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Micro hospitals are a new form of for-profit health-care facility with rapid expansion in some parts of the country. They continue to grow in Texas without in-depth public understanding or explicit policy guidance on their role in the health-care system. Our project aims to define socioeconomic and demographic characteristics of areas served by micro and regular hospitals, and by doing so help assess micro hospitals' impact in expanding health-care access for disadvantaged populations in Texas.

We (1) estimated hospital service areas (catchment areas) with a spatial model based on advanced Geographic Information System (GIS) methods using a proprietary ESRI traffic network; (2) assigned population socioeconomic measures to the catchment areas from the 2014–2018 American Community Survey 5-Year Estimates, weighted with an empirically tested Gaussian distribution; (3) used two-tailed t-tests to compare means of population characteristics between micro and regular hospital catchment areas; and (4) conducted logistic regressions to examine relationships between selected population variables and the associated odds of micro hospital presence.

We found micro hospitals in Texas tend to serve a population less stressed in health-care access compared to those who are more in need as measured by various dimensions of disadvantages.

Our analysis takes a cross sectional look at the population characteristics of micro hospital service areas. Even though the initial geographic choices of micro hospitals may not reflect the long-term population changes in specific neighborhoods, our analysis can provide policy makers a tool to examine health-care access for disadvantaged populations at given point in time. As the population socioeconomic characteristics have long been associated with health-care inequality, we hope our analysis will help foster structural policy considerations that balance growing health-care delivery innovations and their social accountability.

We used GIS based spatial modeling to dynamically capture the potential patient basis by travel time calculated with a street network dataset, rather than using the traditional static census tract to define hospital service areas. By integrating both spatial and nonspatial dimensions of healthcare access, we demonstrated that the policy considerations on the implications of equal opportunity for health-care access need to take into account the social realities and lived experiences of those experiencing the most vulnerability in our society, rather than a conceptual “equality” existing in the spatial and market abstraction.

This study explores citizen activism in the articulation of a politicised counter-account of Aboriginal rights. It aims to uncover the enabling factors for a successful challenge to established political norms and the obstacles to the fullest expression of a radical imagining.

Laclau and Mouffe's theory of hegemony and discourse is used to frame the movement's success in challenging the prevailing system of urbanised healthcare delivery. Empirical materials were collected through extensive ethnographic fieldwork.

The findings from this longitudinal study identify the factors that predominantly influence the transformational success of an Yaṉangu social movement, such as the institutionalisation of group identity, articulation of a discourse connected to Aboriginal rights to self-determination, demonstration of an alternative imaginary and creation of strong external alliances.

This study offers a rich empirical analysis of counter-accounting in action, drawing on Aboriginal governance traditions of non-confrontational discourse and collective accountability to conceptualise agonistic engagement. These findings contribute to the practical and theoretical construction of democratic accounting and successful citizen activism.

The aim of the present paper is to examine how the introduction of information and communication technologies (ICTs) can have positive implications in a territorial context, where healthcare organizations are characterized by limited organizational independence and lack of individual statutory autonomy, with limited level of integration between the involved parties (healthcare operators, managers, and patients) and an uneven management of data and of information‐sharing.

The approach taken was an investigation based on a combination of quantitative and qualitative methods for information‐gathering and data‐analysis in the context of diabetes care. A case study approach was adopted with the aim of enhancing general practitioners' (GPs') performance levels through an evaluation monitoring and by controlling care paths dynamics.

The realization of the target care path for chronic–degenerative pathologies in the Local Health Trust “Naples 4” in Campania Region (Italy) led to the identification of a suitable framework that modifies, through the implementation of ICT tools, the communications dynamics and the interaction/integration for those actors involved in a patient's care path.

Healthcare markets are currently experiencing an acceleration of technological developments; the study tries to show how the appropriate adoption of new technologies can lead to improvements for the quality of care, managing at the same time the consequent rising costs in the sector.

The study aims to devise a comprehensive evaluation model (CEM) for evaluating spatial equity in the layout of elderly service facilities (ESFs) to address the inequity in the layout of ESFs within city center communities characterized by limited land resources and a dense elderly population.

The CEM incorporates a suite of analytical tools, including accessibility assessment, Lorenz curve and Gini coefficient evaluations and spatial autocorrelation analysis. Utilizing this model, the study scrutinized the distributional equity of three distinct categories of ESFs in the city center of Xi’an and proposed targeted optimization strategies.

The findings reveal that (1) there are disparities in ESFs’ accessibility among different categories and communities, manifesting a distinct center (high) and periphery (low) distribution pattern; (2) there exists inequality in ESFs distribution, with nearly 50% of older adults accessing only 18% of elderly services, and these inequalities are more pronounced in urban areas with lower accessibility, and (3) approximately 14.7% of communities experience a supply-demand disequilibrium, with demand surpassing supply as a predominant issue in the ongoing development of ESFs.

