'Atawhai': a primary care provider-led response to family violence in Aotearoa New Zealand

BACKGROUND

As a key determinant of ill-health, family violence is inadequately responded to within Aotearoa New Zealand health policy and practice. Without adequate system support, health professionals can often be unsure of what to do, or how to help. Developed in response to this system gap, 'Atawhai' aims to make it easier for primary care professionals to respond to family violence.

METHODS

Underpinned by indigenous Māori customs, Atawhai combines complexity theory and participatory research methodologies to be responsive to the complexity involved in family violence. We worked with 14 primary care professionals across ten whakawhitiwhiti kōrero wānanga (meetings for deliberate dialogue) to identify and develop primary care system pathways and tools for responding to family violence. This paper focuses on the development of Atawhai through wānanga and observation methods. Methods used to capture change will be reported separately.

FINDINGS

Atawhai is a relational response to family violence, focused on developing a network of trusted relationships between health and social care professionals to support safe responses to those accessing care. This study identified four key health system pathways to responsiveness and developed associated tools to support health care responsiveness to family violence. We found the quality of relationships, both among professionals and with those accessing care, coupled with critical reflection on the systems and structures that shape policy and practice are essential in generating change within primary care settings.

CONCLUSIONS

Atawhai is a unique health care response to family violence evidenced on empirical knowledge of primary care professionals. Our theoretical lens calls attention to parts of the system often obscured by current health care responses to family violence. Atawhai presents an opportunity to develop a grassroots-informed, long-term response to family violence that evolves in response to needs.

Unravelling the asymmetric effects of procurement practices on firm performance: A complexity theory approach to complementing fsQCA with NCA

Current economic upheavals and supply chain uncertainty have threatened the profitability and sustainability of business organisations. Procurement has proved to be one of the strategies for enhancing firm performance without necessarily increasing revenue with its attendant increase in costs. However, rather than investigating the complex asymmetric relationship between procurement practices and firm performance (which this study advocates), past research engaged in a symmetric evaluation of the relationship between the phenomena. Accordingly, this study, using complexity theory, employs fsQCA and NCA on a sample of 150 respondents from private universities in Ghana to (a) identify different combinations of procurement practices, namely procurement planning, supplier partnership, contract management, and compliance, that lead to firm performance and (b) explore the necessity of these procurement practices (in kind and degree) for firm performance. Whereas the findings from fsQCA reveal three distinct combinations of procurement practices for high firm performance and further suggest that none of the procurement practices was necessary for firm performance, the NCA results suggest that two out of the four procurement practices investigated are necessary for firm performance and hence must be present in the causal recipes produced by fsQCA to guarantee that they lead to firm performance. The study offers pathways to firm performance through procurement practices and demonstrates how to complement fsQCA with NCA to ensure that causal recipes produced by fsQCA can produce the outcome.

Proposal of guidelines to assist managers to face pressing challenges confronting Latin American universities: a complexity theory perspective

The Covid-19 pandemic exacerbated pre-existing problems in Latin America and posed unprecedented challenges for Latin American universities (LAU). These challenges can be characterised as complex problems that cannot be understood through reductionist approaches. This paper aims (i) to provide a complex system perspective of the challenges confronting LAUs and (ii) to propose guidelines for managers of LAUs to address them in practice. A multidisciplinary group was formed and conducted an iterative process of research, brainstorming and debate of potential solutions to the following problems considered particularly important by their universities: mental health issues in the university environment, student learning gaps, brain drain, and anti-science movements. Complexity theory and E/HF concepts are integrated to demonstrate that understanding what LAUs are experiencing in a fragmented manner is impossible, and that the interactions between the challenges should be at the centre of the managers' actions plans. Practitioner summary: Managers of LAUs can benefit from the guidelines proposed to understand the pressing challenges confronting universities and develop systemic approaches to address them.

The lecturer-tutor in undergraduate medical education; navigating complexity as "a recruiter, a timetabler, an administrator, a counsellor"

BACKGROUND

Tutors play an important role in the delivery of effective undergraduate medical education (UGME). These roles commonly involve competing clinical, educational and research commitments. We sought to obtain a rich description of these posts from doctors working in them.

METHODS

We used a pragmatist, sequential explanatory mixed-methods design with a sampling frame of clinical lecturer/tutors in 5 Irish medical schools. Purposive sampling was used for recruitment. Quantitative data collected from a validated online questionnaire were used to inform a semi-structured interview question guide. Thematic analysis was conducted independently by each of the study researchers, using a coding frame derived in part from the findings of the online questionnaire. Quantitative and qualitative mixing occurred during data collection, analysis and reporting.

