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This study aims to investigate the consequence of the quality of governance (QoG) in moderating the effect of healthcare spending on human development.

The authors employ a two-step Windmeijer finite sample-corrected system-generalized method of moments (sys-GMM) estimation technique on a panel dataset of 161 countries from 2005 to 2019. The authors use healthcare expenditure as the main explanatory variable and the Human Development Index (HDI) as the dependent variable and also consider voice and accountability (VnA), political stability and absence of terrorism (PSnAT), governance effectiveness (GoE), regulatory quality (ReQ), rules of law (RLaw) and control of corruption (CoC) dimensions of governance indicators as proxies of good governance. The authors develop a new measure of good governance from these six dimensions of governance using principal component analysis (PCA).

The authors empirically revealed that allocating more healthcare support alone is insufficient to improve human development. Individually, PSnAT has the highest net positive effect on health expenditure that helps to increase human welfare. Further, the corresponding interaction effect between expenditure and the Good Governance Index (GGI) is negative but insignificant for low-income countries (LICs); negative and statistically significant for sub-Saharan African (SSA) economies and positive but insignificant for South Asian nations.

This study is an in-depth analysis of how governance impacts the effectiveness of healthcare expenditure to ensure higher human development, particularly in a large panel of 161 countries. The authors have developed a new index of good governance and later extended the analysis by separating countries based on the income level and geographical location, which are utterly absent in existing literature.

This paper describes a quality improvement project to improve oversight of quality at national board level using statistical process control (SPC) methods, complimented by a qualitative experience of patients and frontline staff. It demonstrates the application of the “Picture-Understanding-Action” approach and shares the lessons learnt.

Using co-design and applying the “Picture-Understanding-Action” approach, the project team supported the directors of the Irish health system to identify and test a qualitative and quantitative picture of the quality of care across the health system. A “Quality Profile” consisting of quantitative indicators, analysed using SPC methods was used to provide an overview of the “critical few” indicators across health and social care. Patient and front-line staff experiences added depth and context to the data. These methods were tested and evolved over the course of six meetings, leading to quality of care being prioritised and interrogated at board level.

This project resulted in the integration of quality as a substantive and prioritised agenda item. Using best practice SPC methods with associated training produced better understanding of performance of the system. In addition, bringing patient and staff experiences of quality to the forefront “people-ised” the data.

The application of the “Picture-Understanding-Action” approach facilitated the development of a co-designed quality agenda item. This is a novel process that shifted the focus from “providing” information to co-designing fit-for-purpose information at board level.

The purpose of this study is to summarize the available pool of literature on service quality to identify different dimensions of service quality in the healthcare industry and understand how it is measured. The study attempts to explore the research gaps in the literature about different service quality dimensions and patient satisfaction.

A systematic literature review process was followed to achieve the objectives of the study. Various inclusion and exclusion criteria were used to select relevant research articles from 2000–2020 for the study, and a total of 100 research articles were selected.

The study identified 41 different dimensions of healthcare service quality measurement and classified these dimensions into four categories, namely servicescape, personnel, hospital administration and patients. It can be concluded that SERVQUAL is the most widely used service quality measurement tool.

The study identified that a majority of the researchers deduced a positive relationship between SERVQUAL dimensions and the quality of healthcare services. The findings of study will assist hospital executives in formulating effective strategies to ensure that patients receive superior quality healthcare services.

Evaluating primary care for children has not before been undertaken on a national level, and only infrequently on an international level, an adult-focused perspective is the norm. The Models of Child Health Appraised (MOCHA) project explored the evaluation of quality of primary care for children in a nationally comparable way, which recognises the influence of all components of child well-being and well-becoming. Using adult-focused metrics fails to account for children’s physical and psycho-social development at different ages, differences in health and non-health determinants, patterns of disease and risk factors and the stages of the life course. To do this, we attempted to identify comparable measures of child health in the European Union and European Economic Area countries, we aimed to perform a structural equation modelling technique to identify causal effects of certain policies or procedures in children’s primary care and we aimed to identify and interrogate large datasets for key tracer conditions. We found that the creation of comparative data for children and child health services remains a low priority in Europe, and the largely unmet need for indicators covering all the healthcare dimensions hampers development of evidence-based policy. In terms of the MOCHA project objective of appraising models of child primary health care, the results of this specific work show that the means of appraisal of system and service quality are not yet agreed or mature, as well as having inadequate data to fuel them.

The goal of this research is to analyse the obstacles to the implementation of mobile health (mHealth) in India and to gain an understanding of the contextual inter-relationships that exist amongst those obstacles.

Potential barriers and their interrelationships in their respective contexts have been uncovered. Using MICMAC analysis, the categorization of these barriers was done based on their degree of reliance and driving power (DP). Furthermore, an interpretive structural modeling (ISM) framework for the barriers to mHealth activities in India has been proposed.

The study explores a total of 15 factors that reduce the efficiency of mHealth adoption in India. The findings of the Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC) investigation show that the economic situation of the government, concerns regarding the safety of intellectual technologies and privacy issues are the primary obstacles because of the significant driving power they have in mHealth applications.

Promoters of mHealth practices may be able to make better plans if they understand the social barriers and how they affect each other; this leads to easier adoption of these practices. The findings of this study might be helpful for governments of developing nations to produce standards relating to the deployment of mHealth; this will increase the efficiency with which it is adopted.

At this time, there is no comprehensive analysis of the factors that influence the adoption of mobile health care with social cognitive theory in developing nations like India. In addition, there is a lack of research in investigating how each of these elements affects the success of mHealth activities and how the others interact with them. Because developed nations learnt the value of mHealth practices during the recent pandemic, this study, by investigating the obstacles to the adoption of mHealth and their inter-relationships, makes an important addition to both theory and practice.

