scholarly journals Performance management in complex adaptive systems: a conceptual framework for health systems

2021 ◽  
Vol 6 (7) ◽  
pp. e005582
Author(s):  
Tom Newton-Lewis ◽  
Wolfgang Munar ◽  
Tata Chanturidze
Keyword(s):  
Performance Management ◽  
Health Systems ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Collective Responsibility ◽  
System Level ◽  
Empirical Literature ◽  
Current Evidence ◽  
Current Evidence Base ◽  
Complex Adaptive

Existing performance management approaches in health systems in low-income and middle-income countries are generally ineffective at driving organisational-level and population-level outcomes. They are largely directive: they try to control behaviour using targets, performance monitoring, incentives and answerability to hierarchies. In contrast, enabling approaches aim to leverage intrinsic motivation, foster collective responsibility, and empower teams to self-organise and use data for shared sensemaking and decision-making.The current evidence base is too limited to guide reforms to strengthen performance management in a particular context. Further, existing conceptual frameworks are undertheorised and do not consider the complexity of dynamic, multilevel health systems. As a result, they are not able to guide reforms, particularly on the contextually appropriate balance between directive and enabling approaches. This paper presents a framework that attempts to situate performance management within complex adaptive systems. Building on theoretical and empirical literature across disciplines, it identifies interdependencies between organisational performance management, organisational culture and software, system-level performance management, and the system-derived enabling environment. It uses these interdependencies to identify when more directive or enabling approaches may be more appropriate. The framework is intended to help those working to strengthen performance management to achieve greater effectiveness in organisational and system performance. The paper provides insights from the literature and examples of pitfalls and successes to aid this thinking. The complexity of the framework and the interdependencies it describes reinforce that there is no one-size-fits-all blueprint for performance management, and interventions must be carefully calibrated to the health system context.

scholarly journals Irrational use of antibiotics in Iran from the perspective of complex adaptive systems: redefining the challenge

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zahra Sharif ◽  
Farzad Peiravian ◽  
Jamshid Salamzadeh ◽  
Nastaran Keshavarz Mohammadi ◽  
Ammar Jalalimanesh
Keyword(s):  
Health Systems ◽  
Information Flow ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Emergent Behavior ◽  
System Level ◽  
Antibiotics Resistance ◽  
Policy Document ◽  
Complex Adaptive ◽  
Antibiotics Use

Abstract Background Irrational use of antibiotics is proving to be a major concern to the health systems globally. This results in antibiotics resistance and increases health care costs. In Iran, despite many years of research, appreciable efforts, and policymaking to avoid irrational use of antibiotics, yet indicators show suboptimal use of antibiotics, pointing to an urgent need for adopting alternative approaches to further understand the problem and to offer new solutions. Applying the Complex Adaptive Systems (CAS) theory, to explore and research health systems and their challenges has become popular. Therefore, this study aimed to better understand the complexity of the irrational use of antibiotics in Iran and to propose potential solutions. Method This research utilized a CAS observatory tool to qualitatively collect and analyse data. Twenty interviews and two Focus Group discussions were conducted. The data was enriched with policy document reviews to fully understand the system. MAXQDA software was used to organize and analyze the data. Result We could identify several diverse and heterogeneous, yet highly interdependent agents operating at different levels in the antibiotics use system in Iran. The network structure and its adaptive emergent behavior, information flow, governing rules, feedback and values of the system, and the way they interact were identified. The findings described antibiotics use as emergent behavior that is formed by an interplay of many factors and agents over time. According to this study, insufficient and ineffective interaction and information flow regarding antibiotics between agents are among key causes of irrational antibiotics use in Iran. Results showed that effective rules to minimize irrational use of antibiotics are missing or can be easily disobeyed. The gaps and weaknesses of the system which need redesigning or modification were recognized as well. Conclusion The study suggests re-engineering the system by implementing several system-level changes including establishing strong, timely, and effective interactions between identified stakeholders, which facilitate information flow and provision of on-time feedback, and create win-win rules in a participatory manner with stakeholders and the distributed control system.

