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For frail older persons, gaining access to care is primarily in the context of long-term care institutions. Based on hypotheses derived from the theory of the total institution (Goffman, 1961) and anticipatory socialization theory (Merton & Kitt, 1950), linkages of intra-institutional and extra-institutional social ties with quality of life outcomes were assessed based on 168 residents’ self-reports of their life and problems experienced in long-term care (Kahana, Kahana, & Young, 1987). Findings reveal that lack of anticipatory socialization was a significant predictor of subsequent wellbeing, whereas the extent of social ties to the outside world did not predict subsequent wellbeing.

The complex challenges facing the healthcare sector call for a revision of the ways it can provide high-quality services with economic sustainability. Revision can proceed along different pathways. Among the new paradigms of healthcare is the shift from a silo approach by hospitals towards an integrated, multidisciplinary approach. This entails restructuring hospitals in disease centres and exploring how AI can aid in the integration of hospital services and community care. Reorganization is vital to the development of patient-centred healthcare and the holistic approach. To achieve these goals, healthcare and policy decision-makers need to consider both the administrative and the clinical aspects of everyday issues. AI can play a key role in helping balance this duality. The overarching objective is to create interdisciplinary therapeutic and diagnostic pathways within care networks shared between the hospital and the community. This involves the analysis of huge amounts of data and interdisciplinary knowledge beyond the grasp of an individual. Therefore, knowing how AI can help in the development and reorganization of community healthcare is essential for clinical leaders to take advantage of this enormous opportunity in larger settings.

Nursing facility inspections routinely produce statistics revealing sharp disparities in care at both the facility and the state level. But whether high rates of deficiencies are more indicative of stringent enforcement of standards, leading to improved care, or ongoing poor quality care remains unclear. Until this question is answered, families of nursing facility residents, responsible public officials and interested professionals, are all unable to make sound decisions about long-term care quality. We employ cross-sectional, panel data to compare states on multiple indices of both care quality and enforcement stringency. We use the multi-method-multi-trait approach to distinguish these concepts. We find that low rates of deficiencies are positively associated with independent measures of high quality care. But, a prominent nursing facility enforcement index likely registers poor quality care more than stringency of enforcement since it is associated positively with independent indices of poor quality care and negatively with independent measures of enforcement. Attentive publics can have reasonable confidence that low rates of deficiencies indicate high quality care. High rates tend to reflect glaring deterioration in care quality. They are less signals of stringent enforcement than of obviously poor care which prompts more visible enforcement activities. Sadly, there is little evidence suggesting that these enforcement measures improve state-level care quality and thus reduce cross-state disparities in the quality of nursing facility long-term care. However, at least some of the factors responsible for sharp disparities in nursing facility care lie within the capacity of states to rectify even in the short term.

The study assesses public health programs to shed light on the experiences of low-income and minority women with children seeking health services. Thirteen focus groups were conducted with 111 pregnant women or women with children. Women consumers of public health services experience difficulties accessing health services due to a lack of insurance, information and language barriers about programs and eligibility, a shortage of Medicaid providers and specialist services, long waits, bureaucratic barriers, and dismissive treatment. Accessibility and information barriers were more prominent in rural regions whereas bureaucratic barriers were more pronounced in urban areas. Lower satisfaction with services was reported among ethnic minority women compared to whites.

Private equity has acquired multiple large nursing home chains within the past few years; by 2007, it owned 6 of the 10 largest chains. Despite widespread public and policy interest, evidence on the purported impact of private equity on nursing home performance is limited. In our review, we begin by briefly reviewing the organizational and environmental changes in the nursing home industry that facilitated private equity investments. We offer a conceptual framework to hypothesize the relationship between private equity ownership and nursing home performance. Finally, we offer a research agenda focused on the important parameters of nursing home performance: financial performance, and quality of care.

Hospitals worldwide are facing the same opportunities and threats: the demographics of an aging population; steady increases in chronic diseases and severe illnesses; and a steadily increasing demand for medical services with more intensive treatment for multi-morbid patients. Additionally, patients are becoming more demanding. They expect high quality medicine within a dignity-driven and painless healing environment.

The severe financial pressures that these developments entail oblige care providers to more and more cost-containment and to apply process reengineering, as well as continuous performance improvement measures, so as to achieve future financial sustainability. At the same time, regulators are calling for improved patient outcomes. Benchmarking and best practice management are successfully proven performance improvement tools for enabling hospitals to achieve a higher level of clinical output quality, enhanced patient satisfaction, and care delivery capability, while simultaneously containing and reducing costs.

This chapter aims to clarify what benchmarking is and what it is not. Furthermore, it is stated that benchmarking is a powerful managerial tool for improving decision-making processes that can contribute to the above-mentioned improvement measures in health care delivery. The benchmarking approach described in this chapter is oriented toward the philosophy of an input–output model and is explained based on practical international examples from different industries in various countries.

Benchmarking is not a project with a defined start and end point, but a continuous initiative of comparing key performance indicators, process structures, and best practices from best-in-class companies inside and outside industry.

Benchmarking is an ongoing process of measuring and searching for best-in-class performance:

• Measure yourself with yourself over time against key performance indicators

• Measure yourself against others

• Identify best practices

• Equal or exceed this best practice in your institution

• Focus on simple and effective ways to implement solutions

Measure yourself with yourself over time against key performance indicators

Measure yourself against others

Identify best practices

Equal or exceed this best practice in your institution

Focus on simple and effective ways to implement solutions

Comparing only figures, such as average length of stay, costs of procedures, infection rates, or out-of-stock rates, can lead easily to wrong conclusions and decision making with often-disastrous consequences. Just looking at figures and ratios is not the basis for detecting potential excellence. It is necessary to look beyond the numbers to understand how processes work and contribute to best-in-class results. Best practices from even quite different industries can enable hospitals to leapfrog results in patient orientation, clinical excellence, and cost-effectiveness.

Despite common benchmarking approaches, it is pointed out that a comparison without “looking behind the figures” (what it means to be familiar with the process structure, process dynamic and drivers, process institutions/rules and process-related incentive components) will be extremely limited referring to reliability and quality of findings.

In order to demonstrate transferability of benchmarking results between different industries practical examples from health care, automotive, and hotel service have been selected.

Additionally, it is depicted that international comparisons between hospitals providing medical services in different health care systems do have a great potential for achieving leapfrog results in medical quality, organization of service provision, effective work structures, purchasing and logistics processes, or management, etc.

Failure to rescue events, or events involving preventable deaths from complications, are a significant contributor to inpatient mortality. While many interventions have been designed and implemented over several decades, this patient safety issue remains at the forefront of concern for most hospitals. In the first part of this study, the development and implementation of one type of highly studied and widely adopted rescue intervention, algorithm-based patient assessment tools, is examined. The analysis summarizes how a lack of systems-oriented approaches in the design and implementation of these tools has resulted in suboptimal understanding of patient risk of mortality and complications and the early recognition of patient deterioration. The gaps identified impact several critical aspects of excellent patient care, including information-sharing across care settings, support for the development of shared mental models within care teams, and access to timely and accurate patient information.

This chapter describes the use of several system-oriented design and implementation activities to establish design objectives, model clinical processes and workflows, and create an extensible information system model to maximize the benefits of patient state and risk assessment tools in the inpatient setting. A prototype based on the product of the design activities is discussed along with system-level considerations for implementation. This study also demonstrates the effectiveness and impact of applying systems design principles and practices to real-world clinical applications.