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Tactical capacity planning is crucial when hospitals must cope with substantial changes in patient requirements, as recently experienced during the Covid-19 pandemic. However, there is only little understanding of the nature of capacity limitations in a hospital, which is essential for effective tactical capacity planning.

We report a detailed analysis of capacity limitations at a Norwegian tertiary public hospital and conducted 22 in-depth interviews. The informants participated in capacity planning and decision-making during the Covid-19 pandemic. Data are clustered into categories of capacity limitations and a correspondence analysis provides additional insights.

Personnel and information were the most mentioned types of capacity limitations, and middle management and organizational functions providing specialized treatment felt most exposed to capacity limitations. Further analysis reveals that capacity limitations are dynamic and vary across hierarchical levels and organizational functions.

Future research on tactical capacity planning should take interdisciplinary patient pathways better into account as capacity limitations are dynamic and systematically different for organizational functions and hierarchical levels.

We argue that our study possesses common characteristics of tertiary public hospitals, including professional silos and fragmentation of responsibilities along patient pathways. Therefore, we recommend operations managers in hospitals to focus more on intra-organizational information flows to increase the agility of their organization.

Our detailed capacity limitation analysis at a tertiary public hospital in Norway during the Covid-19 pandemic provides novel insights into the nature of capacity limitations, which may enhance tactical capacity planning.

Following several prior editions and the acquisition of quantitative data indicating a 18% reduction in perceived caregiver burden and a 27% improvement in their quality of life regarding pain/mild discomfort, this present study aims to compile and examine the shared experiences of caregivers participating in the peer-to-peer Expert Caregiver Programme. The aim is to gain a deeper understanding of the programme’s inherent value.

This is a qualitative study of the Expert Caregiver Programme, a peer-to-peer support and learning initiative designed for informal caregivers of individuals with dementia. Over a span of two and a half months, this study observed a group of ten informal caregivers who were participants in the sixth edition of the Expert Caregiver Programme at a Sociosanitary Hospital in Catalonia.

The results have revealed the emergence of two distinct spirals. Firstly, the ongoing challenge of adapting to a degenerative process, coupled with the caregiver's sense of responsibility, leads to an overwhelming situation for the caregiver as far as caregiving and emotional management are concerned. This, in turn, exacerbates their feelings of isolation, fatigue and discouragement. On the other hand, the understanding of the disease and the sense of compassion towards the person with dementia have been identified as pivotal elements in the construction of an upward spiral, creating greater comfort for the caregiver. Consequently, these factors can be effectively addressed within the framework of a programme such as the Expert Caregiver.

The qualitative approach has allowed for a comprehensive and extensive exploration of the caregivers' experiences with individuals suffering from dementia. This has revealed the existence of a positive spiral that can be nurtured through peer support programmes.

This paper – the final paper of a series of three – aims to discuss the implications of the findings from a service user needs assessment of people experiencing homelessness in the Northwest of England. It will expand on the previous paper by offering a more detailed analysis and discussion of the identified key themes and issues. The service user needs assessment was completed as part of a review of local service provision in the Northwest of England against the backdrop of the COVID-19 pandemic.

Semi-structured questionnaires were administered and used by health-care professionals to collect data from individuals accessing the Homeless and Vulnerable Adults Service (HVAS) in Bolton. The questionnaires included a section exploring Adverse Childhood Experiences. Data from 100 completed questionnaires were analysed to better understand the needs of those accessing the HVAS.

Multiple deprivations including extensive health and social care needs were identified within the cohort. Meeting these complex needs was challenging for both service users and service providers. This paper will explore key themes identified by the needs assessment and draw upon further comments from those who participated in the data-gathering process. The paper discusses the practicalities of responding to the complex needs of those with lived experience of homelessness. It highlights how a coordinated partnership approach, using an integrated service delivery model can be both cost-effective and responsive to the needs of those often on the margins of our society.

Data collection during the COVID-19 pandemic presented a number of challenges. The collection period had to be extended whilst patient care was prioritised. Quantitative methods were used, however, this limited the opportunity for service user involvement and feedback. Future research could use qualitative methods to address this balance and use a more inclusive approach.

