Complexity Science to Conceptualize Health and Disease: Is It Relevant to Clinical Medicine?

Jayasinghe, Saroj

doi:10.1016/j.mayocp.2011.11.018

Cited by 20 publications

(12 citation statements)

References 30 publications

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“…An appropriate conceptual basis is required to develop a tool to tackle CCSs at the bedside. One recently proposed approach is systems science, which perceives events and conditions in the human body in terms of a system [ 12 ]. Briefly, this views the human body to consist of several closely linked organ systems (or subsystems) that are embedded in and ‘open’ to the external environment (e.g.…”

Section: Proposalmentioning

confidence: 99%

Describing complex clinical scenarios at the bed-side: Is a systems science approach useful? Exploring a novel diagrammatic approach to facilitate clinical reasoning

Jayasinghe

2016

BMC Med Educ

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Clinicians often encounter patients having complex clinical scenarios (CCS) where diverse and dynamic diagnostic and therapeutic issues interact. A limited range of bedside methods are available to describe such patients and most often it is a diagnostic summary, a problem list, or a list of differential diagnoses. These methods fail to portray the interconnected nature of CCCs. They prevent visualization of a system of networks or a web of causation operative in CCSs.A more holistic conceptualization is required and the author argues for an approach based on systems science. The latter views the human body to consist of several closely linked organ systems, constantly interacting with each other and embedded in, and ‘open’ to the external environment. In order to capture the systems nature at bedside, a tool based on network diagrams, termed a Clinical Reasoning Map (CRM) is proposed which depicts diseases or conditions as nodes linked to each other by lines or arrows. The latter linkages follow simple rules: possible causes or associations as mere lines; probable cause using a single dotted arrow with directionality (from ‘cause’ to ‘effect’); definite causal pathways by directional arrows; and bi-directional arrows to indicate organs-systems influencing each other.CRM’s utility was investigated in several groups of undergraduate medical students. The results varied: 289, 5th year and 4th year medical students showed that 245 (85.5 %) perceived CRM improve their understanding of the case. However, there was no clear advantage in the CRM over a list of diagnoses in recall of key information. A majority (83.9 %) were keen to learn the technique of drawing a CRM. Postgraduates too found the tool to be useful to understand the interconnected nature of real-life complex case scenarios and pathogenesis of their multifaceted condition to generate differential diagnosis and to select appropriate investigations. Effectiveness of CRM is supported by adult learning theories such as meaningful learning and experiential learning.The author proposes that systems science and tools based in this approach such as CRM has utility in understanding and managing complex case scenarios. They differ significantly from other diagrammatic methods available in the medical literature.

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Section: Proposalmentioning

confidence: 99%

Describing complex clinical scenarios at the bed-side: Is a systems science approach useful? Exploring a novel diagrammatic approach to facilitate clinical reasoning

Jayasinghe

2016

BMC Med Educ

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“…With the enormous intricacy of the system, new approaches to conceptualization of the health care system called “complexity science” (Hast, Digioia, Thompson, & Wolf, 2013; Jayasinghe, 2012; West, 2012) may be important to contemplate. Complexity science actually takes us back to a systems biology approach which was introduced in discussing the integration of behavior and physiology within any well-regulated systems.…”

Section: Controllability and Caregiversmentioning

confidence: 99%

“Anatomy of an Illness”: Control from a caregiver’s perspective

Laudenslager

2014

Brain, Behavior, and Immunity

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Caregivers of loved ones with chronic illnesses experience an uncontrollable challenge with potentially negative behavioral and medical consequences. Extensive research has demonstrated immune and endocrine regulation can be significantly disrupted by negative behavioral factors based on both animal models and human studies. However, fewer studies have focused on how psychosocial interventions might reverse the negative consequences of stressors such as caregiving. The distress of caring for individuals with cancer has only recently begun to receive attention. These interventions addressing caregiver distress are rare overall and caregivers of patients receiving hematopoietic stem cell transplants (HSCT) have received even less attention. HSCT caregivers report feelings of loss of control. Animal studies suggest that control over aversive events can mitigate the negative consequences of stressors. Caregivers of allogeneic HSCT patients for blood cancers must be available 24/7 for three months or longer following stem cell infusion to closely monitor the recipients’ health and well-being. Does establishing a greater sense of control have positive impacts on caregivers? A randomized control trial of a cognitive behavioral stress management intervention for allogeneic HSCT caregivers is briefly described. A model of caregiver mental health which may potentially impact the patient’s quality of life is proposed. These relationships exist in a complex system that includes genetic influences, sex, social environment, and prior experience. This system fits well within recent formulations of a “complexity science” approach to health and well-being.

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“…In recent times there has been an interest in the utility of a systems science approach that captures the combined and inter-related effects of multiple parameters in determining severity of illnesses [ 24 ]. Our study is an attempt to take a systems science view of severity and develop a mathematical model to capture the combined effect of multiple inflammatory mediators that are elevated in dengue.…”

Section: Introductionmentioning

confidence: 99%

Mathematical modelling and a systems science approach to describe the role of cytokines in the evolution of severe dengue

et al. 2017

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BackgroundDengue causes considerable morbidity and mortality in Sri Lanka. Inflammatory mediators such as cytokines, contribute to its evolution from an asymptotic infection to severe forms of dengue. The majority of previous studies have analysed the association of individual cytokines with clinical disease severity. In contrast, we view evolution to Dengue Haemorrhagic Fever as the behaviour of a complex dynamic system. We therefore, analyse the combined effect of multiple cytokines that interact dynamically with each other in order to generate a mathematical model to predict occurrence of Dengue Haemorrhagic Fever. We expect this to have predictive value in detecting severe cases and improve outcomes. Platelet activating factor (PAF), Sphingosine 1- Phosphate (S1P), IL-1β, TNFα and IL-10 are used as the parameters for the model. Hierarchical clustering is used to detect factors that correlated with each other. Their interactions are mapped using Fuzzy Logic mechanisms with the combination of modified Hamacher and OWA operators. Trapezoidal membership functions are developed for each of the cytokine parameters and the degree of unfavourability to attain Dengue Haemorrhagic Fever is measured.ResultsThe accuracy of this model in predicting severity level of dengue is 71.43% at 96 h from the onset of illness, 85.00% at 108 h and 76.92% at 120 h. A region of ambiguity is detected in the model for the value range 0.36 to 0.51. Sensitivity analysis indicates that this is a robust mathematical model.ConclusionsThe results show a robust mathematical model that explains the evolution from dengue to its serious forms in individual patients with high accuracy. However, this model would have to be further improved by including additional parameters and should be validated on other data sets.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-017-0415-3) contains supplementary material, which is available to authorized users.

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Complexity Science to Conceptualize Health and Disease: Is It Relevant to Clinical Medicine?

Cited by 20 publications

References 30 publications

Describing complex clinical scenarios at the bed-side: Is a systems science approach useful? Exploring a novel diagrammatic approach to facilitate clinical reasoning

Describing complex clinical scenarios at the bed-side: Is a systems science approach useful? Exploring a novel diagrammatic approach to facilitate clinical reasoning

“Anatomy of an Illness”: Control from a caregiver’s perspective

Mathematical modelling and a systems science approach to describe the role of cytokines in the evolution of severe dengue

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