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In the face of growing demand for care and tightening resource constraints, hospitals need to ensure access to care that is affordable and effective. Yet, the multiplicity of objectives is a key challenge in this industry. An understanding of the interrelationships (tradeoffs) between the multiple outcome objectives of care (throughput, experiential and financial performance) and returns to operational inputs (diversification of care) is fundamental to improving access to care that is effective and affordable. This study serves to address this need.

The empirical analysis in the study builds on an output-oriented distance function model and uses a longitudinal panel dataset from 153 hospitals in California.

This study results point to key insights related to output–output tradeoffs along the production frontier. Specifically, the authors find that higher throughput rates may lead to significantly lower levels of experiential quality, and net revenue from operations, accounting for the clinical quality of care. Similarly, the authors’ findings highlight the resource intensity and operational challenges of improving experiential quality of care. In regards to input–output relationships, this study finds diversification of care is associated with increased throughput, improvements in service satisfaction and a corresponding increase in the net revenue from operations.

Highlighting the tradeoffs along the production frontier among the various outcomes of interest (throughput, experiential quality and net revenue from operations), and highlighting the link between diversification of care and care delivery outcomes at the hospital level are key contributions of this study. An understanding of the tradeoffs and returns in healthcare delivery serves to inform policy-making with key managerial implications in the delivery of care.

The research analyzes good practices in health care “management experimentation models,” which fall within the broader range of the integrative public–private partnerships (PPPs). Introduced by the Italian National Healthcare System in 1991, the “management experimentation models” are based on a public governance system mixed with a private management approach, a patient-centric orientation, a shared financial risk, and payment mechanisms correlated with clinical outcomes, quality, and cost-savings. This model makes public hospitals more competitive and efficient without affecting the principles of universal coverage, solidarity, and equity of access, but requires higher financial responsibility for managers and more flexibility in operations.

In Italy the experience of such experimental models is limited but successful. The study adopts the case study methodology and refers to the international collaboration started in 1997 between two Italian hospitals and the University of Pittsburgh Medical Center (UPMC – Pennsylvania, USA) in the field of organ transplants and biomedical advanced therapies.

The research allows identifying what constitutes good management practices and factors associated with higher clinical performance. Thus, it allows to understand whether and how the management experimentation model can be implemented on a broader basis, both nationwide and internationally. However, the implementation of integrative PPPs requires strategic, cultural, and managerial changes in the way in which a hospital operates; these transformations are not always sustainable.

The recognition of ISMETT’s good management practices is useful for competitive benchmarking among hospitals specialized in organ transplants and for its insights on the strategies concerning the governance reorganization in the hospital setting. Findings can be used in the future for analyzing the cross-country differences in productivity among well-managed public hospitals.

Hospital managers are confronted with decisions that have to account for multiple objectives, which may be in conflict with regard to efficiency and quality of care. In empirical studies occupancy and staffing ratios as well as in‐hospital mortality are frequently used measures for efficiency and quality‐of‐care, respectively. Efficiency and quality measures vary on a daily basis. However, most empirical studies fail to take this variation into account, especially because data of daily staffing levels are lacking. The paper seeks to exploit the notion that staffing levels are planned according to expected occupancy levels, i.e. estimated daily occupancy levels account for unobserved daily staffing levels.

Using administrative data from 2004 for a sample of 62 departments in 33 German hospitals, the relation between daily occupancy levels and in‐hospital mortality count on the department level is analyzed. In an OLS‐framework the paper estimates daily occupancy level for all departments and then uses the predicted occupancy levels in a zero‐inflated Poisson (ZIP) regression framework to explain in‐hospital mortality count.

The results show a potential trade‐off relation between predicted occupancy rates and mortality. More specifically, the paper finds that the trade‐off relation is less pronounced in hospitals with a higher number of available staff per bed.

First, the paper shows evidence for a negative trade‐off between measures of managerial and medical performance on a day‐to‐day basis. Second, interactions between single measures of efficiency are modeled, namely predicted occupancy rate and staff per bed ratios, and policy implications are developed. Third, first empirical results in this respect using German data are presented.

