Table of contents(14 chapters)
Since the publication of the report “To Err Is Human: Building a Safer Health System” by the US Institute of Medicine in 2000, much has changed with regard to patient safety. Many of the more recent initiatives to improve patient safety target the behavior of health care staff (e.g., training, double-checking procedures, and standard operating procedures). System-based interventions have so far received less attention, even though they produce more substantial improvements, being less dependent on individuals’ behavior. One type of system-based intervention that can benefit patient safety involves improvements to hospital design. Given that people’s working environments affect their behavior, good design at a systemic level not only enables staff to work more efficiently; it can also prevent errors and mishaps, which can have serious consequences for patients. While an increasing number of studies have demonstrated the effect of hospital design on patient safety, this knowledge is not easily accessible to clinicians, practitioners, risk managers, and other decision-makers, such as designers and architects of health care facilities. This is why the Swiss Patient Safety Foundation launched its project, “More Patient Safety by Design: Systemic Approaches for Hospitals,” which is presented in this chapter.
Changes in the physical environments of health care settings have become increasingly common to meet the evolving needs of the health care marketplace, new technologies, and infrastructure demands. Physical environment change takes many forms including new build construction, renovation of existing space, and relocation of units with little to no construction customization. The interrelated nature of the complex socio-technical health care system suggests that even small environmental modifications can result in system-level changes. Environmental modifications can lead to unintended consequences and introduce the potential for latent safety threats. Engaging users throughout the change lifecycle allows for iterative design and testing of system modifications. This chapter introduces a flexible process model, PROcess for the Design of User-Centered Environments (PRODUCE), designed to guide system change. The model was developed and refined across a series of real-world renovations and relocations in a large multihospital health care system. Utilizing the principles of user-centered design, human factors, and in-situ simulation, the model engages users in the planning, testing, and implementation of physical environment change. Case studies presented here offer exemplars of how to modify the model to support individual project objectives and outcomes to assess at each stage of the project.
Healthcare-associated infections (HAIs) are a major cause of concern because of the high levels of associated morbidity, mortality, and cost. In addition, children and intensive care unit (ICU) patients are more vulnerable to these infections due to low levels of immunity. Various medical interventions and statistical process control techniques have been suggested to counter the spread of these infections and aid early detection of an infection outbreak. Methods such as hand hygiene help in the prevention of HAIs and are well-documented in the literature. This chapter demonstrates the utilization of a systems methodology to model and validate factors that contribute to the risk of HAIs in a pediatric ICU. It proposes an approach that has three unique aspects: it studies the problem of HAIs as a whole by focusing on several HAIs instead of a single type, it projects the effects of interventions onto the general patient population using the system-level model, and it studies both medical and behavioral interventions and compares their effectiveness. This methodology uses a systems modeling framework that includes simulation, risk analysis, and statistical techniques for studying interventions to reduce the transmission likelihood of HAIs.
This chapter discusses the potential role of geographic information systems (GIS) for infection control within the hospital system. The chapter provides a brief overview of the role of GIS in public health and reviews current work applying these methods to the hospital setting. Finally, it outlines the potential opportunities and challenges for adapting GIS for use in the hospital setting for infection prevention. A targeted literature review is used to illustrate current use of GIS in the hospital setting. The discussion of complexity was compiled using the nonadoption, abandonment, scale-up, spread, and sustainability (NASSS) framework. Challenges and opportunities were then extracted from this exercise by the authors. There are multiple challenges to implementation of a Hospital GIS for infection prevention, mainly involving the domains of technology, organization, and adaptation. Use of a transdisciplinary approach can address many of these challenges. More research, specifically prospective, reproducible clinical trials, needs to be done to better assess the potential impact and effectiveness of a Hospital GIS in real-world settings. This chapter highlights a powerful but rarely used tool for infection prevention within the hospital. Given the importance of reducing hospital-acquired infection rates, it is vital to identify relevant methods from other fields that could be translated into the field of hospital epidemiology.