This study illustrates that the needs of the homeless population are broad and varied. Although the population themselves have developed different responses to their situations, their needs can only be fully met by a co-ordinated, multi-agency, partnership response. An integrated service model can help identify, understand, and meet the needs of the whole population and individuals within it to improve healthcare for a vulnerable population.

This study highlighted new and important findings around the resilience of the homeless population and the significance of building protective factors to help combat the multiplicity of social isolation with both physical and mental health problems.

The discussion provides an opportunity to reflect on established views in relation to the nature and scope of homelessness. The paper describes a contemporary approach to tackling current issues faced by those experiencing homelessness in the current context of the COVID-19 pandemic. Recommendations for service improvements will include highlighting established good practices including embedding a more inclusive/participatory approach.

This research paper aimed to study the legal structure of top-performing health governance systems and compare them with the Indonesian health social security system to identify the main differences and provide recommendations for Indonesian and other developing countries’ health policymakers and administrators.

Using formative research with a conceptual approach and statute approach as method in this study. Data was gathered using the document study technique, which studies various documents, especially legal documents related to health law, linked to legal purpose theories. Moreover, the World Health Organization ranking was considered to choose the two countries (France and Singapore) with a high social health security system for comparative analysis. All data collected has been analyzed using a qualitative and theoretical basis. Content analysis was performed by analyzing the legal documents, and the regulatory framework of all three countries was deeply analyzed to draw conclusions and recommendations.

Indonesia has specific laws to implement a social security system in the health sector. However, the lack of the best medical facilities and infrastructure and weak implementation of existing laws were identified as major reasons behind the poor health security system compared to comparative countries. Also, as a developing nation Indonesian Government face budgetary pressures and huge population challenges to meet required standards. Thus, the financing approaches used by Singapore and France may help developing countries meet these challenges effectively. Therefore, there is a dire need to strengthen the social health security system all over the country with amendments to laws and ensure the implementation of prevailing laws and regulations.

Providing understanding related to the social security health system in Indonesia along with a detailed description of the sound social health security system in France and Singapore will further provide an avenue for the researchers to critically analyze this line of study to devise some valuable suggestions further and to draw loopholes in the system.

A comparative approach for legal studies in the health sector is rare. So, this research advanced the social security health system-related literature and legal studies on the health sector by using this comparative approach to develop policy insights and future research directions, which will further help the field to grow.

This study aims to investigate the key factors that influence the behavioural intention of doctors to adopt the knowledge sharing driven blockchain technology in government hospitals. The study is based on the Unified Theory of Acceptance and Use of Technology 2, with the addition of trust as an independent variable and knowledge sharing as a mediating variable between trust and behavioural intention.

The data for the study was collected through a correlation and cross-sectional study using a survey, with a sample of 322 responses being used for the final analysis. The initial analysis of the data was conducted using SPSS v.26, followed by a partial least squares structural equation modelling (PLS-SEM) analysis using SmartPLS v.3.9 to test the validity and reliability of the measures and to examine the hypothesized relationships.

The results supported the proposed framework. The results of PLS-SEM indicate that all proposed pathways support the model. In particular, the results of the study reveal that performance expectation, effort expectation, social influence, facilitation conditions and trust are drivers of blockchain adoption and have a significant impact on the behavioural intention of clinicians in hospitals. Furthermore, the study found that knowledge sharing mediated the relationship between trust and behavioural intention.

The present study sheds light on the challenges facing blockchain technology, such as privacy and trust concerns and proposes a more sustainable approach based on knowledge management to enhance the effectiveness of blockchain technology and overcome these challenges.

The significance of this paper lies in the limited literature examining the relationships between blockchain technology and knowledge management processes. Furthermore, a hypothetical framework that includes the knowledge sharing process as a mediating variable between trust and behavioural intention to adopt blockchain technology has not been presented or developed in any previous studies, particularly in the context of Iraq. Thus, this work is novel and unique in its approach.

To analyze the quality of transitional care for patients with COVID-19 at discharge from Brazilian university hospitals.

