productivity and quality are represented, with a specific focus on the patient.

Drawing on critical discourse analysis (CDA), the authors conduct a longitudinal study (2007–2018) of healthcare reporting foci across the five administrative regions responsible for public hospitals in Denmark. The study analyses sixty annual reports and draws on contemporary reform documents over this period. CDA enables a micro-textual analysis, combined with macro-insights and discussions on social practice.

The findings show complex webs of presentation strategies, but in particular two changes occur during the period. First, the patient is centred throughout but the framing changes from productivity and waiting lists to quality and dialogue. Second, in the first years, the regions present themselves as actively highlighting financial and quality concerns, which changes to a passive and indirect form of presentation steered by indicators and patient legislation enforced by central government. This enhances passivity and distance in healthcare regional non-financial reporting where the regions seek to conform to such demands. Simultaneously, however, the authors find a tendency to highlight very different local initiatives, which shows an attempt to go beyond a pure automatic mode of reporting found in earlier studies.

Responding to the literature on both healthcare and financial reporting, this study identifies novel links between micro-level texts and macro-level social practices, enabling insights into the potentially intertwined impacts of public-sector reporting. The authors offer insights into the complexity of the construction of non-financial reporting in the public sector, which has a wider impact and different intentions than private-sector reporting.

General Data Protection Regulation (GDPR) of the European Union (EU) was passed to protect data privacy. Though the GDPR intended to address issues related to data privacy in the EU, it created an extra-territorial effect through Articles 3, 45 and 46. Extra-territorial effect refers to the application or the effect of local laws and regulations in another country. Lawmakers around the globe passed or intensified their efforts to pass laws to have personal data privacy covered so that they meet the adequacy requirement under Articles 45–46 of GDPR while providing comprehensive legislation locally. This study aims to analyze the Malaysian and Saudi Arabian legislation on health data privacy and their adequacy in meeting GDPR data privacy protection requirements.

The research used a systematic literature review, legal content analysis and comparative analysis to critically analyze the health data protection in Malaysia and Saudi Arabia in comparison with GDPR and to see the adequacy of health data protection that could meet the requirement of EU data transfer requirement.

The finding suggested that the private sector is better regulated in Malaysia than the public sector. Saudi Arabia has some general laws to cover health data privacy in both public and private sector organizations until the newly passed data protection law is implemented in 2024. The finding also suggested that the Personal Data Protection Act 2010 of Malaysia and the Personal Data Protection Law 2022 of Saudi Arabia could be considered “adequate” under GDPR.

The research would be able to identify the key principles that could identify the adequacy of the laws about health data in Malaysia and Saudi Arabia as there is a dearth of literature in this area. This will help to propose suggestions to improve the laws concerning health data protection so that various stakeholders can benefit from it.

This paper delves into the ex ante rates of return demanded by the private sector in Indonesian public–private partnership (PPP) infrastructure projects and the manifold factors emanating from project attributes that can influence these rates.

This paper analyzes feasibility studies of 37 PPP projects across different sectors. The studies were carefully selected based on relevance, completeness and validity of data. The analysis uses statistical techniques, including Levene’s tests, t-tests, ANOVA tests, Cohen’s effect size and Pearson correlations, to explore differences in cost of capital and excess returns across various attributes.

Based on the statistical analysis, no significant difference exists between the excess return of 200 basis points (bps) and the equity excess return of 0 bps. This suggests that the eligibility criteria for PPP projects require an internal rate of return (IRR) equal to the weighted average cost of capital plus 200 bps or an equity IRR equal to the cost of equity. The variations in the tested variables among diverse project attributes do not exhibit statistically significant disparities, even though specific attributes display moderate to high effect sizes.

This paper represents one of the first attempts to examine the rates of return demanded by the private sector in the context of Indonesian PPP projects. It comprehensively explores the factors that influence these rates, drawing on insights derived from feasibility studies.

The purpose of this study is to provide a detailed demonstration of how artificial intelligence (AI) can be used to potentially generate valuable insights and recommendations regarding the role of accounting in addressing key sustainability-related issues.

The study offers a novel method for leveraging AI tools to augment traditional scoping study techniques. The method was used to show how the authors can produce recommendations for potentially enhancing organisational accountability pertaining to seasonal workers.

Through the use of AI and informed by the knowledge base that the authors created, the authors have developed prescriptions that have the potential to advance the interests of seasonal workers. In doing so, the authors have focussed on developing a useful and detailed guide to assist their colleagues to apply AI to various research questions.

This study demonstrates the ability of AI to assist researchers in efficiently finding solutions to social problems. By augmenting traditional scoping study techniques with AI tools, the authors present a framework to assist future research in such areas as accounting and accountability.