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In this study, we consider the human body and the healthcare system as two complex networks and use theories regarding entropy, requisite variety, and network centrality metrics with resilience to assess and quantify the strengths and weaknesses of healthcare systems. Entropy is used to quantify the uncertainty and variety regarding a patient’s health state. The extent of the entropy defines the requisite variety a healthcare system should contain to be able to treat a patient safely and correctly. We use network centrality metrics to visualize and quantify the healthcare system as a network and assign the strengths and weaknesses of the network and of individual agents in the network. We apply organization design theories to formulate improvements and explain how a healthcare system should adjust to create a more robust and resilient healthcare system that is able to continuously deal with variations and uncertainties regarding a patient’s health, despite possible stressors and disturbances at the healthcare system. In this article, these concepts and theories are explained and applied to a fictive and a real-life example. We conclude that entropy and network science can be used as tools to quantify the resilience of healthcare systems.

In the original publication [...]

Background: The literature on measuring the complexity of production systems employs the graph and information theory. This study analyzes these systems and their coordination under varying states of control, with a focus on the probability of unfavorable events and their temporal characteristics. Methods: Coordination systems are represented as temporal networks, using entropy and node influence metrics. Two case studies are presented: a factory operating under the principles of the Toyota Production System (TPS) with adjacent (local) coordination and andon (global) coordination and a university obstetrics clinic with only adjacent (local) coordination. Results: Adjacent coordination leads to zero entropy in 38.40% of all situations in the TPS example, contrasted to 76.62% in the same system with andon coordination. Degree centrality of nodes outside of zero-entropy situations exhibits higher average and maximum values in andon coordination networks, compared to those with adjacent coordination in TPS. Entropy values in the university obstetric clinic range from 0.92 to 2.23, average degrees vary between 3 and 4.08, and maximum degrees range from 7 to 9. Conclusions: Coordination systems modeled as temporal networks capture the evolving nature of centralizing and decentralizing coordination in production systems.

Background/Objectives: Elderly patients who require aftercare in an intramural care (IMC) facility may contribute to “bed blocking,” which occurs when patients who are ready for discharge remain hospitalized longer than medically necessary. While most bed-blocking studies focus on capacity issues, this study also investigates the coordination process. In a regional hospital in the Netherlands, we examine the extent to which bed blocking occurs due to patients awaiting IMC, and how this issue can be characterized in terms of capacity and coordination challenges. Methods: The case study employs a mixed-methods approach, analyzing system data, documents, and interviews from the hospital, IMC organizations, and a health insurance provider. The location of each patient (organization and department) was collected and reconstructed to a patient path. All patient paths together formed a network enabling data analysis both on the level of patient paths as well as on the level of the networks as they developed through time. This gave insight into the complexity of the total network that has to be coordinated. Results: In 2023, 6% of the hospital capacity was occupied by patients awaiting IMC. Delays were observed at various coordination stages. Due to a lack of data on IMC bed capacity, we were unable to establish whether capacity limitations also contributed to bed blocking. Conclusions: The coordination system is complex and includes waiting times at each coordination stage, resulting in bed blocking. The absence of a centralized capacity overview, coupled with limited data, prevents decision-makers from identifying bed blocking arising from capacity shortages. Greater insight is needed to coordinate patient flow and determine the required slack capacity.

Background: Delivering sustainable, high-quality eye care requires a comprehensive understanding of patient conditions, clinical evidence, patients’ preferences, demand patterns, quality supplies, outcomes, financial sustainability, and satisfaction metrics. Evidence-based management (EBM) offers a structured approach to align actions with evidence, enabling effective decision-making and better organizational outcomes. Evaluating current practices against EBM principles fosters awareness and promotes an EBM culture in eye hospitals, supporting improved and sustainable service delivery. Methods: A descriptive cross-sectional survey was conducted in 2023–2024 among 94 eye hospitals worldwide, selected from two networks, using the Centre for Evidence-Based Management (CEBM) assessment questionnaire. Follow-up reminders resulted in 43 responses. Data analysis utilized frequency distributions and Pearson’s correlation to explore relationships between variables. Results: A strong positive correlation was observed between data accessibility and the capacity to interpret data in fostering evidence-based decision-making (r = 0.69, p < 0.01). Additionally, leveraging internal expertise and engaging stakeholders in assessing and utilizing data showed a moderate association with EBM practices (r = 0.48, p < 0.01). Conclusions: Eye hospitals demonstrate alignment with EBM principles, though regional variations exist. Organizations with robust data utilization systems, analytical expertise, and a commitment to continuous improvement are more effective in practicing EBM. Educational and peer-learning initiatives can further support hospitals in adopting EBM principles, strengthening their capacity for evidence-based decision-making, and enhancing eye care services.