A cross-sectional descriptive study was carried out in five Brazilian university hospitals between April and December 2021. The sample consisted of 527 participants. Data collection consisted of a sociodemographic questionnaire and the Care Transitions Measure (CTM-15), a care transition assessment instrument, which was translated and validated in Portuguese.

Most participants were patients (n = 369; 70.0%), with primary school completion (n = 218; 43.4%), multiracial (n = 218; 43.5%) and with an income of up to two minimum wages (n = 182; 42.8%). Dimension 1 – management preparation – obtained the highest score (71.2 points, SD = 16.5), while Dimension 4 – care plan – obtained the lowest score (62.2 points, SD = 23.4). Among the participating hospitals, there was a difference in the overall mean with results ranging from 67.0 to 72.9 points.

A satisfactory quality of care transition was found, considering the context of a pandemic. The main weaknesses in the care transitions were related to the care planning after hospital discharge.

In the present-day highly customer-conscious service environment, supply chain management has become a critical component of health-care industry, helping in fulfilling patient expectation, optimizing inventory and automating departmental activities. Supplier selection is one of the crucial elements of health-care supplier chain, establishing mutually beneficial relationships with the reliable suppliers that provide the most value of money. Health-care supplier selection with feasible sets of alternatives and conflicting criteria can be treated as a multi-criteria decision making (MCDM) problem. Among the MCDM methods, grey relational analysis (GRA) appears as a potent tool due to its simple computational steps and ability to deal with imprecise data. The purpose of this paper is to explore the applicability of a newly developed MCDM tool for solving a health-care supplier selection problem.

In GRA, the distinguishing coefficient (ξ) plays a contributive role in final ranking of the alternative suppliers and almost all the past researchers have considered its value as 0.5. In this paper, a newly developed MCDM tool, i.e. dynamic GRA (DGRA), is adopted to evaluate the relative performance of 25 leading pharmaceutical suppliers for a health-care unit based on nine important financial metrics. Instead of static value of ξ, DGRA treats it as a dynamic variable dependent on grey relational variator and ranks the health-care suppliers using their computed rank product scores.

Based on rank product scores and developed exponential curve, DGRA classifies all the suppliers into reliable, moderately reliable and unreliable clusters, helping the health-care unit in identifying the best performing suppliers for subsequent order allocation. Among the reliable suppliers, alternatives A₂ and A₁₁ occupy the top two positions having almost the same performance with respect to the considered financial metrics.

Application of DGRA along with determination of the most reliable suppliers would help in effectively adopting multi-sourcing strategy to increase resilience while diversifying the supply portfolio, thereby enabling the health-care unit to minimize chances of sudden disruption in the supply chain. It can act as an intelligent decision-making framework aiding in solving health-care supplier selection problems considering perceived risks and dynamic input data.

Investigating the role of leadership during the COVID-19 pandemic in maintaining the well-being and performance of the medical personnel, as frontline workers, is of major importance. The aim of this study was to investigate the relationships between engaging leadership in health care during COVID-19 pandemic and followers’ work engagement and performance and to test the mediating role of followers’ basic psychological need satisfaction in these relationships.

A cross-sectional study was conducted on a sample consisting of 200 health-care employees. Data were collected starting with May 2020 and ending with November 2020, during the COVID-19 pandemic. Participants reported on the engaging leadership of their direct supervisor and on their own psychological need satisfaction, work meaningfulness, work engagement and quality of care.

The positive association between engaging leadership and followers’ work engagement was fully mediated by followers’ basic needs satisfaction. The relationship between engaging leadership and followers’ quality of patient care was not supported. Work meaningfulness did not mediate the link between engaging leadership and followers’ engagement.

By meeting followers’ needs for autonomy, competence and relatedness, engaging leaders can stimulate followers’ work engagement during outbreaks and other similar crises. Managers in health care may maintain a high level of followers’ work engagement during crises if they adopt an engaging leadership style.

The study investigated for the first time the role of meeting the psychological needs of health-care workers by leaders during a health-care crisis.