RESULTS

34 tutors completed the online survey with 7 volunteers for interview. Most respondents took the job to gain experience in either educational practice (79.4%) or in research (61.8%). Major themes to emerge were the diverse interactions with students, balancing multiple professional commitments, a high degree of role-autonomy, mis-perception of role by non-tutor colleagues, challenges around work-life balance and unpredictable work demands. Using a complexity theory lens, the tutor role was defined by its relational interactions with numerous stakeholders, all in the context of an environment that changed regularly and in an unpredictable manner.

CONCLUSIONS

The undergraduate tutor works in a demanding role balancing educational and non-educational commitments with suboptimal senior guidance and feedback. The role is notable for its position within a complex adaptive system. An understanding of the system's interactions recognises the non-linearity of the role. Using a complex systems lens, we propose improvements to undergraduate education centred around the tutor.

Climate change and government policy: Fresh insights from complexity theory

Governments worldwide are increasingly concerned about ensuring a balance between economic and environmental well being. Global economies, particularly developing ones, emphasize the importance of achieving escofriendly growth to maintain the levels of the ecological footprint while achieving higher economic growth. The ecological footprint is a comprehensive indicator of environmental degradation. It is used to assess the state of the environment because it reflects the impact of all human activities on nature. This study contributes to the literature by offering a novel analytical approach for solving complex interactions of ecological footprint antecedents, advancing the theoretical reasoning behind how government policy combines to explain the ecological footprint from some G7 countries (France, Italy, Japan, United Kingdom, and Germany) from 1996 to 2020. To establish a composite score of environmental footprint, we used complexity theory as well as fuzzy set qualitative comparative analysis (fsQCA) and necessary condition analysis (NCA). Our analysis revealed that low expenditures on environmental protection and waste management, low taxes on transport, and high energy use are sufficient conditions to be included in the causal configurations for a high ecological footprint. Additionally, the sufficient solution, which has the highest coverage score that produces a low ecological footprint relies on high expenditure on environmental protection and high taxes on transportation. In this framework, Japan, Italy, and France have more effective government policies in terms of reducing the ecological footprint.

Challenges, opportunities, and prospects of adopting and using smart digital technologies in learning environments: An iterative review

The adoption of smart digital technologies in the education system has grown exponentially over the years, creating new possibilities to improve teaching and enhance learning. Against this backdrop, the 'brick-and-mortar' education approach survives on life support, with digital technologies promoting ubiquitous teaching and learning. Through complexity theory, this study uses an iterative review research approach comprising of nine steps to frame the study of smart digital education. The complexity theory lens provides an appropriate framework to reason about the complexities that surface due to interactions of the elements of smart digital technologies in the education system. The complementary strength of the adopted methodological approach led to multiple discourses on technology-enabled and technology-enhanced learning environments. In particular, four broad themes emerged, which demonstrated the prevalence of various technologies and how they interact as a means of making sense of the emerging digitally-enabled education environment. Through these themes, this paper highlights digitalisation affordances (which include multimodality, a/synchronicity, and new forms of engagement), discusses the key challenges and complexities of digitally enabled education, and advances the discourse on how digitalisation can support and promote inclusivity amidst historic challenges. Finally, it discusses how the advancement of technologies provides a new paradigm of learning, revolutionises knowledge construction, and extends and enriches the 'brick-and-mortar' learning environment to enhance the educational experience. As a future research agenda, this paper recommends comprehensive end-to-end programmes and innovative ways to conceptualise and execute digitally-enabled education that provides equity-oriented opportunities for cognitive development.

Developing an agent-based model to minimize spreading of malicious information in dynamic social networks

This research introduces a systematic and multidisciplinary agent-based model to interpret and simplify the dynamic actions of the users and communities in an evolutionary online (offline) social network. The organizational cybernetics approach is used to control/monitor the malicious information spread between communities. The stochastic one-median problem minimizes the agent response time and eliminates the information spread across the online (offline) environment. The performance of these methods was measured against a Twitter network related to an armed protest demonstration against the COVID-19 lockdown in Michigan state in May 2020. The proposed model demonstrated the dynamicity of the network, enhanced the agent level performance, minimized the malicious information spread, and measured the response to the second stochastic information spread in the network.

