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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.

Ensuring adequate access to healthcare services is a priority across European countries. The EU has developed performance indicators to compare access using self-reported unmet need. Cross-country comparisons require adjustment for factors outside the health systems' control. We address two research questions to improve the comparability of unmet need for medical and dental care across the EU and the comparability of socio-economic inequalities in unmet need across the EU. First, we explore the role of risk adjustment for demographic and socio-economic factors, which are outside health systems' control, for both overall unmet need and unmet need due to affordability, waiting lists and distance. Second, we compare differences in unmet need by socio-economic status, and investigate whether different forms of risk adjustment affect such comparison. We show that adjusting for age, gender and chronic conditions reduces dispersion of unmet need for medical care across the EU. Controlling for income further reduces the dispersion, mostly due to affordability. When comparing socio-economic inequalities across countries, risk adjustment for age, gender and chronic conditions play a limited role. Socio-economic inequalities by income and education vary by reason of unmet need: the income gradient, even controlling for education, is mostly due to affordability rather than waiting list or distance. For dental care, the main reason for unmet need is affordability. Risk adjustment for age, gender, chronic conditions and education plays a limited role. The income and education gradients are more pronounced for dental than medical care.

Interventions that improve timely access to outpatient health services are essential in managing demand. This process evaluation aimed to describe the implementation, mechanism of impact and context of an intervention to reduce waiting for first appointments in an outpatient epilepsy clinic.

The UK Medical Research Council framework was used as the theoretical basis for a process evaluation alongside an intervention trial. The intervention, Specific Timely Appointments for Triage (STAT), is a data-driven approach that combines a one-off backlog reduction strategy with methods to balance supply and demand. A mixed methods process evaluation synthesised routinely collected quantitative and qualitative data, which were mapped to the domains of implementation, mechanisms of impact and contextual elements.

The principles of the STAT model were implemented as intended without adaptation. The STAT model reached all patients referred, including long waiters and was likely generalisable to other medical outpatient clinics. Mechanisms of impact were increased clinic capacity and elimination of unwanted variation. Contextual elements included the complexity of healthcare systems and the two-tier triage practice that contributes to prolonged waiting for patients classified as non-urgent.

This process evaluation shows how a data-driven strategy was applied in a medical outpatient setting to manage demand. Improving patient flow by reducing waiting in non-urgent, outpatient care is a complex problem. Understanding how and why interventions work is important for improved timeliness of care, and sustainability of public health services.

The primary objective of this paper is to show a systematic and methodological approach for the digitalization of critical clinical pathways (CPs) within the healthcare domain.

The methodology entails the integration of service design (SD) and action research (AR) methodologies, characterized by iterative phases that systematically alternate between action and reflective processes, fostering cycles of change and learning. Within this framework, stakeholders are engaged through semi-structured interviews, while the existing and envisioned processes are delineated and represented using BPMN 2.0. These methodological steps emphasize the development of an autonomous, patient-centric web application alongside the implementation of an adaptable and patient-oriented scheduling system. Also, business processes simulation is employed to measure key performance indicators of processes and test for potential improvements. This method is implemented in the context of the CP addressing transient loss of consciousness (TLOC), within a publicly funded hospital setting.

The methodology integrating SD and AR enables the detection of pivotal bottlenecks within diagnostic CPs and proposes optimal corrective measures to ensure uninterrupted patient care, all the while advancing the digitalization of diagnostic CP management. This study contributes to theoretical discussions by emphasizing the criticality of process optimization, the transformative potential of digitalization in healthcare and the paramount importance of user-centric design principles, and offers valuable insights into healthcare management implications.

The study’s relevance lies in its ability to enhance healthcare practices without necessitating disruptive and resource-intensive process overhauls. This pragmatic approach aligns with the imperative for healthcare organizations to improve their operations efficiently and cost-effectively, making the study’s findings relevant.

The study aims to have adults discuss experiences, practices needs and feelings related to health management, diet and food security.

A total of 22 immigrants were recruited from the Open School of Immigrants in Piraeus, Attica, Greece, to participate in focus group discussions. The discussions were audio recorded and thematically analyzed. Three major themes were developed: pathways to health care, nutrition management and experiences related to food shortages.

Most of the participants identified internet as the most commonly used way to obtain health advice; they also stated that unexpected ill-health is usually accompanied by feelings of fear, anxiety and loneliness. Immigrants, who had visited a public hospital in Greece, identified the language barrier as the most challenging issue, followed by the long waiting lists. Fear and anxiety of hospital visits was an important factor in their decision to vaccinate against COVID-19. Lack of time, high cost of healthy food and lack of knowledge were the most common obstacles to a healthy diet. One in two immigrants reported that they have faced food insecurity issues in the past. Stress, psychological distress and irritation were reported, due to food shortages, especially during the first few years of arriving in Greece. The exclusion of some foods, reduced portion sizes and buying cheaper foods were among the coping strategies to address food shortages.

The study offers an insight into immigrant’s experiences, practices and feelings about managing health issues and could be useful for health-care practitioners, researchers and policymakers.

