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Objective – The first wave of experiences of exemptions policies suggested that poverty-based exemptions, using individual targeting, were not effective, for practical and political economic reasons. In response, many countries have changed their approach in recent years – while maintaining user fees as a necessary source of revenue for facilities, they have been switching to categorical targeting, offering exemptions based on high-priority services or population groups. This chapter aims to examine the impact and conditions for effectiveness of this recent health finance modality.

Methodology/approach – The chapter is based on a literature review and on data from two complex evaluations of national fee exemption policies for delivery care in West Africa (Ghana and Senegal). A conceptual framework for analysing the impact of exemption policies is developed and used. Although the analysis focuses on exemption for deliveries, the framework and findings are likely to be generalisable to other service- or population-based exemptions.

Findings – The chapter presents background information on the nature of delivery exemptions, the drivers for their use, their scale and common modalities in low-income countries. It then looks at evidence of their impact, on utilisation, quality of care and equity and investigates their cost-effectiveness. The final section presents lessons on implementation and implications for policy-makers, including the acceptability and sustainability of exemptions and how they compare to other possible mechanisms.

Implications for policy – The chapter concludes that funded service- or group-based exemptions offer a simple, potentially effective route to mitigating inequity and inefficiency in the health systems of low-income countries. However, there are a number of key constraints. One is the fungibility of resources at health facility level. The second is the difficulty of sustaining a separate funding stream over the medium to long term. The third is the arbitrary basis for selecting high-priority services for exemption. The chapter therefore concludes that this financing mode is unstable and is likely to be transitional.

High quality health-care delivery is not only the governments’ responsibility but also every prisoner’s right. Health care in prison and, particularly, of Iranian prisoners is increasingly important topic because of the rising number of the prison population. This paper aims to explore health-care managers’ perspectives and experiences of prisons and the barriers to health-care delivery in Iranian prisons.

A qualitative research design was conducted in Iran from October 2018 to August 2019. The participants consisted of 51 health-care managers (50 men and one woman) from Iranian prisons. A combination of face-to-face (N = 42) and telephonic (N = 9) semi-structured interviews were used because of the geographical distribution of the respondents. The first part of the interview guide consisted of demographic characteristics, and the second part consisted of three main open ended-questions. Interviews were recorded and transcribed, and thematic descriptive analysis was used to interpret the data.

The barriers to health-care delivery in Iranian prisons were categorized into four main topics: human resources, financing, facilities and barriers related to the health-care delivery process. Data synthesis identified the following themes for barriers to human resources: barriers to human resources planning (with eight sub-themes); barriers to education (with three sub-themes); and motivational barriers (with seven sub-themes). Moreover, barriers to financing consisted of five sub-themes. The barriers to facilities consisted of barriers related to physical infrastructures (with two sub-themes) and barriers related to equipment (with six sub-themes). Finally, barriers to the health-care delivery process included the following themes: communication barriers (with six sub-themes); legal barriers (with five sub-themes); and environmental-demographic factors (with seven sub-themes).

Identifying the barriers to health-care delivery in Iranian prisons plays a critical role in the improvement of planning, decision-making and the health-care delivery process.

The theme of this volume is reorganizing health care delivery systems: problems of managed care and other models of health care delivery. The volume contains 11 papers, organized into four sections. The sections cover, in order, managed care issues and organizational features, special groups of patients and health issues, lessons from other countries, and broader policy concerns and health insurance reform. Issues of how to best organize a health care delivery system are not new, but the amount of interest in this topic in the U.S. (as well as in other countries) has grown in recent decades. Reorganizing health care delivery systems is a concern of many of the systems of the world, and this volume contains some papers from countries other than the U.S., although the majority of the papers do relate issues to the U.S. health care delivery system. While the majority of the papers in this volume relate to structural and organizational factors, the impact of individual patients is not neglected. One section focuses very much on more specialized groups of patients, and several other papers use surveys of patients or other individual level data as part of their discussion of these issues. Before discussing the specific papers briefly, it is useful to review some material about the organization of the health care delivery system, especially within the U.S. This includes some discussion of how issues of organization of care and special forms of delivering care such as managed care have become major issues in the U.S. health care system at this point in time.

Healthcare services in the USA have been described as being fragmented and uncoordinated. Integrated delivery systems are frequently promoted as being instrumental in efforts to improve the coordination of care and, thus, enhancing the quality of clinical care and patient services while ensuring optimum cost‐efficiencies. This study seeks to analyze and compare the performance of hospitals participating in highly integrated systems with non‐integrated hospitals based on outcome measures involving hospital performance.

The study compares the performance of 50 flagship hospitals participating in the most highly integrated delivery systems in the USA with a representative sample of non‐system hospitals utilizing one‐way analysis of variance. The comparative analysis was based on three key performance measures; clinical quality of medical care, patient satisfaction, and cost‐efficiency considerations.

The results of the review demonstrate that there is a statistically significant positive difference between the clinical quality performance of the highly integrated hospitals compared with the quality performance of non‐highly integrated facilities. No difference was identified between the two sample groups of hospitals for the performance measures related to patient satisfaction or cost‐efficiencies.

The study is an attempt to evaluate the implications and effectiveness of integration within the health care delivery system. It suggests that integrated delivery systems may provide the organization structure appropriate to help support and enhance the quality of clinical care for patients.

Bureaucracy to a large extent entrenches orderliness and productive means of achieving goals in both public and private organisations across the world. However, bureaucracy is not suitable in the management of hospitals due to its peculiar nature of operations. This study investigates the conundrum of bureaucratic processes and health-care service delivery in government hospitals in Nigeria.