This paper aims to classify journal papers in the context of hybrid quality function deployment QFD and multi-criteria decision-making (MCDM) methods published during 2004–2021.

A conceptual classification scheme is presented to analyze the hybrid QFD-MCDM methods. Then some recommendations are given to introduce directions for future research.

The results show that among all related areas, the manufacturing application has the most frequency of published papers regarding hybrid QFD-MCDM methods. Moreover, using uncertainty to establish a hybrid QFD-MCDM the relevant papers have been considered during the time interval 2004–2021.

There are various shortcomings in conventional QFD which limit its efficiency and potential applications. Since 2004, when MCDM methods were frequently adopted in the quality management context, increasing attention has been drawn from both practical and academic perspectives. Recently, the integration of MCDM techniques into the QFD model has played an important role in designing new products and services, supplier selection, green manufacturing systems and sustainability topics. Hence, this survey reviewed hybrid QFD-MCDM methods during 2004–2021.

The purpose of this paper is to determine whether some aspects of the distinctive Mayo Clinic care model could be translated into English National Health Service (NHS) hospital settings, to overcome the fragmented and episodic nature of non-emergency patient care.

The authors used a rapid review to assess the literature on integrated clinical care in hospital settings and critical analysis of links between Mayo Clinic’s care model and the organisation’s performance and associated patient outcomes.

The literature directly concerned with Mayo Clinic’s distinctive ethos and approach to patient care is limited in scope and largely confined to “grey” sources or to authors and institutions with links to Mayo Clinic. The authors found only two peer-reviewed articles which offer critical analysis of the contribution of the Mayo model to the performance of the organisation.

Mayo Clinic is not the only organisation to practice integrated, in-hospital clinical care; however, it is widely regarded as an exemplar.

There are barriers to implementing a Mayo-style model in English NHS hospitals, but they are not insurmountable and could lead to much better coordination of care for some patients.

The study shows that there is an appetite among NHS patients and staff for better coordinated, multi-specialty care within NHS hospitals.

In the English NHS integrated care generally aims to improve coordination between primary, community and secondary care, but problems remain of fragmented care for non-emergency hospital patients. Use of a Mayo-type care model, within hospital settings, could offer significant benefits to this patient group, particularly for multi-morbid patients.

This paper aims to describe the evolution of Sanokondu, highlighting the rationale, achievements and lessons learnt from this initiative. Sanokondu is a multinational community of practice dedicated to fostering health-care leadership education worldwide. This platform for health-care leadership education was conceived in 2014 at the first Toronto International Summit on Leadership Education for Physicians (TISLEP) and evolved into a formal network of collaborators in 2016.

This paper is a case study of a multinational collaboration of health-care leaders, educators, learners and other stakeholders. It describes Sanokondu’s development and contribution to global health-care leadership education. One of the major strategies has been establishing partnerships with other educational organizations involved in clinical leadership and health systems improvement.

A major flagship of Sanokondu has been its annual TISLEP meetings, which brings various health-care leaders, educators, learners and patients together. The meetings provide opportunities for dialog and knowledge exchange on leadership education. The work of Sanokondu has resulted in an open access knowledge bank for health-care leadership education, which in addition to the individual expertise of its members, is readily available for consultation. Sanokondu continues to contribute to scholarship in health-care leadership through ongoing research, education and dissemination in the scholarly literature.

Sanokondu embodies the achievements of a multinational collaboration of health-care stakeholders invested in leadership education. The interactions culminating from this platform have resulted in new insights, innovative ideas and best practices on health-care leadership education.

The primary objective of this paper is to explore the robust determinants influencing the infection rate and case mortality rate of COVID-19 in both developing and developed economies. The analysis is conducted using a dataset encompassing 148 countries.

To achieve this goal, empirical testing utilizes the Sala-i-Martin version of extreme bounds analysis, a method grounded in the cumulative density function. This approach allows for a comprehensive exploration of potential determinants.

The analysis results reveal that, to a large extent, distinct factors contribute to the infection and mortality rates in developed and developing countries. Notwithstanding these differences, certain common factors emerge, such as the risk environment, the number of tests conducted per million people and the percentage of the population over 65.

Despite acknowledging the potential limitations inherent in official data, this study concludes that the presented results offer valuable insights. The identified determinants, both unique and common, contribute to understanding the dynamics of COVID-19 in diverse economic settings. The information gleaned from this research holds significance for decision-makers involved in combating the ongoing pandemic.

To discuss how managers contribute in promoting resilience in healthcare, and to suggest a model of managers' role in supporting resilience and elaborate on how future research and implementation studies can use this to further operationalize the concept and promote healthcare resilience.

The authors first provide an overview of and discuss the main approaches to healthcare resilience and research on management and resilience. Second, the authors provide examples on how managers work to promote healthcare resilience during a one-year Norwegian longitudinal intervention study following managers in nursing homes and homecare services in their daily quality and safety work. They use this material to propose a model of management and resilience.

The authors consider managerial strategies to support healthcare resilience as the strategies managers use to engage people in collaborative and coordinated processes that adapt, enhance or reorganize system functioning, promoting possibilities of learning, growth, development and recovery of the healthcare system to maintain high quality care. The authors’ model illustrates how managers influence the healthcare systems ability to adapt, enhance and reorganize, with high quality care as the key outcome.

In this study, the authors argue that managerial strategies should be considered and operationalized as part of a healthcare system's overall resilience. They propose a new model of managers' role in supporting resilience to be used in practice, interventions and future research projects.