The healthcare and education sectors suffer from shortages of nurses and teachers. Extending their working hours has often been proposed as a solution to reduce shortages. In this study, we conduct a discrete choice experiment (DCE) in the Netherlands to elicit nurses’ and teachers’ preferences for different jobs and working conditions. We present both nurses and teachers with nine hypothetical choice sets, each consisting of two jobs that differ in seven observable job attributes. From the DCE, we infer workers’ willingness to pay for these different job characteristics. Moreover, we calculate how many additional hours they would be willing to work if a specific workplace condition were met. We find that both nurses and teachers most negatively value high work pressure. Spending a lot of time on patient-related tasks is highly valued by nurses, followed by having more control over working hours. Next to work pressure, teachers place significant importance on receiving social support from both colleagues and managers. Part-time teachers and nurses require a 23 and 21 percent increase in net hourly wages to accept a full-time working contract, respectively.

Organizational structure enables organizations to achieve their goals. The chosen organizational structure determines, to a large extent, the flow of information streams and the manner and extent to which roles, power, and responsibilities are delegated and coordinated to achieve the organization’s goals. In this study, we applied information theory with entropy as the central concept to assess the effectiveness and costs of an organizational structure and its coordination processes. Entropy was used to measure the amount of uncertainty associated with probabilistic events. In the context of organizational design, entropy values can be assigned to specific organizational structures to gain insights into the factors that lead to delays in decision-making. We used Shannon’s entropy theory to quantify Galbraith’s organizational structure and coordination process as applied to the perinatology care system of Radboud University Medical Centre in the Netherlands. Our entropy analysis provided insights into how departments should be partitioned and which coordination mechanisms should be used to achieve organizational goals, such as minimizing delays in decision-making. Particularly, two types of entropy appear to be important: positional entropy and task allocation entropy. These are different dependent variables on the organizational design scenarios. Our analysis shows that entropy is one method to determine optimal organizational structures and coordination processes. Entropy can be used as a concrete way of assessing the effectiveness of organizational design given the level of uncertainty of the environment and the required speed of decision-making.

A lack of nurses is a prevalent and persistent problem in many countries [...]

Both the healthcare and education sector suffer from considerable staff shortages. In the healthcare sector, shortages are particularly prominent for nurses, while the education sector experiences significant teacher shortages. In this systematic literature review, we examine the effectiveness of interventions and policies to reduce staff shortages in healthcare and education in high-income countries. We focus our analysis on studies that apply research designs that allow for causal inference to inform policymakers about the effectiveness of interventions. In total, we include 85 studies that meet our inclusion criteria. Out of these studies, 71 studies focus on teachers and 14 on nurses, and 72 of the retrieved studies were conducted in the US. The majority of studies examine the impact of financial incentives and a large share of these studies report positive effects on teacher employment. Moreover, different types of interventions that invest in workers’ human capital show predominantly positive effects on employment. Interventions that equip nurses with skills to better cope with the stressors of their profession seem to be particularly effective. The same holds for policies that increase the scope of practice for nurses. Finally, effective school leaders are better capable of retaining (high-quality) teachers.

A redesign of hospitals (i.e., partitioning departments and delegating decision authority) may be needed to deal with variable demand. Uncertain demands and throughput times often need short reaction times. In this study, we develop quantitative methods to guide a redesign through an information-processing approach. To demonstrate how the methods can be used in practice, we tested them by applying them to a large perinatology care system in the Netherlands. We used the following two methods: 1. portfolio optimization and 2. efficient coordination of workload and reallocation of nurses. Our case study of a large perinatology care system showed that several designs of clustered units minimized the demand uncertainty in the perinatology care system. For the coordination strategy, the information and decision uncertainty is minimized when the decision power is positioned at the operation level and with the help of a centralized information system. When the operation decision-making power is not supplemented with the centralized and system-wide information system, hospitals can better use the hierarchy model, where the manager holds decision-making power with a system-wide overview. We also found that the speed of decision-making in real-time depends on the level of information aggregation set up by the system. We conclude that combining the correlation perspectives and the entropy theory is a way of quantifying how organizations can be (re)designed.