Exploring changes in integration, differentiation, rules, coordination and performance following the introduction of a hospital planning centre: a case study

Entropy Optimization by Redesigning Organization in Hospital Operations

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.

Hospital Organizational Structure and Information Processing: An Entropy Perspective

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.

Creating Coherence-Based Nurse Planning in the Perinatology Care System

The combination of increasing demand and a shortage of nurses puts pressure on hospital care systems to use their current volume of resources more efficiently and effectively. This study focused on gaining insight into how nurses can be assigned to units in a perinatology care system to balance patient demand with the available nurses. Discrete event simulation was used to evaluate the what-if analysis of nurse flexibility strategies and care system configurations from a case study of the Perinatology Care System at Radboud University Medical Center in Nijmegen, the Netherlands. Decisions to exercise nurse flexibility strategies to solve supply–demand mismatches were made by considering the entire patient care trajectory perspective, as they necessitate a coherence perspective (i.e., taking the interdependency between departments into account). The study results showed that in the current care system configuration, where care is delivered in six independent units, implementing a nurse flexibility strategy based on skill requirements was the best solution, averaging two fewer under-/overstaffed nurses per shift in the care system. However, exercising flexibility below or above a certain limit did not substantially improve the performance of the system. To meet the actual demand in the studied setting (70 beds), the ideal range of flexibility was between 7% and 20% of scheduled nurses per shift. When the care system was configured differently (i.e., into two large departments or pooling units into one large department), supply–demand mismatches were also minimized without having to implement any of the three nurse flexibility strategies mentioned in this study. These results provide insights into the possible solutions that can be implemented to deal with nurse shortages, given that these shortages could potentially worsen in the coming years.