Worldwide, there is significant growth in the cost of (and demand for) healthcare, which often clashes with a requirement to contain expenditure. This duality leads to an increasing need for a systematic approach to disinvestment in health technologies. The purpose of this paper is to consider the challenges and opportunities for disinvestment policy decisions in Australia. It discusses the implementation of the Choosing Wisely campaign and the need for rigorous evaluation of such campaigns in the Australian healthcare system.

The authors highlight characteristics of disinvestment: what it is and what it is not and discuss international examples of identifying low value care, including the recent Choosing Wisely initiative. The authors discuss the barriers to implementing initiatives such as Choosing Wisely and the complexities in evaluating their effectiveness.

While the primary purpose of the Choosing Wisely campaign is improved decision making through clinical engagement, it is expected that implementation could lead to resource savings alongside improvements in patient safety and service quality. While there is research looking to understand the barriers and facilitators to the implementation of initiatives such as Choosing Wisely, little is known about broader patient impacts, and more attention on the quantification of their effect on both patient outcomes and resource use is needed.

This work highlights the limited knowledge around implementation of disinvestment strategies and the paucity of research around the impact of strategies such as Choosing Wisely in the Australian public hospital system. This is important as future research in this area will give greater certainty about the benefits and consequences of Choosing Wisely leading to improved opportunities for resource savings and patient safety and quality.

This article aims to encourage healthcare administrators to consider the learning organization concept and foster collaborative learning among teams in their attempt to improve patient safety.

Relevant healthcare, organizational behavior and human resource management literature was reviewed.

A patient safety culture, fostered by healthcare leaders, should include an organizational culture that encourages collaborative learning, replaces the blame culture, prioritizes patient safety and rewards individuals who identify serious mistakes.

As healthcare institution staffs are being asked to deliver more complex medical services with fewer resources, there is a need to understand how hospital staff can learn from other organizational settings, especially the non‐healthcare sectors.

The paper provides suggestions for improving patient safety which are drawn from the health and business management literature.

The purpose of this paper is to describe the processes and results of implementing and evaluating the Releasing Time to Care™ (RTC™) model in a 45‐bed Neurosciences unit in a tertiary care hospital in Saskatchewan province of western Canada.

Organizational restructuring in healthcare systems has impacted the ability of clinical registered nurses (CRNs) in participation and in influencing the decision making that affect the delivery and outcomes of patient‐centered care. At the same time, CRNs' work has intensified because of increases in patient acuity, technological advances, complexity of care provided to patient families and communities, in addition to the intensifying demands put on by an aging population and dwindling resources. The work reported in this paper shows that significant improvements have been made based on the current needs and the change is forever imminent. Establishing solid people connections and networking opportunities proved valuable for current and future exchange of information and knowledge translation.

Model implementation resulted in positive narrative and empirical data including: improved patient safety, staff engagement, leadership opportunities and an affirmative shift in organizational culture. Improved patient safety was evidenced by a reduction in falls and decreased medication errors.

The paper focuses on including the clinical nurse in organizational and system change towards improving patient‐centered quality care. Neurosciences 6300 at Royal University Hospital (RUH) in Saskatoon, was viewed as an RTC™ champion and one of the first to implement and complete the 11‐module toolkit.

The purpose of this paper is to overview, background and context to clinical governance in Australia, areas for further development and potential learnings for other jurisdictions.

Commentary; non-systematic review of clinical governance literature; review of web sites for national, state and territory health departments, quality and safety organisations, and clinical colleges in Australia.

Clinical governance in Australia shows variation across jurisdictions, reflective of a fragmented health system with responsibility for funding, policy and service provision being divided between levels of government and across service streams. The mechanisms in place to protect and engage with consumers thus varies according to where one lives. Information on quality and safety outcomes also varies; is difficult to find and often does not drill down to a service level useful for informing consumer treatment decisions. Organisational stability was identified as a key success factor in realising and maintaining the cultural shift to deliver ongoing quality.

Comparison of quality indicators with clinical governance systems and processes at a hospital level will provide a more detailed understanding of components most influencing quality outcomes.

The information reported will assist health service providers to improve information and processes to engage with consumers and build further transparency and accountability.