Skills-approximate occupations: using networks to guide jobs retraining

An issue often confronting economic development agencies is how to minimize unemployment due to disruptions like technological change, trade wars, recessions, or other economic shocks. Decision makers are left to craft policies that can absorb surplus labor with as little pain to workers as possible. The questions they face include how to re-employ displaced workers and how to fill labor shortages. To address such questions, we quantify the proximity of any two occupations based on the skills inherent in each. Taking labor skills as nodes, we model US labor as a weighted network of interdependent skills, deriving link values from geographical patterns of skill co-occurrence. We use this network to locate occupations, measure their proximity to each other, and identify which missing skills may inhibit workers from easily transitioning from one occupation to another. Thus, given that an occupation is a bundle of skills, we use our skills network to help policy makers identify which other occupations are most proximate a worker's current occupation. Finally, we apply our method to assess various worker retraining pathways for metropolitan Washington, DC, USA, whose economy was simultaneously disrupted by both the COVID-19 pandemic and the arrival of a second headquarters for Amazon.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s41109-022-00487-7.

Evaluating the integration of strategic priorities within a complex research-for-development funding program

This paper examines the application of Complexity Theory constructs to a research-for-development program evaluation and presents an overview of the implications and promising approaches for evaluating complex programs. We discuss lessons learned from an evaluation completed for the International Development Research Centre's Food, Environment and Health (FEH) program, which investigated the integration and outcomes of five strategic program priorities: partnerships, southern leadership, gender and equity, scale, and environmental sustainability. We present interpretations from a secondary, thematic content analysis that categorized evaluation findings across four complexity constructs: emergence, unpredictability, contradiction and self-organization. Viewing the evaluation through these constructs surfaced some important features of the FEH program to date, specifically its evolving approach, adaptiveness to emergent issues, non-linear outcomes, and self-organizing agents, which had several implications for the evaluative process. We conclude that the most appropriate evaluation designs for complex funding programs are participatory (to explore all stakeholders' influence), adaptive (to capture the unexpected) and assess external contexts. The application of complexity constructs may be useful for evaluators to gain a deeper understanding of how program contexts change in the face of complexity and why some evaluation methods work more effectively than others.

Innovation in the solid waste management industry: Integrating neoclassical and complexity theory perspectives

Often considered a traditional labour intensive activity, in recent years, the solid waste management (SWM) industry has been largely interested in innovation. Nonetheless, the analysis of innovations in the SW industry is frequently confined to process innovation in the disposal segment, neglecting other kinds of innovation - such as product innovation and organizational innovation - in other segments. While several economic theoretical frameworks have been developed for interpreting eco-innovation in general, a specific analysis of innovation in each segment of SWM is still missing, despite the specificities of this sector. To fill this gap, this paper shows how complexity theory can be profitably used to integrate the more traditional neoclassical approach, offering a comprehensive theoretical framework to analyse innovation in the SWM industry from both a market and firm perspective (the neoclassical approach) and from a social perspective (the complexity theory framework). Four main typologies of the SW market system, exhibiting different kinds of innovation, are outlined: (i) a "traditional" landfill-oriented system; (ii) a modern "waste-to-energy" incinerator-oriented system; (iii) a "light recycling" system with integrated solutions and a selection performance that is lower than 50%; and (iv) a "hard recycling" system.

Does application of complexity theory simplify concepts of psychiatry: Analogies and insights

Scientific curiosity has not been able to explain the cause of psychiatric illness based on primarily biological or social paradigm. Available literatures were explored to understand causality of psychiatric illness from perspective of physics. Theory of complexity and other relevant theories were extrapolated to address these questions. Mental illness appeared to be a complex interplay of reductionism and emergentism, genetic and epigenetics, stress and the vulnerability or the core and the periphery. Mental illness displayed complex interaction between biological trait and environmental state.

Complicated versus complexity: when an old woman and her daughter meet the health care system

Background

Detecting infection in frail elderly is a challenge due to lack of specific signs and symptoms. We highlight the complex situation when an elderly woman with urinary tract infection (UTI) and her daughter meet the highly qualified health care system. The aim was to describe and analyze the process when an elderly individual with an acute infection encounters the healthcare system.

Methods

A descriptive, retrospective Single Case Study design with a qualitative approach was used. Data from interviews with the old women and her daughter, medical record data and different regulatory documents were gathered and analysed with a qualitative content analysis. In a second step, the results were interpreted with concepts from the complexity theory. Complexity theory has been used as a conceptual framework for analysis or a framework for interpretation. In this study we are using the theory for interpretation by comparing the results with the complexity theory, which is explored in the discussion.

Results

The latent content analysis of the daughter’s story is interpreted as though she perceives the situation as causing a life crisis and a threat to her mother’s entire existence. The old women herself does not take part in what is happening, though after returning to home she is trying to understand her behaviour and what has happened. The health care tries different diagnoses and treatment according to standardized care plans without success. When urinary tract infection is finally diagnosed and treated successfully, the old women recovers quickly.