scholarly journals Irrational use of antibiotics in Iran from the Perspective of Complex Adaptive Systems: redefining the challenge

2020 ◽  
Author(s):  
Zahra Sharif ◽  
Farzad Peiravian ◽  
Jamshid Salamzadeh ◽  
Nastaran Keshavarz Mohammadi ◽  
Ammar Jalalimanesh
Keyword(s):  
Health Systems ◽  
Information Flow ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Emergent Behavior ◽  
System Level ◽  
Antibiotics Resistance ◽  
Policy Document ◽  
Complex Adaptive ◽  
Antibiotics Use

Abstract Background: Irrational use of antibiotics is proving to be major concern to the health systems globally. It results in antibiotics resistance and increases health care costs. In Iran, many years of research, appreciable efforts and policy making have been of little avail and indicators still show suboptimal use of antibiotics, pointing to an urgent need for adopting an alternative approach to understanding the problem and generating new solutions. Applying the Complex Adaptive Systems theory, to explore and research in health systems and their challenges has become popular. Therefore, this study aimed to better understand the complexity of irrational use of antibiotics use in Iran and to propose potential solutions. Method: This research utilized a CAS observatory tool to qualitatively collect and analyse data. Twenty interviews and two Focus Group Discussion were conducted. The data was enriched with policy document reviews to fully understand the system. MAXQDA software was used to organize and analyze the data. Result: We could identify several diverse and heterogeneous, yet highly interdependent agents operating at different levels in the antibiotics use system in Iran. The network structure and its adaptive emergent behavior, information flow, governing rules, feedback and values of the system, and the way they interact were identified. The findings describe antibiotics use as an emergent behavior which is formed by an interplay of many factors and agents over time. Insufficient and ineffective interaction and information flow regarding antibiotics between agents were among key causes of irrational antibiotics use in Iran. Results showed that effective rules to minimize irrational use of antibiotics are missing or can be easily disobeyed. The gaps and weakness of the system which needs redesigning or modification were recognized as well. Conclusion: The study suggests re-engineering the system by implementing several system-level changes including establishing strong, timely, and effective interactions between identified stakeholders, which facilitate information flow and provision of on-time feedback, and create win-win rules in a participatory manner with stakeholders and the distributed control system.

scholarly journals Irrational use of antibiotics in Iran from the Perspective of Complex Adaptive Systems: redefining the challenge

2020 ◽  
Author(s):  
Zahra Sharif ◽  
Farzad Peiravian ◽  
Jamshid Salamzadeh ◽  
Nastaran Keshavarz Mohammadi ◽  
Ammar Jalalimanesh
Keyword(s):  
Health Systems ◽  
Information Flow ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Antibiotic Use ◽  
Analysis Data ◽  
Antibiotic Consumption ◽  
System Level ◽  
Antibiotics Resistance ◽  
Complex Adaptive

Abstract Background: Irrational use of antibiotics proves major concerns to the health systems globally. It results in antibiotics resistance and increases health care costs. In Iran, many years of research, appreciable efforts and policy making have been of little avail and indicators still show suboptimal use of antibiotics, pointing out an urgent need to alternative approach to understand the problem and generate new solutions. Applying the Complex Adaptive Systems theory, to explore and research in health systems and their challenges and has become popular. Therefore, this study was aimed to better understand the complexity of irrational use of antibiotic use in Iran and the potential solutions. Method: This research utilized a CAS observatory tool to qualitatively collect and analysis data. Many interviews with key informants were conducted. The data was enriched with documents reviews in order to fully understand the system. MAXQDA software was applied to organize and analyze the data. Result: We could identify several diverse and heterogeneous, yet highly interdependent agents in the antibiotic consumption system in Iran, operating at different levels. The network structure and its adaptive emergent behaviour, information flow, governing rules, feedbacks and values of the system and the way they interact were identified. The gaps and weakness of the system which needs redesigning or modification were recognized as well. Findings describe antibiotic use as an emerge behavior of the system which is formed by interplay of many factors and actors over time.Conclusion: The study suggests re-engineering the system by implementing several system level changes including establishing strong, timely and effective interactions between identified stakeholders which facilitate information flow and provision of on time feedbacks, create win-win rules in participatory manner with stakeholders and distributed control system.