Only recently has physical space design become more widely recognized as playing a critical role in delivery of care, with an emerging body of literature on the application of human factors approaches to design and evaluation. This chapter describes the use of human factors approaches to develop and conduct an evaluation of a proposed Neonatal Intensive Care Unit redesign in a Midwestern children’s hospital. Methods included observations and knowledge elicitation from stakeholders to characterize their goals, challenges, and needs. This characterization is integral to informing the design of user-centered solutions, including physical space design. We also describe an approach to evaluating the proposed design that yielded actionable recommendations specific to hospital-driven design goals.
Medical errors in obstetric departments are commonly reported and may involve both mother and neonate. The complexity of obstetric care, the interactions between various disciplines, and the inherent limitations of human performance make it critically important for these departments to provide patient-safe and friendly working environments that are open to learning and participative safety. Obstetric care involves stressful work, and health care professionals are prone to develop burnout, this being associated with unsafe practices and lower probability for reporting safety concerns. This study aims to test the mediating role of burnout in the relationship of patient-safe and friendly working environment with unsafe performance. The full population of professionals working in an obstetrics department in Malta was invited to participate in a cross-sectional study, with 73.6% (n = 184) of its members responding. The research tool was adapted from the Sexton et al.’s Safety Attitudes Questionnaire – Labor and Delivery version and surveyed participants on their working environment, burnout, and perceived unsafe performance. Analysis was done using Structural Equation Modeling. Results supported the relationship between the lack of a perceived patient-safe and friendly working environment and unsafe performance that is mediated by burnout. Creating a working environment that ensures patient safety practices, that allows communication, and is open to learning may protect employees from burnout. In so doing, they are more likely to perceive that they are practicing safely. This study contributes to patient safety literature by relating working environment, burnout, and perceived unsafe practice with the intention of raising awareness of health managers’ roles in ensuring optimal clinical working environment for health care employees.
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.
Inappropriate cardiac monitoring leads to increased hospital resource utilization and alarm fatigue, which is ultimately detrimental to patient safety. Our institution implemented a continuous cardiac monitoring (CCM) policy that focused on selective monitoring for patients based on the American Heart Association (AHA) guidelines. The primary goal of this study was to perform a three-year median follow-up review on the longitudinal impact of a selective CCM policy on usage rates, length of stay (LOS), and mortality rates across the medical center. A secondary goal was to determine the effect of smaller-scale interventions focused on reeducating the nursing population on the importance of cardiac alarms.
A system-wide policy was developed at The Ohio State University in December 2013 based on guidelines for selective CCM in all patient populations. Patients were stratified into Critical Class I, II, and III with 72 hours, 48 hours, or 36 hours of CCM, respectively. Pre- and post-implementation measures included average cardiac monitoring days (CMD), emergency department (ED) boarding rate, mortality rates, and LOS. A 12-week evaluation period was analyzed prior to, directly after, and three years after implementation.
There was an overall decrease of 53.5% CMDs directly after implementation of selective CCM. This had remained stable at the three-year follow-up with slight increase of 0.5% (p = 0.2764). Subsequent analysis by hospital type revealed that the largest and most stable reductions in CMD were in noncardiac hospitals. The cardiac hospital CMD reduction was stable for roughly one year, then dipped into a lower stable level for nine months, then returned to the previous post-implementation levels. This change coincided with a smaller intervention to further reduce CMD in the cardiac hospital. There was no significant change in mortality rates with a slight decrease of 3.1% at follow-up (p = 0.781). Furthermore, there was no significant difference in LOS with a slight increase of 1.1% on follow-up (p = 0.649). However, there was a significant increase in ED boarding rate of 7.7% (p < 0.001) likely due to other hospital factors altering boarding times.
Implementing selective CCM decreases average cardiac monitoring rate without affecting LOS or overall mortality rate. Selective cardiac monitoring is also a sustainable way to decrease overall hospital resource utilization and more appropriately focus on patient care.
