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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.

Research suggests that improving hospital work environments and solving the nursing shortage are critical to improving patient care. The Houston–Galveston region created an aggressive approach to this issue by forming an unusual coalition of business, university, and hospital leaders and using a quality improvement approach. Four years later, the project has achieved over 40% participation among hospitals in the 13-county region and includes 50 hospitals employing approximately 15,000 registered nurses. The data that have been collected by this collaborative to date suggests that hospitals are taking action to improve outcomes by modifying their key initiatives to address the attributed causes of poor work environments. From 2004 to 2005, executives of top performing hospitals increasingly attributed successful work environment outcomes to an emphasis on management development and executive-driven initiatives, de-emphasizing specific employee behavior, process, and outcome-based initiatives.

Research on hospital productivity has progressed over the last few decades considerably from early models where measurements of hospital services simply counted inpatient days, and perhaps outpatient visits or numbers of surgeries performed. This simplicity represents an extreme of aggregation, focuses the attention of the analysis entirely on the structure of the organization at the highest levels, and provides no insight into the specific services that might be provided to each patient as well as the characteristics of those patients, which might lead to specialization of their care. This process is fundamentally complex, which makes it especially difficult to model. This table-setting chapter will characterize some of the key contextual choices that must be made by researchers in this field which are then applied in subsequent chapters. The key point of this chapter will be to argue that there are very few “one size fits all” decisions in this process and thus the context of particular research objectives and questions will determine how modeling choices are made in practice. Some intuition about how these decisions have substantial implications for outcomes of measurement for hospital productivity will be provided; however, no attempt will be made to conduct a literature review of all the choices that have been made. Instead, we will suggest that new careful attention to the choices made can make future studies more effective in communicating to the communities implementing the research.

It is well recognized that hospitals do not operate in a competitive market typically observed in the economics literature, but rather alternative measures of performance must be developed. In other words, health policy analysts, managers, and decision-makers cannot rely on determining efficiency via the typical profit maximizing/cost minimizing firm but develop techniques that address the issues germane to hospital productivity. What has been presented in this book demonstrates the research in both productivity and policy that must attend to this anomaly. In this introductory section, we briefly summarize the theoretical underpinnings of this book.

Hospitals worldwide command the majority of any countries’ health care budget. Reasons for these higher costs include the aging of the population requiring more intensive health care treatments provided in hospitals, the relatively high costs of labor in this labor intensive industry and payment systems that may encourage inefficient behavior on the part of hospital managers and physicians, that have not been fully mitigated via reforms and regulations.

Tactical capacity planning is crucial when hospitals must cope with substantial changes in patient requirements, as recently experienced during the Covid-19 pandemic. However, there is only little understanding of the nature of capacity limitations in a hospital, which is essential for effective tactical capacity planning.

We report a detailed analysis of capacity limitations at a Norwegian tertiary public hospital and conducted 22 in-depth interviews. The informants participated in capacity planning and decision-making during the Covid-19 pandemic. Data are clustered into categories of capacity limitations and a correspondence analysis provides additional insights.

Personnel and information were the most mentioned types of capacity limitations, and middle management and organizational functions providing specialized treatment felt most exposed to capacity limitations. Further analysis reveals that capacity limitations are dynamic and vary across hierarchical levels and organizational functions.

Future research on tactical capacity planning should take interdisciplinary patient pathways better into account as capacity limitations are dynamic and systematically different for organizational functions and hierarchical levels.

We argue that our study possesses common characteristics of tertiary public hospitals, including professional silos and fragmentation of responsibilities along patient pathways. Therefore, we recommend operations managers in hospitals to focus more on intra-organizational information flows to increase the agility of their organization.

Our detailed capacity limitation analysis at a tertiary public hospital in Norway during the Covid-19 pandemic provides novel insights into the nature of capacity limitations, which may enhance tactical capacity planning.

Strategic leadership plays an important role in achieving organizational success in surviving and growing in a challenging business environment. This study aims to examine the role of strategic leadership in responding to a rare moment in the health industry, which is the combination of government regulations that tend to continue to change and the emergence of COVID-19 pandemic.

A total of 358 respondents from 141 type C and D hospitals in Indonesia participated in this research. This study used six latent variables and 27 dimensions, processed using structural equation modeling.