Conclusion

The healthcare system should embrace the complexity in the encounter with an elderly individual. However, we found that the immediate reaction from the healthcare system is to handle the patients’ problem as complicated by complexity reduction. Shortcomings are that elderly patients with multiple disorders are difficult to evaluate and triage “correctly” for later placement in the appropriate continuum of care, although the findings of this case study also imply that with time the system instead took on an approach of absorption of complexity.

A framework for distributed health professions training: using participatory action research to build consensus

BACKGROUND

There is a global trend towards providing training for health professions students outside of tertiary academic complexes. In many countries, this shift places pressure on available sites and the resources at their disposal, specifically within the public health sector. Introducing an educational remit into a complex health system is challenging, requiring commitment from a range of stakeholders, including national authorities. To facilitate the effective implementation of distributed training, we developed a guiding framework through an extensive, national consultative process with a view to informing both practice and policy.

METHODS

We adopted a participatory action research approach over a four year period across three phases, which included seven local, provincial and national consultative workshops, reflective work sessions by the research team, and expert reviews. Approximately 240 people participated in these activities. Engagement with the national department of health and health professions council further informed the development of the Framework.

RESULTS

Each successive 'feedback loop' contributed to the development of the Framework which comprised a set of guiding principles, as well as the components essential to the effective implementation of distributed training. Analysis further pointed to the centrality of relationships, while emphasising the importance of involving all sectors relevant to the training of health professionals. A tool to facilitate the implementation of the Framework was also developed, incorporating a set of 'Simple Rules for Effective distributed health professions training'. A national consensus statement was adopted.

CONCLUSIONS

In this project, we drew on the thinking and practices of key stakeholders to enable a synthesis between their embodied and inscribed knowledge, and the prevailing literature, this with a view to further enaction as the knowledge generators become knowledge users. The Framework and its subsequent implementation has not only assisted us to apply the evidence to our educational practice, but also to begin to influence policy at a national level.

Enhancing the adaptive capacity for urban sustainability: A bottom-up approach to understanding the urban social system in China

Solutions that effectively promote sustainable development in urban environments require an understanding of the complexity of human-environment interactions. This paper adopted a systems-based framework to understanding how social, organisational, and environmental factors interact within an urban system in China. Drawing upon a case study from the industrial city of Jinchang, it applied a qualitative bottom-up approach to understand these key factors operating from three perspectives: the commitment of stakeholders, institutional development and personal development of social systems. It revealed that decision-making mechanisms play a key role in improving the sustainability of governance, and that public-private cooperation and public participation are critical for innovative knowledge-based strategies. The key for improving institutional development is to reform the evaluation system of governance thus enhancing the capacities of decision and policy makers, and consequently improve the process of decision-making. Cultural and personal development are important soft power components that influence individual pro-environmental behaviour and performance toward sustainability. The results demonstrated how, in a Chinese context, the urban social system can be understood and urban sustainability can be promoted through environmental adaptation supported by joint efforts from governments, businesses, society and individuals. In this, China does not differ from other nations in spite of significant differences in cultural and political systems. This study contributed to a better understanding of complex urban systems, providing a bottom-up approach and knowledge for enhancing the adaptive capacity toward urban sustainability.

Public health emergency preparedness: a framework to promote resilience

Background

Emergencies and disasters impact population health. Despite the importance of upstream readiness, a persistent challenge for public health practitioners is defining what it means to be prepared. There is a knowledge gap in that existing frameworks lack consideration for complexity relevant to health systems and the emergency context. The objective of this study is to describe the essential elements of a resilient public health system and how the elements interact as a complex adaptive system.

Methods

This study used a qualitative design employing the Structured Interview Matrix facilitation technique in six focus groups across Canada. Focus group participants were practitioners from public health and related sectors. Data collection generated qualitative data on the essential elements, and interactions between elements, for a resilient public health system. Data analysis employed qualitative content analysis and the lens of complexity theory to account for the complex nature of public health emergency preparedness (PHEP). The unit of study was the local/regional public health agency. Ethics and values were considered in the development of the framework.

Results

A total of 130 participants attended the six focus groups. Urban, urban-rural and rural regions from across Canada participated and focus group size ranged from 15 to 33 across the six sites. Eleven elements emerged from the data; these included one cross-cutting element (Governance and leadership) and 10 distinct but interlinked elements. The essential elements define a conceptual framework for PHEP. The framework was refined to ensure practice and policy relevance for local/regional public health agencies; the framework has ethics and values at its core.