The study surveyed 600 outpatients and attendees visiting tertiary and government hospitals in Nigeria using descriptive design to obtained data from the respondents. A research instrument, questionnaire, was used to gather data. Out of the 600 outpatients visiting the 20 hospitals in government and tertiary hospitals, 494 responses were returned from the attendees. The study employed random sampling strategy to collect the information.

The findings of this study were that service delivery in government hospitals were in adverse position on all the four constructs of bureaucratic dimensions as against quality of service delivery in hospitals in Nigeria. It discovered that bureaucratic impersonality cannot impact on the quality of service delivery in government hospitals in Nigeria. Separation and division of labour among health workers have no significant effect on quality service delivery in government hospitals. Formal rules and regulations (administrative procedure, rules, and policies) prevent quality service delivery in government hospitals in Nigeria. Also, patient’s waiting time was not significant to the quality of service delivery in government hospitals.

The results are constrained with dimensions of bureaucratic processes. Thus, the implication of this study is that bureaucracy in the Nigerian public hospitals is an unnecessary marriage which should be carefully separated and de-emphasised for quality service delivery in the hospitals to thrive.

Largely, this study is practical essential as it unearths the irrelevant operations procedure that hinder progress in Nigerian hospitals.

The study accomplishes recognised importance to survey how bureaucracy impedes quality service delivery in government hospitals. This study has provided a vital clue to elements that will bring rapid attention to patients’outcome in Nigerian hospitals and health-care facilities which hitherto has not been emphasised. The study has contributed to the existing body of knowledge associated to healthcare service quality in developing country.

Objective – Nepal's Safe Delivery Incentive Programme (SDIP) was introduced nationwide in 2005 with the aim of encouraging greater use of professional care at childbirth. It provided cash to women giving birth in a public health facility and an incentive to the health provider for each delivery attended, either at home or in the facility. We aimed to assess the impact of the programme on neonatal mortality and health care seeking behaviour at childbirth in one district of Nepal.

Methods – Impacts were identified using an interrupted time series approach, applied to household data. We estimated a model linking the level of each outcome at a point in time to the start of the programme, demographic controls, a vector of time variables and community-level fixed effects.

Findings – The recipients of the cash transfer in the programme's first two years were disproportionately wealthier households, reflecting existing inequality in the use of government maternity services. In places with women's groups – where information about the policy was widely disseminated – the SDIP substantially increased skilled birth attendance, but failed to impact on either neonatal mortality or the caesarean section rate. In places with no women's groups, the SDIP had no impact on utilisation outcomes or neonatal mortality.

Implications for policy – The lack of any impact on neonatal mortality suggests that greater increases in utilisation or better quality of care are needed to improve health outcomes. The SDIP changed health care seeking behaviour only in those areas with women's groups highlighting the importance of effective communication of the policy to the wider public.

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.

The COVID-19 pandemic stressed the health care sector's longstanding pain points, including the poor quality of frontline work and the staffing challenges that result from it. This has renewed interest in technology-centered approaches to achieving not only the “Triple Aim” of reducing costs while raising access and quality but also the “Quadruple Aim” of doing so without further squeezing wages and abrading job quality for frontline workers.

How can we leverage technology toward the achievement of the Quadruple Aim? I view this as a “grand challenge” for health care managers and policymakers. Those looking for guidance will find that most analyses of the workforce impact of technological change consider broad classes of technology such as computers or robots outside of any particular industry context. Further, they typically predict changes in work or labor market outcomes will come about at some ill-defined point in the medium to long run. This decontextualization and detemporization proves markedly problematic in the health care sector: the nonmarket, institutional factors driving technology adoption and implementation loom especially large in frontline care delivery, and managers and policymakers understandably must consider a well-defined, near-term, i.e., 5–10-year, time horizon.

This study is predicated on interviews with hospital and home health agency administrators, union representatives, health care information technology (IT) experts and consultants, and technology developers. I detail the near-term drivers and anticipated workforce impact of technological changes in frontline care delivery. With my emergent prescriptions for managers and policymakers, I hope to guide sectoral actors in using technology to address the “grand challenge” inherent to achieving the Quadruple Aim.

The adoption of electronic health records (EHRs) and digitization of health data over the past decade is ushering in the next generation of digital health tools that leverage artificial intelligence (AI) to improve varied aspects of health system performance. The decade ahead is therefore shaping up to be one in which digital health becomes even more at the forefront of health care delivery – demanding the time, attention, and resources of health care leaders and frontline staff, and becoming inextricably linked with all dimensions of health care delivery. In this chapter, we look back and look ahead. There are substantive lessons learned from the first era of large-scale adoption of enterprise EHRs and ongoing challenges that organizations are wrestling with – particularly related to the tension between standardization and flexibility/customization of EHR systems and the processes they support. Managing this tension during efforts to implement and optimize enterprise systems is perhaps the core challenge of the past decade, and one that has impeded consistent realization of value from initial EHR investments. We describe these challenges, how they manifest, and organizational strategies to address them, with a specific focus on alignment with broader value-based care transformation. We then look ahead to the AI wave – the massive number of applications of AI to health care delivery, the expected benefits, the risks and challenges, and approaches that health systems can consider to realize the benefits while avoiding the risks.

Integrated health care delivery (IHCD), as a major issue of managed care, was considered the panacea to rising health care costs. In theory it would simultaneously provide high-quality and continuous care. However, owing to the backlash of managed care at the turn of the century many health care providers today refrain from using further integrative activities. Based on transaction cost economics, this chapter investigates why IHCD is deemed appropriate in certain circumstances and why it failed in the past. It explores the new understanding of IHCD, which focuses on actual integration through virtual integration instead of aggregation of health care entities. Current success factors of virtually integrated hybrid structures, which have been evaluated in a long-term case study conducted in the San Francisco Bay Area from July 2001 to September 2002, will elucidate the further development of IHCD and the implications for other industrialized countries, such as Germany.