scholarly journals A health systems resilience research agenda: moving from concept to practice

2021 ◽  
Vol 6 (8) ◽  
pp. e006779
Author(s):  
Dell D Saulnier ◽  
Karl Blanchet ◽  
Carmelita Canila ◽  
Daniel Cobos Muñoz ◽  
Livia Dal Zennaro ◽  
...  
Keyword(s):  
Health System ◽  
Health Systems ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Dynamic Performance ◽  
Performance Outcomes ◽  
Theoretical Research ◽  
Systems Research ◽  
Complex Adaptive ◽  
System Resilience

Health system resilience, known as the ability for health systems to absorb, adapt or transform to maintain essential functions when stressed or shocked, has quickly gained popularity following shocks like COVID-19. The concept is relatively new in health policy and systems research and the existing research remains mostly theoretical. Research to date has viewed resilience as an outcome that can be measured through performance outcomes, as an ability of complex adaptive systems that is derived from dynamic behaviour and interactions, or as both. However, there is little congruence on the theory and the existing frameworks have not been widely used, which as diluted the research applications for health system resilience. A global group of health system researchers were convened in March 2021 to discuss and identify priorities for health system resilience research and implementation based on lessons from COVID-19 and other health emergencies. Five research priority areas were identified: (1) measuring and managing systems dynamic performance, (2) the linkages between societal resilience and health system resilience, (3) the effect of governance on the capacity for resilience, (4) creating legitimacy and (5) the influence of the private sector on health system resilience. A key to filling these research gaps will be longitudinal and comparative case studies that use cocreation and coproduction approaches that go beyond researchers to include policy-makers, practitioners and the public.

scholarly journals A complex systems model for transformative supply chains in emerging markets

2019 ◽  
Vol 15 (1) ◽  
pp. 50-69
Author(s):  
Ruth Yeoman ◽  
Milena Mueller Santos
Keyword(s):  
Supply Chain ◽  
Emerging Markets ◽  
Supply Chains ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Emerging Market ◽  
System Level ◽  
Value Chains ◽  
Content Type ◽  
Complex Adaptive

Purpose Corporations operating global value chains must grapple with a multiplicity of ethical and practical considerations, most notably when value chains extend to emerging markets. Such contexts involve interactions with diverse stakeholders who possess the ability to impact supply chain performance, but who also bring conflicting needs, values and interests. The purpose of this paper is to outline a transformative model of supply chain fairness, arguing that adopting plural fairness principles and practices generates a higher fairness equilibrium which includes all affected stakeholders in the production of fairness outcomes, with consequent positive organizational and system level impacts. Design/methodology/approach Through a philosophically informed overview of the literature on organizational fairness, the paper applies fairness to the management of supplier relations to identify the institutional features of ethically sustainable supply chains. The proposed conceptual model uses a complex adaptive systems approach (CADs), supplemented by describing the contribution of fairness norms and practices. Findings This paper argues that a transformative approach to supply chain fairness can suggest new structures for interaction between firms, stakeholders, mediating institutions and governments. Originality/value Emerging market supply chains are facing significant changes. Adopting a complex adaptive systems perspective upon stakeholder relationships, this paper offers insights from the theoretical literature on fairness, and proposes a normative model of supply chain fairness which accounts for both the normative and empirical aspects of relational complexity.

scholarly journals Findings of Case-Study Analysis: System-Level Biomimicry in Built-Environment Design

