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The purpose of this paper is to investigate the relationship between ownership type and population health initiatives adopted by hospitals using the 2015 American Hospital Association data.

Hospitals of various sizes, ownership structures and geographic locations are represented in the survey. The outcome variables of interest include measures of hospital population health activities.

Findings indicate that nonprofit hospitals are most likely to express commitment to population health and participate in population health activities, with for-profit hospitals being least likely. Implications for policy and practice are discussed.

This study demonstrates that discrepancies in population health approaches exist across ownership status – particularly, nonprofit hospitals appear to be the most likely to be involved in population health efforts.

As we continue to push for population health management in the hospital setting, grappling with the definition and purpose of population health management will be essential.

Overall, these results suggest that nonprofit hospitals are more likely to be implementing population health efforts than for-profit or government-owned hospitals.

Although there are several studies on population health in hospitals, this study is the first to investigate the relationship between ownership type and population health initiatives adopted by hospitals.

This chapter provides an introduction both to some major issues and concerns in the area of population health and major health problems, especially chronic health problems, and to the overall volume. The topic of population health is reviewed, beginning with the more public health approach of Kindig and that attempt to define the term and the outcomes of interests. The chapter will then move to an examination of the linkages between population health from a more specifically sociological perspective, and especially to relationships between social structure, including socioeconomic status, and health. The last part of this introductory chapter briefly discusses the other sections in the book and each of the chapters within those sections.

The purpose of this paper is to consider how the evolving concept of the “primary care home” (PCH) that is developing in England might be an effective vehicle for the delivery of the goals of “population health”. The authors examine evidence from earlier initiatives to achieve similar objectives of primary care-led health system planning and care integration to understand relevant lessons for the PCH.

This paper is based on a descriptive review of the PCH using documentary sources and a non-systematic review of literature relating to primary care commissioning initiatives and recent initiatives to deliver general practice services on a larger scale.

The PCH is likely to bring forth relatively high engagement from general practitioners due to its neighbourhood scale, voluntary nature and its focus on professional partnership, personalisation of care and outcomes. It is important that participants have sufficient autonomy to act and that financial incentives are aligned with the goals of population health. It is also important that, unlike some earlier primary care initiatives, the PCH is given time to develop to maturity.

The PCH is a recent phenomenon that is developing in England and elsewhere. This paper locates the PCH within a historical context and draws conclusions from a relevant evidence base.

Epidemiology is often described as “the basic science of public health” (Savitz, Poole & Miller, 1999; Syme & Yen, 2000). This description suggests both a close association with public health practice, and the separation of “pure” scientific knowledge from its application in the messy social world. Although the attainability of absolute objectivity is rarely claimed, epidemiologists are routinely encouraged to “persist in their efforts to substitute evidence for faith in scientific reasoning” (Stolley, 1985, p. 38) and reminded that “public health decision makers gain little from impassioned scholars who go beyond advancing and explaining the science to promoting a specific public health agenda” (Savitz et al., 1999, p. 1160). Epidemiology produces authoritative data that are transformed into evidence which informs public health. Those data are authoritative because epidemiology is regarded as a neutral scientific enterprise. Because its claims are grounded in science, epidemiological knowledge is deemed to have “a special technical status and hence is not contestable in the same way as are say, religion or ethics” (Lock, 1988, p. 6). Despite the veneer of universality afforded by its scientific pedigree, epidemiology is not a static or monolithic discipline. Epidemiological truth claims are embodied in several shifting paradigms that span the life of the discipline. Public health knowledges and practices, competing claims internal and external to epidemiology, and structural conditions (such as current political economies, material technologies, and institutions) provide important contexts in which certain kinds of epidemiological knowledge are more likely to emerge.

Longitudinal data are required to characterise and measure the dynamics of income-related health inequalities (IRHI). This chapter develops a framework to evaluate the impact of population changes on the level of cross-sectional IRHI over time and thereby provides further insight into how health inequalities develop or perpetuate themselves in a society. The approach is illustrated by an empirical analysis of the increase in IRHI in Great Britain between 1999 and 2004 using the British Household Panel Survey. The results imply that levels of IRHI would have been even higher in 2004 but for the entry of youths into the adult population and deaths, with these natural processes of population turnover serving to partially mask the increase in IRHI among the resident adult population over the five-year period. We conclude that a failure to take demographic changes into account may lead to erroneous conclusions on the effectiveness of policies designed to tackle health inequalities.

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 Affordable Care Act is transforming health care practice nationwide through emphasis on population health and prevention. Health care organizations are increasingly required to address population health needs. However, they may be ill equipped to answer that call.

This study identified ways that health care organizations might better integrate public and population health efforts to better respond to this new emphasis on population health. Employing semi-structured key informant interviews, barriers to and facilitators of integration were explored and implications for health care and public health leaders were developed.

Participants (n = 17) – including senior hospital executives, group practice administrators, and health department officials – identified strategies for health care and public health leaders to more effectively integrate in order to achieve better performance and population health gains. These strategies and their implications are discussed.

The results of this study provide important value to health care administrators leading efforts to integrate population and public health.

Purpose: We review theory and research to suggest how research on sexual and gender minority (SGM) population health could more completely account for social class.

Approach: First, we review theory on social class, gender, and sexuality, especially pertaining to health. Next, we review research on social class among SGM populations. Then, we review 42 studies of SGM population health that accounted for one or more components of social class. Finally, we suggest future directions for investigating social class as a fundamental driver of SGM health.

Findings: Social class and SGM stigma are both theorized as “fundamental causes” of health, yet most studies of SGM health do not rigorously theorize social class. A few studies control socioeconomic characteristics as mediators of SGM health disparities, but that approach obscures class disparities within SGM populations. Only two of 42 studies we reviewed examined SGM population health at the intersections of social class, gender, and sexuality.

Research implications: Researchers interested in SGM population health would benefit from explicitly stating their chosen theory and operationalization of social class. Techniques such as splitting samples by social class and statistical interactions can help illuminate how social class and SGM status intertwine to influence health.

Originality: We synthesize theory and research on social class, sexuality, and gender pertaining to health. In doing so, we hope to help future research more thoroughly account for social class as a factor shaping the lives and health of SGM people.

The purpose of this paper is to provide an overview of post-Soviet and demographic challenges faced by the government in Moldova that have posed as challenges to reform of the healthcare system. Since independence from the Soviet Union in 1991, Moldova has undergone significant challenges and reforms throughout the society. Healthcare has been no exception. Changes in family structures due to migration, a decreased birthrate, and an aging population have placed strain on the healthcare system which is working to both modernize and provide specialized care. Legislation has helped to streamline and reform the healthcare system but systemic challenges are still faced by at-risk populations including the elderly, women, and rural populations.

Information presented in this paper is based on a review of independent research, United Nations and government reports.

Findings show that progress has been made through legislative reform, new government programming, and most recently volunteer/nonprofit involvement in healthcare reform. Currently, the government is working to establish holistic patient centered care and to bridge the healthcare divide between rural and urban populations. Healthcare reforms include basic universal health care services and family support programming. Additionally, there has been a renewed emphasis on how environmental factors, like housing and nutrition, interact with health quality.

Moldova faces an increasing challenge of caring for elderly populations at the family and societal level due to the increased number of elderly, shifts in family structures, and international migration for employment. A discussion of the developing role of nonprofit and nongovernment organizations is included.

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.