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Barriers to adequate healthcare in rural areas remain a grand challenge for local healthcare systems. In addition to patients' travel burdens, lack of health insurance, and lower health literacy, rural healthcare systems also experience significant resource shortages, as well as issues with recruitment and retention of healthcare providers, particularly specialists. These factors combined result in complex change management-focused challenges for rural healthcare systems. Change management initiatives are often resource intensive, and in rural health organizations already strapped for resources, it may be particularly risky to embark on change initiatives. One way to address these change management concerns is by leveraging socio-technical simulation models to estimate techno-economic feasibility (e.g., is it technologically feasible, and is it economical?) as well as socio-utility feasibility (e.g., how will the changes be utilized?). We present a framework for how healthcare systems can integrate modeling and simulation techniques from systems engineering into a change management process. Modeling and simulation are particularly useful for investigating the amount of uncertainty about potential outcomes, guiding decision-making that considers different scenarios, and validating theories to determine if they accurately reflect real-life processes. The results of these simulations can be integrated into critical change management recommendations related to developing readiness for change and addressing resistance to change. As part of our integration, we present a case study showcasing how simulation modeling has been used to determine feasibility and potential resistance to change considerations for implementing a mobile radiation oncology unit. Recommendations and implications are discussed.

Complex and sudden change that healthcare organizations often have to respond to, such as during the recent pandemic, can create major disruptions and a prolonged state of alert. Although the impact of such crises can be predominantly negative, rapid adjustments during this time can also yield positive change that can support organizational response to crisis, if managed well. Using insights from organizational learning and organizational change theory, the aim of this study was to understand organizational learning during sudden change. Specifically, the authors aimed to understand the experiences and types of gains and losses in the processes of complex and disruptive change in one large healthcare organization in the UK.

Focus group data were used from 23 focus group discussions with 575 participants representing all functions and departments in one Healthcare Trust.

The participants revealed the rich gains, losses, and lessons experienced in response to sudden change that can promote organizational learning. Perceived losses are more likely to drive a desire to refreeze “back to normal” and perceived gains more likely to lead to an emphasis on embedding gains and changing to better. Therefore, on balance, the substantial, in number and variety, gains and learnings point to a learning organization. This is an essential attribute for responding to disruptive change successfully and facilitating organizational recovery in a post-pandemic world.

The findings highlight the importance of timely harnessing of the organizational learning emerging from crises and how this can inform a more resilient organization, as well as supporting sustainable organizational cross-learning.

By extending these insights on workers’ adaptation to sudden change, the findings can help to advance the science and practice of organizational learning and support organizational recovery, especially as they describe the new status in UK healthcare organizations.

The outbreak of the COVID-19 pandemic has significantly impacted healthcare systems, presenting unforeseen challenges that necessitated the implementation of change management strategies to adapt to the new contextual conditions. This study aims to analyze organizational changes within the total hip replacement (THR) surgery pathway at multiple levels, including macro, meso and micro. It employs data triangulation from various sources to gauge the complexity of the change process and comprehend how multi-level decision-making influenced an unexpected shift.

A multicentric, single in-depth case study was conducted using a mixed-methods approach. Data sources included patient-reported outcome measures specific to the THR pathway and carefully structured in-depth interviews administered to managers and clinicians in two healthcare organizations serving the same population.

Decisions made at the macro level resulted in an overall reduction in surgical activities. Organizational changes at the meso level led to a complete cessation or partial reorganization of activities. Micro-level actions for change and adaptation revealed diverse and fragmented change management strategies.

Organizations with segmented structures may require a robust and structured department for coordinating change management responses to prevent the entire system from becoming stuck in the absorptive phase of change. However, it is important to recognize that absorptive solutions can serve as a starting point for genuine innovations in change management.

The utilization of data triangulation enables the authors to visualize how specific changes implemented in response to the pandemic have influenced the observed outcomes. From a managerial perspective, it provides insights into how future innovations could be introduced.

The purpose of this study is to examine the role of artificial intelligence (AI) in transforming the healthcare sector, with a focus on how AI contributes to entrepreneurship and value creation. This study also aims to explore the potential of combining AI with other technologies, such as cloud computing, blockchain, IoMT, additive manufacturing and 5G, in the healthcare industry.

Exploratory qualitative methodology was chosen to analyze 22 case studies from the USA, EU, Asia and South America. The data source was public and specialized podcast platforms.

The findings show that combining technologies can create a competitive advantage for technology entrepreneurs and bring about transitions from simple consumer devices to actionable healthcare applications. The results of this research identified three main entrepreneurship areas: 1. Analytics, including staff reduction, patient prediction and decision support; 2. Security, including protection against cyberattacks and detection of atypical cases; 3. Performance optimization, which, in addition to reducing the time and costs of medical procedures, includes staff training, reducing capital costs and working with new markets.

This study demonstrates how AI can be used with other technologies to cocreate value in the healthcare industry. This study provides a conceptual framework, “AI facilitators – AI achievers,” based on the findings and offer several theoretical contributions to academic literature in technology entrepreneurship and technology management and industry recommendations for practical implication.

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.

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.

Using data from a continuous and ongoing cross-sectional web survey on hospitalisation service experiences in two Italian regions, the authors used multilevel and multivariate logistic regression models to identify factors related to users' demographics, emotional and informative support, technical and physical aspects of the provision, influencing satisfaction and willingness-to-recommend, before and during a crisis.