Conclusions

This framework describes the complexity of the system yet moves beyond description to use tenets of complexity to support building resilience. This applied public health framework for local/regional public health agencies is empirically-derived and theoretically-informed and represents a complex adaptive systems approach to upstream readiness for PHEP.

Electronic supplementary material

The online version of this article (10.1186/s12889-018-6250-7) contains supplementary material, which is available to authorized users.

Exploring the complex pathway of the primary health care response to intimate partner violence in New Zealand

Background

Integrating sustainable responses to intimate partner violence in health care is a persistent and complex problem internationally. New Zealand holds a leading role, having established national health system infrastructure for responding to intimate partner violence within hospital and selected community settings. However, resources for, and engagement with, the primary health care sector has been limited. The present study focuses on what affects a sustainable response to intimate partner violence within New Zealand primary health care settings.

Methods

Utilising complexity theory, we reconceptualised a sustainable primary health care response to intimate partner violence as a complex adaptive system. To explore interactions between agents, we analysed the function(s) of key policy, strategy, guideline and evaluation documents informing intimate partner violence responsiveness in health care. We chronologically threaded these documents together by their function(s) to show how discourse influencing intimate partner violence responsiveness emerges from agent interactions.

Results

This paper presents a complexity informed implementation narrative of the New Zealand health system response to intimate partner violence across the last two decades, focused on the participation of the primary health care sector. We demonstrate how competing discourses have contributed to system gaps and unintended consequences over time. Our findings consider implications for a sustainable response to intimate partner violence in primary health care and call attention to system interactions that challenge a whole health system approach in New Zealand.

Conclusions

Use of complexity theory facilitates an innovative perspective of a persistent and complex problem. Given the complexity of the problem and New Zealand’s leadership, sharing the lessons learnt is critical for the international community involved in developing health care system approaches to intimate partner violence.

Simple rules for evidence translation in complex systems: A qualitative study

BACKGROUND

Ensuring patients benefit from the latest medical and technical advances remains a major challenge, with rational-linear and reductionist approaches to translating evidence into practice proving inefficient and ineffective. Complexity thinking, which emphasises interconnectedness and unpredictability, offers insights to inform evidence translation theories and strategies. Drawing on detailed insights into complex micro-systems, this research aimed to advance empirical and theoretical understanding of the reality of making and sustaining improvements in complex healthcare systems.

METHODS

Using analytical auto-ethnography, including documentary analysis and literature review, we assimilated learning from 5 years of observation of 22 evidence translation projects (UK). We used a grounded theory approach to develop substantive theory and a conceptual framework. Results were interpreted using complexity theory and 'simple rules' were identified reflecting the practical strategies that enhanced project progress.

RESULTS

The framework for Successful Healthcare Improvement From Translating Evidence in complex systems (SHIFT-Evidence) positions the challenge of evidence translation within the dynamic context of the health system. SHIFT-Evidence is summarised by three strategic principles, namely (1) 'act scientifically and pragmatically' - knowledge of existing evidence needs to be combined with knowledge of the unique initial conditions of a system, and interventions need to adapt as the complex system responds and learning emerges about unpredictable effects; (2) 'embrace complexity' - evidence-based interventions only work if related practices and processes of care within the complex system are functional, and evidence-translation efforts need to identify and address any problems with usual care, recognising that this typically includes a range of interdependent parts of the system; and (3) 'engage and empower' - evidence translation and system navigation requires commitment and insights from staff and patients with experience of the local system, and changes need to align with their motivations and concerns. Twelve associated 'simple rules' are presented to provide actionable guidance to support evidence translation and improvement in complex systems.

CONCLUSION

By recognising how agency, interconnectedness and unpredictability influences evidence translation in complex systems, SHIFT-Evidence provides a tool to guide practice and research. The 'simple rules' have potential to provide a common platform for academics, practitioners, patients and policymakers to collaborate when intervening to achieve improvements in healthcare.

Being pragmatic about healthcare complexity: our experiences applying complexity theory and pragmatism to health services research

BACKGROUND

The healthcare system has proved a challenging environment for innovation, especially in the area of health services management and research. This is often attributed to the complexity of the healthcare sector, characterized by intersecting biological, social and political systems spread across geographically disparate areas. To help make sense of this complexity, researchers are turning towards new methods and frameworks, including simulation modeling and complexity theory.

DISCUSSION

Herein, we describe our experiences implementing and evaluating a health services innovation in the form of simulation modeling. We explore the strengths and limitations of complexity theory in evaluating health service interventions, using our experiences as examples. We then argue for the potential of pragmatism as an epistemic foundation for the methodological pluralism currently found in complexity research. We discuss the similarities between complexity theory and pragmatism, and close by revisiting our experiences putting pragmatic complexity theory into practice.