Achieving reliable instrument reprocessing requires finding the right balance among cost, productivity, and safety. However, there have been few attempts to comprehensively examine sterile processing department (SPD) work systems. We considered an SPD as an example of a socio-technical system – where people, tools, technologies, the work environment, and the organization mutually interact – and applied work systems analysis (WSA) to provide a framework for future intervention and improvement.
The study was conducted at two SPD facilities at a 700-bed academic medical center servicing 56 onsite clinics, 31 operating rooms (ORs), and nine ambulatory centers. Process maps, task analyses, abstraction hierarchies, and variance matrices were developed through direct observations of reprocessing work and staff interviews and iteratively refined based on feedback from an expert group composed of eight staff from SPD, infection control, performance improvement, quality and safety, and perioperative services. Performance sampling conducted focused on specific challenges observed, interruptions during case cart preparation, and analysis of tray defect data from administrative databases.
Across five main sterilization tasks (prepare load, perform double-checks, run sterilizers, place trays in cooling, and test the biological indicator), variance analysis identified 16 failures created by 21 performance shaping factors (PSFs), leading to nine different outcome variations. Case cart preparation involved three main tasks: storing trays, picking cases, and prioritizing trays. Variance analysis for case cart preparation identified 11 different failures, 16 different PSFs, and seven different outcomes. Approximately 1% of cases had a tray with a sterilization or case cart preparation defect and 13.5 interruptions per hour were noted during case cart preparation.
While highly dependent upon the individual skills of the sterile processing technicians, making the sterilization process less complex and more visible, managing interruptions during case cart preparation, improving communication with the OR, and improving workspace and technology design could enhance performance in instrument reprocessing.
The importance of culture is often emphasized for continuous learning and quality improvement within health care organizations. Limited empirical evidence for cultivating a culture that supports continuous learning and quality improvement in health care settings is currently available.
The purpose of this report is to characterize the evolution of a large division of physical therapists and occupational therapists in a pediatric hospital setting from 2005 to 2018 to identify key facilitators and barriers for cultivating a culture empowered to engage in continuous learning and improvement.
An ethnographic methodology was used including participant observation, document review, and stakeholder interviews to acquire a deep understanding and develop a theoretical model to depict insights gained from the investigation.
A variety of individual, social, and structural enablers and motivators emerged as key influences toward a culture empowered to support continuous learning and improvement. Features of the system that helped create sustainable, positive momentum (e.g., systems thinking, leaders with grit, and mindful design) and factors that hindered momentum (e.g., system uncertainty, staff turnover, slow barrier resolution, and competing priorities) were also identified.
Individual-level, social-level, and structural-level elements all influenced the culture that emerged over a 12-year period. Several cultural catalysts and deterrents emerged as factors that supported and hindered progress and sustainability of the emergent culture.
Cultivating a culture of continuous learning and improvement is possible. Purposeful consideration of the proposed model and identified factors from this report may yield important insights to advance understanding of how to cultivate a culture that facilitates continuous learning and improvement within a health care setting.
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.
High patient satisfaction is not simply a customer service goal; it is an important dimension of quality and part of financial incentives and public reporting requirements. However, patient experience is often siloed within health system organizational charts and considered separately from quality and safety initiatives, instead of being seen predominantly as a “customer service” initiative. Representatives from 52 health care systems across the United States completed an online survey to explore both the processes and infrastructure hospitals employ to improve patient experience, and the metrics hospitals use to assess the quality of patient experience beyond patient satisfaction survey data. When asked about performance metrics beyond satisfaction, most hospitals or systems noted other metrics of the entire patient experience such as the rate of complaints or grievances and direct feedback from patient and family advisors. Additionally, respondents suggested that a broader definition of “quality of the patient experience” may be appropriate to encompass measures of access, clinical processes, and quality of care and patient safety outcomes. Almost all respondents that we surveyed listed metrics from these less traditional categories, indicating that performance improvement within the patient experience domain in these organizations is linked with other areas of hospital performance that rely on the same metrics, such as clinical quality and patient safety.