The value-in-use, defined in terms of a positive or negative value given by the experience with services, can be evaluated by users and influenced by the context of provision. The authors tested whether and how the value-in-use of services changed in a context of crisis. This study is applied to the healthcare sector during the coronavirus disease 2019 (COVID-19) epidemic, by evaluating the impact of the pandemic on hospitalisation experience.

Overall, analyses of 8,712 questionnaires found a greater value after the pandemic spread. In a time of crisis, technical and informative aspects of care were found to be most valued by patients that may recognise the extraordinary professionalism of workers during the crisis.

This study empirically suggests that context can affect the evaluation of value-in-use by patients during unprecedented circumstances, producing additional value-in-context.

These findings imply that during critical periods where there is less scope for expressions of gratitude and appreciation towards front-line workers, user-reported data can be used for motivating professionals and increase resilience. These results reiterate the need to continue collecting and reporting the service users' voices, including as activity within plans for managing challenging situations.

The level of healthcare system distress, due to the COVID-19 epidemic, positively affects patients' propensity to recommend, which the authors suggest is driven by healthcare services' feelings of reverse compassion. These findings imply that during critical periods where there is less scope for expressions of gratitude and appreciation towards front-line workers, user-reported data can be used for motivating professionals and increase resilience, which can have positive social implications. These results reiterate the need to continue collecting and reporting the service users' voices, including as activity within plans for managing challenging situations.

Research based on the intersection of theoretical and empirical research regarding value-in-use, value-in-context and service quality measured through user experience is scarce, in particular in the healthcare sector. The authors' findings set the direction for future research on the influence of context on value creation and value creation's perception by users, on the concept of reverse compassion and on reverse compassion's impact on organisational well-being, particularly in times of crisis.

Healthcare organisations are often described as less innovative than other organisations, since organisational culture works against innovations. In this paper, the authors ask whether it has to be that way or whether is possible to nurture an innovative culture in a healthcare organisation. The aim of this paper is to describe and analyse nurturing an innovative culture within a healthcare organisation and how culture can support innovations in such a healthcare organisation.

Based on a qualitative case study of a healthcare unit that changed, within a few years, from having no innovations to repeatedly generating innovations, the authors describe important aspects of how innovative culture can be nurtured in healthcare. Data were analysed using inductive and deductive analysis steps.

The study shows that it is possible to nurture an innovative culture in a healthcare organisation. Relationships and competences beyond healthcare, empowering structures and signalling the importance of innovation work with resources all proved to be important. All are aspects that a manager can influence. In this case, the manager's role in nurturing innovative culture was very important.

This study highlights that an innovative culture can be nurtured in healthcare organisations and that managers can play a key role in such a process.

The paper describes and analyses an innovative culture in a healthcare unit and identifies important conditions and strategies for nurturing innovative culture in healthcare organisations.

Many healthcare institutions, such as hospitals, have recently implemented quality improvement initiatives such as Lean Six Sigma (LSS). However, only a few have sustained the initiatives and remained successful. One of the main reasons for the failure of LSS implementation is that managers tend to view LSS as individual projects. Managers lack a Change Management (CM) focus during the implementation. The primary purpose of this study is to document the implementation of LSS through a CM approach to improve sustainability.

Define-Measure-Analyse-Improve-Control (DMAIC) and the Awareness-Desire-Knowledge-Ability-Reinforcement (ADKAR), a popular CM approach, are combined to propose a new framework. The usefulness of the proposed framework is demonstrated using a case study in a multispeciality hospital located in southern India.

The study found that several factors are responsible for the high Length of Stay (LOS) for patients in the Emergency Department (ED). By implementing this proposed model to implement LSS and taking corrective actions, the average LOS was reduced from 267 to 158 min (a 40% reduction approximately).

The complete step-by-step approach is explained, and the LOS was considerably reduced during the pilot project. The findings will provide valuable insights for healthcare practitioners to understand the steps involved in the combined DMAIC-ADKAR model. The findings would also give healthcare practitioners the confidence to identify suitable tools and implement LSS in organisations where the practitioners work.

According to the authors' knowledge, this is the first study that synergises two models (DMAIC and ADKAR) into a single framework to implement in a hospital.

Post COVID-19 crisis, healthcare has become a priority for every government. Furthermore, the pandemic has also made us realise why do we need an affordable healthcare delivery service at the grassroots level. As a result, the Government of India has come out with the Ayushman Sahakar scheme. This scheme has been launched by the Union Government with an aim to assist the cooperatives in the creation of healthcare infrastructure in this country. It is pertinent to note that the cooperatives in the last few years have transformed rural areas and have pushed them out of poverty. As a result, it will be interesting to see the impact cooperatives will have in the field of healthcare.

The authors in this work have discussed the history of healthcare cooperatives in India. After this, the authors have analysed the government schemes and legal provisions which regulate the functioning of healthcare cooperatives in this country. In the next part, the authors studied the Ayushman Sahakar scheme. The authors have discussed the features of the scheme and the impact it has generated in the field of healthcare. Lastly, the author has discussed the challenges which healthcare cooperatives face in this country and how we can overcome those challenges.