CONCLUSION

We found the commonalities between pragmatism and complexity theory to be striking. These included a sensitivity to research context, a focus on applied research, and the valuing of different forms of knowledge. We found that, in practice, a pragmatic complexity theory approach provided more flexibility to respond to the rapidly changing context of health services implementation and evaluation. However, this approach requires a redefinition of implementation success, away from pre-determined outcomes and process fidelity, to one that embraces the continual learning, evolution, and emergence that characterized our project.

Pair- ${v}$ -SVR: A Novel and Efficient Pairing nu-Support Vector Regression Algorithm

This paper proposes a novel and efficient pairing nu-support vector regression (pair--SVR) algorithm that combines successfully the superior advantages of twin support vector regression (TSVR) and classical -SVR algorithms. In spirit of TSVR, the proposed pair--SVR solves two quadratic programming problems (QPPs) of smaller size rather than a single larger QPP, and thus has faster learning speed than classical -SVR. The significant advantage of our pair--SVR over TSVR is the improvement in the prediction speed and generalization ability by introducing the concepts of the insensitive zone and the regularization term that embodies the essence of statistical learning theory. Moreover, pair--SVR has additional advantage of using parameter for controlling the bounds on fractions of SVs and errors. Furthermore, the upper bound and lower bound functions of the regression model estimated by pair--SVR capture well the characteristics of data distributions, thus facilitating automatic estimation of the conditional mean and predictive variance simultaneously. This may be useful in many cases, especially when the noise is heteroscedastic and depends strongly on the input values. The experimental results validate the superiority of our pair--SVR in both training/prediction speed and generalization ability.This paper proposes a novel and efficient pairing nu-support vector regression (pair--SVR) algorithm that combines successfully the superior advantages of twin support vector regression (TSVR) and classical -SVR algorithms. In spirit of TSVR, the proposed pair--SVR solves two quadratic programming problems (QPPs) of smaller size rather than a single larger QPP, and thus has faster learning speed than classical -SVR. The significant advantage of our pair--SVR over TSVR is the improvement in the prediction speed and generalization ability by introducing the concepts of the insensitive zone and the regularization term that embodies the essence of statistical learning theory. Moreover, pair--SVR has additional advantage of using parameter for controlling the bounds on fractions of SVs and errors. Furthermore, the upper bound and lower bound functions of the regression model estimated by pair--SVR capture well the characteristics of data distributions, thus facilitating automatic estimation of the conditional mean and predictive variance simultaneously. This may be useful in many cases, especially when the noise is heteroscedastic and depends strongly on the input values. The experimental results validate the superiority of our pair--SVR in both training/prediction speed and generalization ability.

Bridging complexity theory and resilience to develop surge capacity in health systems

Purpose Health systems are periodically confronted by crises - think of Severe Acute Respiratory Syndrome, H1N1, and Ebola - during which they are called upon to manage exceptional situations without interrupting essential services to the population. The ability to accomplish this dual mandate is at the heart of resilience strategies, which in healthcare systems involve developing surge capacity to manage a sudden influx of patients. The paper aims to discuss these issues. Design/methodology/approach This paper relates insights from resilience research to the four "S" of surge capacity (staff, stuff, structures and systems) and proposes a framework based on complexity theory to better understand and assess resilience factors that enable the development of surge capacity in complex health systems. Findings Detailed and dynamic complexities manifest in different challenges during a crisis. Resilience factors are classified according to these types of complexity and along their temporal dimensions: proactive factors that improve preparedness to confront both usual and exceptional requirements, and passive factors that enable response to unexpected demands as they arise during a crisis. The framework is completed by further categorizing resilience factors according to their stabilizing or destabilizing impact, drawing on feedback processes described in complexity theory. Favorable order resilience factors create consistency and act as stabilizing forces in systems, while favorable disorder factors such as diversity and complementarity act as destabilizing forces. Originality/value The framework suggests a balanced and innovative process to integrate these factors in a pragmatic approach built around the fours "S" of surge capacity to increase health system resilience.