Biomimetics ◽  
2019 ◽  
Vol 4 (4) ◽  
pp. 73 ◽  
Author(s):  
Hayes ◽  
Desha ◽  
Gibbs
Keyword(s):  
Built Environment ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Meta Analysis ◽  
System Level ◽  
Research Approach ◽  
Environment Design ◽  
Complex Adaptive ◽  
Barriers To Implementation ◽  
Analysis System

Complex systems challenges like those facing 21st-century humanity, require system-level solutions that avoid siloed or unnecessarily narrow responses. System-level biomimicry aims to identify and adopt design approaches that have been developed and refined within ecosystems over 3.8 billion years of evolution. While not new, system-level biomimetic solutions have been less widely applied in urban design than the ‘form’ and ‘process’ level counterparts. This paper explores insights from a selection of system-level case studies in the built environment, using meta-analysis to investigate common challenges and priorities from these projects to support knowledge-sharing and continued development in the field. Using a grounded research approach, common themes are distilled, and findings presented regarding success and barriers to implementation and scaling. Considering the findings, and drawing on complex adaptive systems theory, the paper posits opportunities to facilitate broader implementation and mainstreaming of system-level biomimetic design approaches in the built environment.

scholarly journals Destination governance in times of change: a complex adaptive systems perspective to improve tourism destination development

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Stefan Hartman
Keyword(s):  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Analytical Framework ◽  
System Level ◽  
Tourism Destination ◽  
Content Type ◽  
Sustainable Tourism Development ◽  
Systems Perspective ◽  
Complex Adaptive ◽  
The Individual

PurposeThis paper brings together the literature on theories of complexity adaptive systems (CAS), develops an analytical framework, applies this framework to the development of tourism destinations and critically reflects on the use of this perspective.Design/methodology/approachThis paper elaborates on a CAS perspective on destination development, to further develop complexity thinking in tourism studies. This approach enables to identify policy avenues geared towards improving destination governance and contributing to sustainable tourism development.FindingsTheories of CAS offer an analytical lens to better understand destination development, drawing explicit attention to (1) the levels of the individual, (emergent) structures, the structure-agency interface and the system level, (2) the steps related to the process of adaptation that is critical for systems to survive and thrive in times of change and (3) the undervalued importance of considering the factor of time.Originality/valueApplying CAS theories help to address a range of (policy) avenues to improve destination governance, contributing to a shift in focus from reactively fixing problems to proactively addressing the structural issue of adaptive capacity building. It shows that managing tourism destination as complex systems involves a set of conditions that are critical as well as difficult to meet in tourism practice.

EMERGENT FEATURES IN A GENERAL FOOD WEB SIMULATION: LOTKA–VOLTERRA, GAUSE'S LAW, AND THE PARADOX OF ENRICHMENT

2013 ◽  
Vol 16 (08) ◽  
pp. 1350014 ◽  
Author(s):  
TED CARMICHAEL ◽  
MIRSAD HADZIKADIC
Keyword(s):  
Simulation Model ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Marine Ecosystem ◽  
System Level ◽  
Computer Simulation Model ◽  
Agent Based ◽  
Predator Prey ◽  
Paradox Of Enrichment ◽  
Complex Adaptive

Computer simulations of complex food-webs are important tools for deepening our understanding of these systems. Yet most computer models assume, rather than generate, key system-level patterns, or use mathematical modeling approaches that make it difficult to fully account for nonlinear dynamics. In this paper, we present a computer simulation model that addresses these concerns by focusing on assumptions of agent attributes rather than agent outcomes. Our model utilizes the techniques of complex adaptive systems and agent-based modeling so that system level patterns of a marine ecosystem emerge from the interactions of thousands of individual computer agents. This methodology is validated by using this general simulation model to replicate fundamental properties of a marine ecosystem, including: (i) the predator–prey oscillations found in Lotka–Volterra; (ii) the stepped pattern of biomass accrual from resource enrichment; (iii) the Paradox of Enrichment; and (iv) Gause's Law.

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