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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.

Although it is widely acknowledged that health care delivery systems are complex adaptive systems, there are gaps in understanding the application of systems engineering approaches to systems analysis and redesign in the health care domain. Commonly employed methods, such as statistical analysis of risk factors and outcomes, are simply not adequate to robustly characterize all system requirements and facilitate reliable design of complex care delivery systems. This is especially apparent in institutional-level systems, such as patient safety programs that must mitigate the risk of infections and other complications that can occur in virtually any setting providing direct and indirect patient care. The case example presented here illustrates the application of various system engineering methods to identify requirements and intervention candidates for a critical patient safety problem known as failure to rescue. Detailed descriptions of the analysis methods and their application are presented along with specific analysis artifacts related to the failure to rescue case study. Given the prevalence of complex systems in health care, this practical and effective approach provides an important example of how systems engineering methods can effectively address the shortcomings in current health care analysis and design, where complex systems are increasingly prevalent.

The purpose of this paper is to determine associations between initially recorded deviations in individual bedside vital parameters that contribute to total Modified Early Warning Score (MEWS) levels 2 or 3 and further clinical deterioration (MEWS level=4).

This was a prospective study in which 27,504 vital parameter values, corresponding to a total MEWS level⩾2, belonging to 1,315 adult medical and surgical inpatient patients admitted to a 90-bed study setting at a university hospital, were subjected to binary logistic and COX regression analyses to determine associations between vital parameter values initially corresponding to total MEWS levels 2 or 3 and later deterioration to total MEWS level ⩾4, and to evaluate corresponding time intervals.

Respiratory rate, heart rate and patient age were significantly (p=0.012, p<0.001 and p=0.028, respectively) associated with further deterioration from a total MEWS level 2, and the heart rate also (p=0.009) from a total MEWS level 3. Within 24 h from the initially recorded total MEWS levels 2 or 3, 8 and 17 percent of patients, respectively, deteriorated to a total MEWS level=4. Patients initially scoring MEWS 2 had a 27 percent 30-day mortality rate if they later scored MEWS level=4, and 8.7 percent if they did not.

It is important to observe all patients closely, but especially elderly patients, if total MEWS levels 2 or 3 are tachypnoea and/or tachycardia related.

Findings might contribute to patient safety by facilitating appropriate clinical and organizational decisions on adequate time spans for early warning scoring in general ward patients.

The purpose of the paper is to investigate the potential relationships between emergency-care flow, patient mortality and healthcare costs using a patient-flow model.

The researchers used performance data from one UK NHS trust collected over three years to identify periods where patient flow was compromised. The delays’ root causes in the entire emergency care system were investigated. Event time-lines that disrupted patient flow and patient mortality statistics were compared.

Data showed that patient mortality increases at times when accident and emergency (A&E) department staff were struggling to admit patients. Four delays influenced mortality: first, volume increase and mixed admissions; second, process delays; third, unplanned hospital capacity adjustments and finally, long-term capacity restructuring downstream.

This is an observational study that uses process control data to find times when mortality increases coincide with other events. It captures contextual background to whole system issues that affect patient mortality.

Managers must consider cost-decisions and flow in the whole system. Localised, cost-focused decisions can have a detrimental effect on patient care. Attention must also be paid to mortality reports as existing data-presentation methods do not allow correlation analysis.

Previous studies correlate A&E overcrowding and mortality. This method allows the whole system to be studied and increased mortality root causes to be understood.

The COVID-19 pandemic and its related economic meltdown and social unrest severely challenged most countries, their societies, economies, organizations, and individual citizens. Focusing on both more and less successful country-specific initiatives to fight the pandemic and its multitude of related consequences, this chapter explores implications for leadership and effective action at the individual, organizational, and societal levels. As international management scholars and consultants, the authors document actions taken and their wide-ranging consequences in a diverse set of countries, including countries that have been more or less successful in fighting the pandemic, are geographically larger and smaller, are located in each region of the world, are economically advanced and economically developing, and that chose unique strategies versus strategies more similar to those of their neighbors. Cultural influences on leadership, strategy, and outcomes are described for 19 countries. Informed by a cross-cultural lens, the authors explore such urgent questions as: What is most important for leaders, scholars, and organizations to learn from critical, life-threatening, society-encompassing crises and grand challenges? How do leaders build and maintain trust? What types of communication are most effective at various stages of a crisis? How can we accelerate learning processes globally? How does cultural resilience emerge within rapidly changing environments of fear, shifting cultural norms, and profound challenges to core identity and meaning? This chapter invites readers and authors alike to learn from each other and to begin to discover novel and more successful approaches to tackling grand challenges. It is not definitive; we are all still learning.

This chapter proposes an optimized innovative information technology as a means for achieving operational functionalities of real-time portable electronic health records, system interoperability, longitudinal health-risks research cohort and surveillance of adverse events infrastructure, and clinical, genome regions – disease and interventional prevention infrastructure. In application to the Dod-VA (Department of Defense and Veteran's Administration) health information systems, the proposed modernization can be carried out as an “add-on” expansion (estimated at $288 million in constant dollars) or as a “stand-alone” innovative information technology system (estimated at $489.7 million), and either solution will prototype an infrastructure for nation-wide health information systems interoperability, portable real-time electronic health records (EHRs), adverse events surveillance, and interventional prevention based on targeted single nucleotide polymorphisms (SNPs) discovery.

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.

Health care institutions in many Western countries have developed preoperative testing and assessment guidelines to improve surgical outcomes and reduce cost of surgical care. The aims of this chapter are to (1) summarize the literature on the effect of preoperative testing on clinical outcomes, efficiency, and cost; and (2) to compare preoperative testing guidelines developed in the United States, the United Kingdom, and Canada.

We reviewed the literature from 1975 to 2014 for studies and preoperative testing guidelines.

We identified 29 empirical studies and 8 country-specific guidelines for review. Most studies indicate that preoperative testing is overused and comes at a high cost. Guidelines are tied to payment only in one country studied. This is the most recent review of the literature on preoperative testing and assessment with a focus on quality of care, efficiency, and cost outcomes. In addition, this chapter provides an international comparison of preoperative guidelines.

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.