The performance of primary health care organizations depends on interdependences with the local environment

Purpose Improving the performance of health care organizations is now perceived as essential in order to better address the needs of the populations and respect their ability to pay for the services. There is no consensus on what is performance. It is increasingly considered as the optimal execution of four functions that every organization must achieve in order to survive and develop: reach goals; adapt to its environment; produce goods or services and maintain values; and a satisfying organizational climate. There is also no consensus on strategies to improve this performance. The paper aims to discuss these issues. Design/methodology/approach This paper intends to analyze the performance of primary health care organizations from the perspective of Kauffman's model. It mainly aims to understand the often contradictory, paradoxical and unexpected results that emerge from studies on this topic. Findings To do so, the first section briefly presents Kauffman's model and lays forward its principal components. The second section presents three studies on the performance of primary organizations and brings out the contradictory, paradoxical and unexpected results they obtained. The third section explains these results in the light of Kauffman's model. Originality/value Kauffman's model helps give meaning to the results of researches on performance of primary health care organizations that were qualified as paradoxical or unexpected. The performance of primary health care organizations then cannot be understood by only taking into account the characteristics of these organizations. The complexity of the environments in which they operate must simultaneously be taken into account. This paper brings original development of an integrated view of the performance of organizations, their own characteristics and those of the local environment in which they operated.

The complexity of divisibility

We address two sets of long-standing open questions in linear algebra and probability theory, from a computational complexity perspective: stochastic matrix divisibility, and divisibility and decomposability of probability distributions. We prove that finite divisibility of stochastic matrices is an NP-complete problem, and extend this result to nonnegative matrices, and completely-positive trace-preserving maps, i.e. the quantum analogue of stochastic matrices. We further prove a complexity hierarchy for the divisibility and decomposability of probability distributions, showing that finite distribution divisibility is in P, but decomposability is NP-hard. For the former, we give an explicit polynomial-time algorithm. All results on distributions extend to weak-membership formulations, proving that the complexity of these problems is robust to perturbations.

Examining the influence of country-level and health system factors on nursing and physician personnel production

BACKGROUND

A key component to achieving good patient outcomes is having the right type and number of healthcare professionals with the right resources. Lack of investment in infrastructure required for producing and retaining adequate numbers of health professionals is one reason, and contextual factors related to socioeconomic development may further explain the trend. Therefore, this study sought to explore the relationships between country-level contextual factors and healthcare human resource production (defined as worker-to-population ratio) across 184 countries.

METHODS

This exploratory observational study is grounded in complexity theory as a guiding framework. Variables were selected through a process that attempted to choose macro-level indicators identified by the interdisciplinary literature as known or likely to affect the number of healthcare workers in a country. The combination of these variables attempts to account for the gender- and class-sensitive identities of physicians and nurses. The analysis consisted of 1 year of publicly available data, using the most recently available year for each country where multiple regressions assessed how context may influence health worker production. Missing data were imputed using the ICE technique in STATA and the analyses rerun in R as an additional validity and rigor check.

RESULTS

The models explained 63 % of the nurse/midwife-to-population ratio (pseudo R (2) = 0.627, p = 0.0000) and 73 % of the physician-to-population ratio (pseudo R (2) = 0.729, p = 0.0000). Average years of school in a country's population, emigration rates, beds-per-1000 population, and low-income country statuses were consistently statistically significant predictors of production, with percentage of public and private sector financing of healthcare showing mixed effects.

CONCLUSIONS

Our study demonstrates that the strength of political, social, and economic institutions does impact human resources for health production and lays a foundation for studying how macro-level contextual factors influence physician and nurse workforce supply. In particular, the results suggest that public and private investments in the education sector would provide the greatest rate of return to countries. The study offers a foundation from which longitudinal analyses can be conducted and identifies additional data that may help enhance the robustness of the models.

Embedding research in health systems: lessons from complexity theory

Background

Internationally, there has been increasing focus on creating health research systems. This article aims to investigate the challenges of implementing apparently simple strategies to support the development of a health research system. We focus on a case study of an English National Health Service Hospital Trust that sought to implement the national recommendation that health organisations should introduce a statement about research on all patient admission letters.

Methods

We apply core concepts from complexity theory to the case study and undertake a documentary analysis of the email dialogue between staff involved in implementing this initiative.

Results

The process of implementing a research statement in patient admission letters in one clinical service took 1 year and 21 days. The length of time needed was influenced firstly by adaptive self-organisation, underpinned by competing interests. Secondly, it was influenced by the relationship between systems, rather than simply being a product of issues within those systems. The relationship between the health system and the research system was weaker than might have been expected. Responsibilities were unclear, leading to confusion and delayed action.

Conclusions

Conventional ways of thinking about organisations suggest that change happens when leaders and managers change the strategic vision, structure or procedures in an organisation and then persuade others to rationally implement the strategy. However, health research systems are complex adaptive systems characterised by high levels of unpredictability due to self-organisation and systemic interactions, which give rise to ‘emergent’ properties. We argue for the need to study how micro-processes of organisational dynamics may give rise to macro patterns of behaviour and strategic organisational direction and for the use of systems approaches to investigate the emergent properties of health research systems.

