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Predicting a patient's length of stay (LOS) in a hospital setting has been widely researched. Accurately predicting an individual's LOS can have a significant impact on a healthcare provider's ability to care for individuals by allowing them to properly prepare and manage resources. A hospital's productivity requires a delicate balance of maintaining enough staffing and resources without being overly equipped or wasteful. This has become even more important in light of the current COVID-19 pandemic, during which emergency departments around the globe have been inundated with patients and are struggling to manage their resources.

In this study, the authors focus on the prediction of LOS at the time of admission in emergency departments at Rhode Island hospitals through discharge data obtained from the Rhode Island Department of Health over the time period of 2012 and 2013. This work also explores the distribution of discharge dispositions in an effort to better characterize the resources patients require upon leaving the emergency department.

Objective. To quantify the association between obesity and somatic hospital costs and number of overall somatic hospital contacts – number of inpatient admissions, number of outpatient visits, and number of emergency department visits – based on anthropometric measurements of waist circumference (WC) and information from The National Patient Registry and The Danish Case-Mix System (DRG).

Participants. The study population consisted of two sub-samples from the Inter99 study at Research Centre for Prevention and Health in 1999–2001. One sub-sample used WC as an indicator for obesity (n=5,151), whereas the other used BMI as an indicator for obesity (n=4,048). Using WC, obesity was defined as WC > 102cm for men and > 88cm for women. Normal weight was defined as circumference < 94cm for men and < 80cm for women. Using BMI, obesity was defined as BMI > 30kg/m2, whereas individuals with BMI=18.5–24.9kg/m2 were defined as normal weight. Individuals with BMI < 18.5kg/m2 were excluded from both sub-samples.

Design. We undertook a 3-year retrospective study of the relationship between obesity and use of hospital resources. Data on hospital contacts and costs were obtained from The National Patient Registry and DRG. Analyses were performed using two-part models and Poisson regression. Outcome variables were costs and hospital contacts.

Results. This study has demonstrated that obese individuals have a greater use of hospital services and greater hospital costs compared with normal weight individuals. When using WC as an indicator for obesity, mean hospital costs were 33.8% greater among obese women and 45.3% greater among obese men in a 3-year period but the differences were not significant. When using BMI to measure obesity, obese men had significantly greater costs (57.5%) than normal weight men.

Furthermore, obese men and women (indicated byWC) had an increased number of hospital contacts compared with normal weight individuals (rate ratio 1.32, 95% CI 1.21–1.43 for men and 1.20, 95% CI 1.11–1.28 for women) including inpatient admissions, outpatient visits, and emergency department visits. The same trends were seen when obesity was indicated by BMI.

This chapter aims to provide suggestive evidence on how the Lombardy region dealt with the COVID-19 pandemic in 2020 and discuss future challenges for the Lombardy healthcare system. After an introduction to the wide spread of the virus inside the region, we describe the Lombardy health system so the reader may understand the context in which the virus has taken hold so quickly. The pandemic has heavily stressed the system, mainly because Lombardy experienced an excess of hospital admissions. We have considered the increased mortality rate as a proxy of the proper managing of the COVID-19 pandemic. In addition, we describe the process of treating non-COVID patients, such as those affected by acute myocardial infarction (AMI), stroke and oncological diseases. Despite the pandemic, hospitals have been able to guarantee a high level of performance. A discussion of the future evolution of the healthcare system concludes this chapter.

While there is established research that explores individual innovations across countries or developments in a specific health area, there is less work that attempts to match national innovations to specific systems of health governance to uncover themes across nations.

We used a cross-comparison design that employed content analysis of health governance models and innovation patterns in eight OECD nations (Australia, Britain, Canada, France, Germany, the Netherlands, Switzerland, and the United States).

Country-level model of health governance may impact the focus of health innovation within the eight jurisdictions studied. Innovation across all governance models has targeted consumer engagement in health systems, the integration of health services across the continuum of care, access to care in the community, and financial models that drive competition.

Improving our understanding of the linkage between health governance and innovation in health systems may heighten awareness of potential enablers and barriers to innovation success.

Patient handoffs involve the exchange of information between health professionals accompanying a transfer of responsibility for, or control of, a patient. Concerns over the safety risks of poor handoffs have resulted in regulatory pressure to standardize practice and considerable growth in research. But handoffs involve more than information transfer, and their consequences for health care organizations extend beyond the safety of patients. Using an organization theory lens, we review the literature on handoffs and propose a framework that characterizes handoffs as multifunctional, situated organizational routines. We also identify implications for researchers and hospital policymakers. Standardization and improvement efforts run the risk of causing unintended problems if they overlook the complexity of handoff and the larger organizational functions it serves. Deepening our understanding of the multifunctional, situated nature of handoff can lead to improvement efforts that not only safeguard individual patients, but also enhance the capabilities of the larger health care organization.

This essay addresses the topic of research lifeworlds and personal lifeworlds and what we gain and lose as researchers, and as people, from their overlaps and collisions. The essay analyses six narrative accounts of the authors lived experience of a unique collision between research and personal lifeworlds when the researcher-mother presented with her sick daughter to the hospital emergency department that served as the field site for her own research. This analysis revealed the following themes through which a researcher’s personhood animates the research process: feeling exposed but empowered; gaining conceptual clarity while opening up ethical ambiguity; and becoming liminal because of identity shifts and coping through self-reflexivity. The essay contributes to our collective understanding and shared learning of the ways a researcher’s personhood shapes, and is shaped by, the research process and (re)production of knowledge.

This chapter discussed the role of business intelligence (BI) in healthcare twofold strategic decision making of the organization and the stakeholders. The visualization techniques of data mining are applied for the early and correct diagnosis of the disease, patient’s satisfaction quotient and also helpful for the hospital to know their best commanders.

In this chapter, the usefulness of BI is shown at two levels: at doctor level and at hospital level. As a case study, a hospital is taken which deals with three different kinds of diseases: Breast Cancer, Diabetes, and Liver disorder. BI can be applied for taking better strategic decisions in the context of hospital and its department’s growth. At the doctor level, on the basis of various symptoms of the disease, the doctor can advise the suitable treatment to the patients. At the hospital level, the best department among all can be identified. Also, a patient’s type of admission, continued their treatments with the hospital, patient’s satisfaction quotient, etc., can be calculated. The authors have used different methods like Correlation matrix, decision tree, mosaic plots, etc., to conduct this analysis.

Health-care systems currently face great challenges, including an increasing elderly population. To respond to this problem, a hospital emergency department, three municipalities, and self-employed general practitioners in Denmark decided to collaborate with the aim of reorganizing treatment of elderly acute ill patients. By establishing a small-scale collaborative community and through an action research process, we show, how to jointly explore and develop a new organization design for in-home hospital treatment that enables the health professionals to collaborate in new ways, and at the same time to investigate and improve this cocreation process and codesign of knowledge among multiple different stakeholders.