Theory of Constraints (TOC), though a well-established process improvement methodology in manufacturing, is still a novel philosophy for healthcare and an exhaustive review of literature is needed to summarize the key findings of various researchers. Such a review can provide a direction to the researchers and academicians interested in exploring the application of TOC in the healthcare sector. This paper aims to review the existing literature of TOC tools and techniques applied to the healthcare environment, and to investigate motivating factors, benefits and key gaps for identifying directions for future research in the domain of healthcare.

In this paper, different electronic repositories were searched using multiple keywords. The current study identified 36 articles published between January 1999 to mid-2021 to conceptualize and summarize the research questions used in the study. Descriptive analysis along with pictorial representations have been used for better visualization of work.

This paper presents a thorough literature review of TOC in healthcare and identifies the evolution, current trends, tools used, nature of services chosen for application and research gaps and recommends future direction for research. A variety of motivating factors and benefits of TOC in healthcare are identified. Another key finding of this study is that almost all implementations listed in literature reported positive outcomes and substantial improvements in the performance of the healthcare unit chosen for study.

This paper provides valuable insight to researchers, practitioners and policymakers on the potential of TOC to improve quality of services, flow of patients, revenues, process efficiency and cost reduction in different health care settings. A number of findings and suggestions compiled in the paper from literature study can be used for diagnosing, learning and making substantial changes in healthcare. The methodologies used by different researchers were analysed and combined to propose a generic step by step procedure to apply TOC. This methodology will guide the practising managers about the appropriate tools of TOC for their specific need.

Good health is always the first desire of all men and women around the globe. The global aim of healthcare is to quickly cure more patients and ensure healthier population both today and in future. This article will work as a foundation for future applications of TOC in healthcare and guide upcoming applications in the booming healthcare sector. The paper will help the healthcare managers in serving a greater number of patients with limited available resources.

This paper provides original collaborative work compiled by the authors. Since no comprehensive systematic review of TOC in healthcare has been reported earlier, this study would be a valuable asset for researchers in this field. A model has been presented that links various benefits with one another and clarifies the need to focus on process improvement which naturally results in these benefits. Similarly, a model has been presented to guide the users in implementation of TOC in healthcare.

Community health centres (CHCs) play a vital role in healthcare service delivery in rural India and act as a crucial link between the primary and tertiary healthcare systems. The rural population in the union territory of Jammu and Kashmir primarily depends on CHCs for healthcare services due to the scarcity of private healthcare infrastructure and the lack of access to tertiary hospitals. The purpose of this study is to analyse the impact of management capability, staff competence, waiting time and patient satisfaction on revisit intention among patients visiting CHCs for care needs. It further examines the mediational role of patient satisfaction between antecedents of patient satisfaction and revisit intention.

A survey by questionnaire was used to collect data from 318 inpatients and outpatients visiting CHCs. Partial least square-structural equation modelling was performed with the help of SmartPLS 3 software to evaluate the causal relationships between variables.

The findings of the study ascertain that staff competence and waiting time are strong predictors of patient satisfaction while management capability was reported as an insignificant factor. Patient satisfaction significantly affects revisit intention and successfully mediates the impact of management capability, staff competence and waiting time on revisit intention.

CHCs play a significant role in bridging the gap between primary healthcare and tertiary healthcare and in delivering healthcare services to the vast rural population in India. This study necessitates the active participation of management to ensure the smooth functioning of CHCs. There is a need to provide adequate staff and necessary infrastructural facilities to reduce the treatment waiting time.

Artificial intelligence (AI) applications are increasingly used for day-to-day operations in healthcare. Each has a relatively limited scope or task, and several find application in managerial and organizational processes. More and more, AI and machine learning (ML) devices have received US FDA approval in the last decade. This chapter covers the main AI applications in healthcare, with a focus on organizational AI solutions (administrative AI), the main AI developers, their investment and real-world data and case studies in healthcare and other sectors. AI can be applied in resource management and procurement, resource allocation, clinical case management, staff work shift scheduling and handling of emergencies. AI applications are becoming ubiquitous in hospital (e.g. emergency room and operating theatre) and outpatient settings (e.g. ambulatory care and dentistry clinics). Their implementation is expected to bring direct benefits for patient care and satisfaction. This chapter gives a broad definition of AI in healthcare settings, with a focus on administrative applications and their use in case study data.

This paper explores the Adoption of Technological Innovation (ATI) in the healthcare industry. It investigates how the literature has evolved, and what are the emerging innovation dimensions in the healthcare industry adoption studies.

We followed a mixed-method approach combining bibliometric methods and topic modeling, with 57 papers being deeply analyzed.

Our results identify three latent topics. The first one is related to the digitalization in healthcare with a specific focus on the COVID-19 pandemic. The second one groups up the word combinations dealing with the research models and their constructs. The third one refers to the healthcare systems/professionals and their resistance to ATI.

The study’s sample selection focused on scientific journals included in the Academic Journal Guide and in the FT Research Rank. However, the paper identifies trends that offer managerial insights for stakeholders in the healthcare industry.

ATI has the potential to revolutionize the health service delivery system and to decentralize services traditionally provided in hospitals or medical centers. All this would contribute to a reduction in waiting lists and the provision of proximity services.

The originality of the paper lies in the combination of two methods: bibliometric analysis and topic modeling. This approach allowed us to understand the ATI evolutions in the healthcare industry.