ArticleEntropy (Basel, Switzerland)2023
Hospital Organizational Structure and Information Processing: An Entropy Perspective.
Article in Entropy (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Equipping mathematical models for hospital dynamics using information theory.NPJ digital medicine · 2025Article
- The Entropy Analysis Method for Assessing the Efficiency of Workload Distribution Among Medical Institution Personnel.Entropy (Basel, Switzerland) · 2025Article
- Patient coordination during the COVID-19 pandemic in the Amsterdam region: effects on capacity utilization and patient flow.BMC health services research · 2025Observational
- Slack Is Needed to Solve the Shortage of Nurses.Healthcare (Basel, Switzerland) · 2024Article
- Quantifying the Resilience of a Healthcare System: Entropy and Network Science Perspectives.Entropy (Basel, Switzerland) · 2023Article
- Entropy Optimization by Redesigning Organization in Hospital Operations.Entropy (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.