The CEM formulated in this study offers policymakers, urban planners and service providers a scientific foundation and guidance for decision-making or policy amendment by promptly assessing and pinpointing areas of spatial inequity in ESFs and identifying deficiencies in their development.

This chapter provides comparative insights into the context of equality and diversity in the United States and the United Kingdom. It argues that there is a real danger that progressive initiatives in combatting racism in both countries may have stalled and indeed may be slipping backwards. The chapter focuses on one sector, the healthcare sector, where service delivery is local but where in both countries there is huge reliance on an international workforce through migration. Despite huge differences in the US and UK healthcare systems, it is found that the pattern of migration with respect to both highly qualified professional workers (e.g. physicians) and middle and lower ranked workers is similar. The resilience of racial disadvantage is exposed in the context of a range diversity management initiatives.

Unequal social conditions that provide people with unequal opportunities to live healthy lives are considered unjust and associated with “health inequity”. Governing power is impacting people's lives through laws, policies and professional decisions, and can be used intentionally to combat health inequity by addressing and changing people's living- and working conditions. Little attention is paid to how these ways of exercising governing power unintentionally can structure further conditions for health inequity. In this paper, the authors coin the term “governance determinants of health” (GDHs). The authors' discussion of GDHs potential impact on health inequity can help avoid the implementation of governing strategies with an adverse impact on health equality. This paper aims to discuss the aforementioned objective.

The authors identify Governance Determinants of Health, the GDHs. GDHs refer to governance strategies that structurally impact healthcare systems and health equality. The authors focus on the unintended, blind sides of GDHs that maintain or reinforce the effects of socioeconomic inequality on health.

The power to organize healthcare is manifested in distinct structural approaches such as juridification, politicalization, bureaucratization and medical standardization. The authors explore the links between different forms of governance and health inequalities.

The authors' discussion in this article is innovative as it seeks to develop a framework that targets power dynamics inherent in GHDs to help identify and avoid GDHs that may promote unequal access to healthcare and prompt health inequity. However, this framework has limitations as the real-world, blurred and intertwined aspects of governing instruments are simplified for analytical purposes. As such, it risks overestimating the boundaries between the separate instruments and reducing the complexity of how the GDHs work in practice. Consequently, this kind of theory-driven framework does not do justice to the myriad of peoples' complex empirical practices where GDHs may overlap and intertwine with each other. Nevertheless, this framework can still help assist governing authorities in imagining a direction for the impacts of GDHs on health equity, so they can take precautionary steps to avoid adverse impacts.

The authors develop and explore – and demonstrate – the relevance of a framework that can assist governing authorities in anticipating the impacts of GDHs on health inequity.

This article examines the determinants of social equality in the education and healthcare sectors in the 15 post-Soviet states. Focussing on regime type and civil society organisations (CSOs), it argues that countries where liberal principles of democracy are achieved or have a stronger civil society deliver a more equitable social policy.

The empirical analysis rests upon a time-series cross-sectional (TSCS) analysis from 1992 to 2019. Data are collected from the Quality of Government (QoG) Dataset 2020 and the Variates of Democracy (V-DEM) Dataset 2020.

The findings demonstrate that while regime type only partially accounts for social equality, as electoral autocracies do not have more equitable social policy than close regime types and democracy weakly explains equality levels, the strength of CSOs is associated with more equality.

The article challenges dominant approaches that consider electoral democracy to be related to more equal social policy and demonstrates that de-facto free and fair elections do not impinge on social equality, while the strength of liberal and civil liberties and CSOs correlate with more equitable social policy.

This study aims to explore the nexus of equality and efficiency by considering public hospitals' development dynamics, capacity and technology indicators.

Data was collected from the Ministry of Health Public Hospital Almanacs from 2014 to 2017. The Gini index (GI) is used to estimate the inequality of distribution of hospital performance indicators. A bias-corrected efficiency analysis is calculated to obtain efficiency scores of public hospitals for the year 2017. A path analysis is then constructed to better identify patterns of causation among a set of development, equality and efficiency variables.

A redefined path model highlights that development dynamics, equality and efficiency are causally related and health technology (path coefficient = 0.57; t = 19.07; p < 0.01) and health services utilization (path coefficient = 0.24; t = 8; p < 0.01) effects public hospital efficiency. The final path model fit well (X²/df = 50.99/8 = 6; RMSEA = 0.089; NFI = 0.95; CFI = 0.96; GFI = 0.98; AGFI = 0.94). Study findings indicate high inequalities in distribution of health technologies (GI > 0.85), number of surgical operations (GI > 0.70) and number of inpatients (GI > 0.60) among public hospitals for the years 2014–2017.

Study results highlight that, hospital managers should prioritize equal distribution of health technology and health services utilization indicators to better orchestrate equity-efficiency trade-off in their operations.