The purpose of this paper is to secure health data collection and transmission (SHDCT). In this system, a native network consists of portable smart devices that interact with multiple gateways. It entails IoMT devices and wearables connecting to exchange sensitive data with a sensor node which performs the aggeration process and then communicates the data using a Fog server. If the aggregator sensor loses the connection from the Fog server, it will be unable to submit data directly to the Fog server. The node transmits encrypted information with a neighboring sensor and sends it to the Fog server integrated with federated learning, which encrypts data to the existing data. The fog server performs the operations on the measured data, and the values are stored in the local storage area and later it is updated to the cloud server.

SHDCT uses an Internet-of-things (IoT)-based monitoring network, making it possible for smart devices to connect and interact with each other. The main purpose of the monitoring network has been in the collection of biological data and additional information from mobile devices to the patients. The monitoring network is composed of three different types of smart devices that is at the heart of the IoT.

It has been addressed in this work how to design an architecture for safe data aggregation in heterogeneous IoT-federated learning-enabled wireless sensor networks (WSNs), which makes use of basic encoding and data aggregation methods to achieve this. The authors suggest that the small gateway node (SGN) captures all of the sensed data from the SD and uses a simple, lightweight encoding scheme and cryptographic techniques to convey the data to the gateway node (GWN). The GWN gets all of the medical data from SGN and ensures that the data is accurate and up to date. If the data obtained is trustworthy, then the medical data should be aggregated and sent to the Fog server for further processing. The Java programming language simulates and analyzes the proposed SHDCT model for deployment and message initiation. When comparing the SHDCT scheme to the SPPDA and electrohydrodynamic atomisation (EHDA) schemes, the results show that the SHDCT method performs significantly better. When compared with the SPPDA and EHDA schemes, the suggested SHDCT plan necessitates a lower communication cost. In comparison to EHDA and SPPDA, SHDCT achieves 4.72% and 13.59% less, respectively. When compared to other transmission techniques, SHDCT has a higher transmission ratio. When compared with EHDA and SPPDA, SHDCT achieves 8.47% and 24.41% higher transmission ratios, respectively. When compared with other ways it uses less electricity. When compared with EHDA and SPPDA, SHDCT achieves 5.85% and 18.86% greater residual energy, respectively.

In the health care sector, a series of interconnected medical devices collect data using IoT networks in the health care domain. Preventive, predictive, personalized and participatory care is becoming increasingly popular in the health care sector. Safe data collection and transfer to a centralized server is a challenging scenario. This study presents a mechanism for SHDCT. The mechanism consists of Smart healthcare IoT devices working on federated learning that link up with one another to exchange health data. Health data is sensitive and needs to be exchanged securely and efficiently. In the mechanism, the sensing devices send data to a SGN. This SGN uses a lightweight encoding scheme and performs cryptography techniques to communicate the data with the GWN. The GWN gets all the health data from the SGN and makes it possible to confirm that the data is validated. If the received data is reliable, then aggregate the medical data and transmit it to the Fog server for further process. The performance parameters are compared with the other systems in terms of communication costs, transmission ratio and energy use.

Efficiency and quality are primary factors for the survival of health systems. The evaluation of the efficiency of the healthcare system is a crucial component of promoting long-term health policy actions. Healthcare capacity indicators provide a basis for evaluating and comparing the performance of different healthcare organizations. Intrinsic quality indicators are Donabedian (1980)’s structural and process elements of quality of healthcare. This study aims to integrate capacity and intrinsic quality indicators of healthcare while measuring the efficiency of provinces by using radial and non-radial efficiency measurement techniques.

Efficiency analysis performed in Turkey from 2015 to 2020 by performing input-oriented radial, nonradial, and super-efficiency estimates for 81 provinces of Turkey by incorporating capacity and intrinsic quality indicators into the different model specifications.

Radial and nonradial efficiency results have an increasing trend over the study years obtained from the efficiency models showing high average scores obtained from the models that include intrinsic quality of care indicators. Statistically significant mean rank differences are observed between different radial efficiency models for all study years (p < 0.001). Negative and moderate level correlations were observed between radial efficiency results and quality of care indicators (r < 0.70).

Under long-term centralized health policies, increases in efficiency result in decreased intrinsic quality of care indicators. A better synthesis of health system capacity and intrinsic healthcare quality indicators is necessary to generate evidence-based health systems.