ArticleHealth systems (Basingstoke, England)2019
Modelling competition in health care markets as a complex adaptive system: an agent-based framework.
Article in Health systems (Basingstoke, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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Who cites it
1 citing paper in PubMed.
- An agent-based model to advance the science of collaborative learning health systems.PloS one · 2025Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Health market reforms necessitate continuous re-evaluation of initiatives, competitive regulations, and antitrust policies. Synergistic implications, evolution, and behaviour changes associated with the market competition are often overlooked due to methodological limitations. To rectify these limitations, parallels between defining features of health care markets (HCM) and complex adaptive systems (CAS) are drawn. The science of CAS develops complex system-level models of dynamic interactions to allow insights for heterogeneous agents and emergent behaviours. Agent-based modelling (ABM) is a computational tool of CAS science suitable for investigating competition in HCM. The proposed agent-based framework conceptualises agents, environment, and interactions, and formalises agent-specific attributes and modules that achieve agent roles to recreate HCM dynamics. The framework conceptualises competition in HCM into an implementable ABM for a CAS assessment, identifies data sources, and develops face-validity procedures. Developments in data, computational power, and decisions theory compel CAS approach to complement studies on pressing HCM issues.
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