Advances in Health Care Management最新文献

Leading health care institutions have recommended greater alignment among health care and social services organizations as a strategy to improve population health. Deepening our understanding of how interorganizational relationships among health care and social service organizations influence care for people with complex needs could improve the design of interventions aimed at aligning these organizations to achieve health goals. Accordingly, we used qualitative methods to (1) elucidate the functions performed by health care and social service organizations caring for older adults and (2) investigate corresponding relationship forms. In-depth interviews with 175 representatives of health care and social service organizations in 10 communities were analyzed. Three distinct interorganizational relationships functions emerged: First, interorganizational relationships gave organizations a deeper and more accurate understanding of how their work was interdependent with the work of other organizations in the community. This function was achieved through coalitions that loosely tied large numbers of organizations and allowed information to flow among them. Second, interorganizational relationships allowed organizations to take joint action toward a shared goal, a function achieved in the form of pairs or small groups of organizations working closely together. Third, interorganizational relationships fostered accountability, with one organization advocating for the needs of clients or patients with another organization. Our results suggest that initiatives to promote regional alignment among health care and social services organizations may benefit from flexible models that anticipate a narrowing of partners to achieve tangible outcomes. Initiatives also need to accommodate low-level conflict that routinely exists among organizations in these sectors.

Health-care professionals undergo numerous training programs each year in order to fulfill licensure requirements and organizational obligations. However, evidence suggests that a substantial amount of what is taught during training is never learned or transferred back to routine work. A major contributor to this issue is low training motivation. Prior conceptual models on training transfer in the organizational sciences literature consider this deficit, yet do not account for the unique conditions of the hospital setting. This chapter seeks to close this gap by adapting conceptual models of training transfer to this setting that are grounded in organizational science. Based on theory and supplemented by semistructured key informant interviews (i.e., organizational leaders and program directors), we introduce an applied model of training motivation to facilitate training transfer in the hospital setting. In this model, training needs analysis is positioned as a key antecedent to ensure support for training, relevant content, and perceived utility of training. We posit that these factors, along with training design and logistics, enhance training motivation in hospital environments. Further, we suggest that training motivation subsequently impacts learning and transfer, with elements of the work environment also serving as moderators of the learning-transfer relationship. Factors such as external support for training content (e.g., from accrediting bodies) and allocation of time for training are emphasized as facilitators. The proposed model suggests there are factors unique to the hospital work setting that impact training motivation and transfer that should be considered when developing and implementing training initiatives in this setting.

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.

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.

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.

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.