The results of this study confirmed that resilient leaders will not seek new partners by developing network capabilities; but rather choose to save the hospital first, by resources reconfiguration as response to the unanticipated adversity caused by fusing the government regulation and emergence of the COVID-19 pandemic.

This study makes an important contribution that enables hospital management to develop action plans in response to national health-care regulations coupled with the emergence and extension of the COVID-19 pandemic; as well as the results of the investigation into organizational resources, and to implement strategic resilience capability more effectively.

Staff shortages in the healthcare sector increase the competition for qualified staff. A magnet hospital is intended to attract, and retain healthcare professionals. This article aims to investigate the challenges related to implementation of a magnet hospital model, and given these challenges, to analyse the interplay between different organisational levels in a Swedish hospital.

The data collection followed the implementation of a magnet hospital model and consisted of 14 meeting observations, 31 interviews and 13 document analyses.

The model implementation was driven by a top-down approach, with accompanying bottom-up activities, involving healthcare professionals, to ensure adaption to the hospital’s conditions at different organisational levels. The findings revealed that the model was more appealing to top management, seeking a standardised solution to attract and retain nurses. Clinic managers preferred tailor-made solutions for managing their employee resourcing challenges. Difficulties in translating and contextualising the model to the hospital’s conditions created challenges at every organisational level. Some were contained within a level while others spread to the organisational level below and turned into something else.

Apart from unique empirical material depicting the implementation of a magnet hospital model as an effort to attract and retain healthcare professionals, the value of this study lies in the attention given to the challenges that arise when responsibility for implementing a management model is shifted from top management to change agents tasked with facilitating and executing the organisational change.

The adoption of digital technology has not been able to overcome the problem of patient healthcare service quality in Indonesian hospitals, especially in lower middle-class hospitals that are widely distributed in the regions, because its utilization has not been well coordinated. This research explores the influence of Digital Adoption Capability (DAC) on Hospital Performance (HP) for these service problems.

This research used a quantitative methodology design approach. Survey data were collected from 285 leaders of class C and D hospitals throughout Indonesia, who were selected at simple random from March to August 2023. Data analysis was carried out using the structural equation modeling method with the help of LISREL version 8.80 software.

The research found a positive and significant influence of DAC on HP. Digital Leadership (DL) plays an important role in performance, both directly and indirectly. ICT Literacy (ICT) and Patient-Centric (PC) do not have a direct influence on HP but provide significant results through DAC. This research also found Environmental Dynamism (ED) factors that significantly drive the need to improve performance through digital adoption.

Providing insight into increasing the role of digital technology to connect healthcare workers and patients to produce safe and quality healthcare services in an ever-changing environmental condition.

This model is very important for the management of small hospital organizations in the context of adopting digital technology to be able to provide better services to patients and improve hospital performance.

Identifying the perception of competition between public and private providers in the national hospital market can help authorities to develop appropriate management strategies applicable to the hospital sector and increase the efficiency of public hospital institutions.

A mixed selective descriptive study including quantitative and qualitative components was carried out on in the Republic of Moldova between 12/2021 and 03/2022. The study included all hospitals in the country. The study revealed the hospital manager's perception of the hospital's competition as respondents to the questionnaire were only the directors and managers of hospital institutions. The concept of evaluation of the perception of competition was carried out through the lens of “Porter's 5 forces” from “Competitive strategies” by Michael E. Porter. The authors used a questionnaire as an instrument for studying the perception of competition. All study participants responded to both the quantitative and qualitative questionnaire.

Interhospital competition perceived by managers using model framework of “Porter's 5 forces” reveals high danger from service providers and high perception of rivalry; hospital directors perceived as low: the patient's bargaining power; the danger of new competitors entering the market; the danger of substitution, which constitutes competitive advantages; the lack of autonomy in the selection of services and patients and legislative barriers are the main perceived dissensions. The perception of competition between public and private hospitals is one with high rivalry, especially in the country's municipalities.

The national public hospital system takes up to 65% of the health budget being extremely expensive, a fact that indicates a rather low competitiveness of them. The European average indicates figures of 30–40%. The private hospital sector is less developed compared to most European countries, being represented by 17 institutions, in comparison Romania has 104 private hospitals representing about 25% of the market share. Private hospitals also occupy a considerable part of the European hospital healthcare market, continuing to increase, reaching over 30% in Germany.