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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.

In recent years, the relationship between Manchester United fans and their club has been put under the spotlight due to the contentious relationship between the fanbase and the club’s American owners, the Glazer family. However, the commercialisation of Manchester United and their ramping up of their associated brand accelerated massively during the 1990s, as a result of the coincident timing of the country’s glamour club returning to dominance during a period of ever-greater financial returns for top-flight success. As the undoubted commercial trailblazers in English football (and the first English club to be listed on the Stock Exchange), analysing their development during the 1990s is, arguably, the best way of understanding how and why top-flight football clubs operate the way they do and, in a knock-on effect on the league’s competitiveness, why the clubs below them can so easily fall away.

The study examines health care inequities in viral load testing among hepatitis C (HCV) antibody-positive patients. The analysis predicts whether individual and census tract sociodemographic characteristics impact the likelihood of viral load testing.

This a study of 26,218 HCV antibody-positive patients in Orange County, California, from 2010 to 2020. The case data were matched with the 2017 American Community Survey to help understand the role of neighborhood socioeconomic characteristics in testing for viral load. Multivariable logistic regression was used to predict the probability of ever testing for HCV viral load.

Thirty-six percent of antibody-positive persons were never viral load tested. The results show inequalities in viral load testing by sociodemographic factors. The following groups were less likely to ever test for viral load than their counterparts: (1) individuals under 65 years old, (2) females, (3) residents of census tracts with lower levels of health insurance enrollment, (4) residents of census tracts with lower levels of government health insurance, and (5) residents of census tracts with a higher proportion of non-white residents.

This is a secondary database from public health department reports. Using census tract data raises the issue of the ecological fallacy. Detailed medical records were not available. The results of this study emphasize the social inequality in viral load testing for HCV. These groups are less likely to be treated and cured, and may spread the disease to others.

This chapter is unique as it combines routinely collected public health department data with census tract level data to examine social inequities associated with lower rates of HCV viral load testing.

Successful smart cities' implementation will require organisational leadership decision-making competences. The foundation of smart cities is digital technologies; many of these technologies are emerging technologies that require IT skills, which are scarce and will exacerbate the battle for talent between organisations. Filling the talent gap will necessitate global hiring, which has implications for organisational culture, cultural diversity and organisational leadership. Organisational cultural mix is an important contributor to leadership decision-making. However, decision-making is underpinned by trust. Blockchain is an emerging technology that has the potential to engender organisational trust in decision-making and, by extension, in the leadership with the ‘right’ organisational culture. Smart cities will be required to leverage emerging technologies to give business performance a competitive advantage and use emerging technologies’ applications to build a sustainable competitive advantage.

The racial reckoning of 2020, alongside the collective trauma of the global Covid-19 pandemic, led to a proliferation of DEI (diversity, equity, and inclusion) offerings within the US higher education system. At the same time, university social justice spaces found a reduction in their staffing, restriction of their work, and an increase of outsourced DEI contributions from non-justice focused locations. This research based, and semi-autobiographical chapter situated Buolamwini's work on coded bias, is grounded in the work of Spivak and Butler, and O'Neil's contributions on mathematical mismanagement. It charts the systematic dismantling of social justice efforts at one mid-sized regional public university as their work was replaced with invalidated and outsourced DEI efforts and gamed with numerical retention requirements, which did little to remedy the genuine inequity built within higher education systems. This chapter offers inferences regarding what those changes mean for inclusion efforts within higher education writ large, particularly with regard to students with marginalized identities (queer, trans, and BIPOC students) who face systemic oppression in the higher education system.