In this paper the authors have included an in depth profile of the background and context for the current state of clinical governance in Australia. The authors expect the detail provided will be of use to the international reader unfamiliar with the nuances of the Australian Healthcare System. Other studies (e.g. Russell and Dawda, 2013; Phillips et al., n.d.) have been based on deep professional understanding of clinical governance in appraising and reporting on initaitives and structures. This review has utilised resources available to an informed consumer seeking to understand the quality and safety of health services.

The authors examine how physician staffing, human capital and knowledge spillovers are related to multiple dimensions of hospital operational and financial performance at the organizational level.

The authors use a data set assembled from multiple sources for more than 1,300 US hospitals and employ hierarchical linear regression to test this study’s hypotheses. The authors use multiple quality, efficiency and financial measures of performance for these hospitals.

The authors find that higher levels of staffing, skills and knowledge spillovers associated with physicians were positively associated with multiple dimensions of hospital performance. The authors find linear and nonlinear relationships between experience and performance, with the relationships primarily negative, and nonlinear relationships between spillovers and quality performance.

Hospital managers should consider increasing physician staffing levels if possible. In addition, the overall Final MIPS Score from the Centers for Medicare and Medicaid Services might be included as a factor in determining which physicians practice in a hospital. Finally, if possible, encouraging physicians to practice at multiple hospitals will likely be beneficial to hospital performance.

This study’s findings are original in that they explore how physician-specific staffing and human capital, which have received comparatively little attention in the literature, are related to several different dimensions of hospital-level operational and financial performance. To the best of the authors’ knowledge, this paper is also the first to examine the relationship between the construct of physician knowledge spillovers and hospital-level operational and financial performance.

The purpose of this paper is to examine the role of perceived service attributes in the development of overall customer satisfaction (OCS) and customer loyalty (CL) in a health-care setting. This paper also sheds light on the role of hospitalist physicians (HPs) and offers suggestions to improve patient satisfaction and loyalty.

A telephone survey was used to collect data from recently hospitalized patients with respect to their HP. Structural equations modeling (SEM) was used to confirm the overall relationships between perceived service quality (PSQ), OCS and CL. The sample was then divided into customer relationship groups (CRGs) based on satisfaction and loyalty measures. Discriminant analysis was used to determine which attributes differentiated most between high and low satisfaction and loyalty groups.

Overall relationships among PSQ, OCS and CL were in conformity with the conceptual model. Findings also revealed that service attributes played an important role in distinguishing between high and low satisfaction and loyalty groups, although some attributes were more important than others and different attributes emerged as being key influencers for satisfaction and loyalty.

The conceptual model used is a fairly straight forward model, and we have not considered the impact of individual factors such as expectations and value perceptions or involvement levels and demographic characteristics on service quality and overall satisfaction. The data for this study were provided by a major health maintenance organization (HMO), and there is room for improvement in the manner in which certain constructs were measured. For example, OCS, recommendation and retention all used single item measures, and it might have been preferable to use multiple item measures for these constructs.

The study shows that organizations can benefit by identifying and focusing on critical attributes as part of their customer relationship management program.

The SEM results provide strong support for the overall model linking service quality, OCS and CL in a health-care setting. As one would expect, PSQ has a strong impact on OCS, which, in turn, has a fairly strong impact on CL. However, there is also a significant direct linkage between PSQ and CL. This linkage shows that at least a certain portion of CL could evolve independent of the satisfaction level with the HP. This shows that, in addition to trying to improve satisfaction, organizations should also explore influencing loyalty directly, perhaps by the strategic use of service attribute perceptions.

The study shows that customer perceptions at the service attribute level can often be the key to the generation and management of customer satisfaction and loyalty. It also has significance for how satisfaction and loyalty with HPs can be improved in a hospital setting.

This study investigates the stability of the “hospital effect” on performance over time by administrative health data as a source of evidence. Using 78,907 heart failure adult records from 117 hospitals in the Lombardy Region (Northern Italy) over three years (2010–2012), we analyzed hospital performance in terms of 30-day mortality and 30-day unplanned readmissions to gather evidence about the stability of the “hospital effect.” Best/worst performers were identified through multi-level models that combine both patient and hospital covariates. Our results confirm that managerial choices affect hospital performance, and that the “hospital effect” is not, contrary to expectations, stable over the short term. Performance improvement/worsening over the three years has been also analyzed.