Facing up to Complexity: Implications for Our Social Experiments

Biological systems are highly complex, and for this reason there is a considerable degree of uncertainty as to the consequences of making significant interventions into their workings. Since a number of new technologies are already impinging on living systems, including our bodies, many of us have become participants in large-scale "social experiments". I will discuss biological complexity and its relevance to the technologies that brought us BSE/vCJD and the controversy over GM foods. Then I will consider some of the complexities of our social dynamics, and argue for making a shift from using the precautionary principle to employing the approach of evaluating the introduction of new technologies by conceiving of them as social experiments.

Big data to smart data in Alzheimer's disease: The brain health modeling initiative to foster actionable knowledge

Massive investment and technological advances in the collection of extensive and longitudinal information on thousands of Alzheimer patients results in large amounts of data. These "big-data" databases can potentially advance CNS research and drug development. However, although necessary, they are not sufficient, and we posit that they must be matched with analytical methods that go beyond retrospective data-driven associations with various clinical phenotypes. Although these empirically derived associations can generate novel and useful hypotheses, they need to be organically integrated in a quantitative understanding of the pathology that can be actionable for drug discovery and development. We argue that mechanism-based modeling and simulation approaches, where existing domain knowledge is formally integrated using complexity science and quantitative systems pharmacology can be combined with data-driven analytics to generate predictive actionable knowledge for drug discovery programs, target validation, and optimization of clinical development.

Dealing with the complex dynamics of teaching hospitals

Innovation and change in postgraduate medical education programs affects teaching hospital organizations, since medical education and clinical service are interrelated.Recent trends towards flexible, time-independent and individualized educational programs put pressure on this relationship. This pressure may lead to organizational uncertainty, unbalance and friction making it an important issue to analyze.The last decade was marked by a transition towards outcome-based postgraduate medical education. During this transition competency-based programs made their appearance. Although competency-based medical education has the potential to make medical education more efficient, the effects are still under debate. And while this debate continues, the field of medical education is already introducing next level innovations: flexible and individualized training programs. Major organizational change, like the transition to flexible education programs, can easily lead to friction and conflict in teaching hospital organizations.This article analyses the organizational impact of postgraduate medical education innovations, with a particular focus on flexible training and competency based medical education. The characteristics of teaching hospital organizations are compared with elements of innovation and complexity theory.With this comparison the article argues that teaching hospital organizations have complex characteristics and behave in a non-linear way. This perspective forms the basis for further discussion and analysis of this unexplored aspect of flexible and competency based education.

Scoping review of complexity theory in health services research

Background

There are calls for better application of theory in health services research. Research exploring knowledge translation and interprofessional collaboration are two examples, and in both areas, complexity theory has been identified as potentially useful. However, how best to conceptualize and operationalize complexity theory in health services research is uncertain. The purpose of this scoping review was to explore how complexity theory has been incorporated in health services research focused on allied health, medicine, and nursing in order to offer guidance for future application. Given the extensiveness of how complexity theory could be conceptualized and ultimately operationalized within health services research, a scoping review of complexity theory in health services research is warranted.

Methods

A scoping review of published research in English was conducted using CINAHL, EMBASE, Medline, Cochrane, and Web of Science databases. We searched terms synonymous with complexity theory.

Results

We included 44 studies in this review: 27 were qualitative, 14 were quantitative, and 3 were mixed methods. Case study was the most common method. Long-term care was the most studied setting. The majority of research was exploratory and focused on relationships between health care workers. Authors most commonly used complexity theory as a conceptual framework for their study. Authors described complexity theory in their research in a variety of ways. The most common attributes of complexity theory used in health services research included relationships, self-organization, and diversity. A common theme across descriptions of complexity theory is that authors incorporate aspects of the theory related to how diverse relationships and communication between individuals in a system can influence change.

Conclusion

Complexity theory is incorporated in many ways across a variety of research designs to explore a multitude of phenomena.. Although complexity theory shows promise in health services research, particularly related to relationships and interactions, conceptual confusion and inconsistent application hinders the operationalization of this potentially important perspective. Generalizability from studies that incorporate complexity theory is, therefore, difficult. Heterogeneous conceptualization and operationalization of complexity theory in health services research suggests there is no universally agreed upon approach of how to use this theory in health services research. Future research should include clear definitions and descriptions of complexity and how it was used in studies. Clear reporting will aid in determining how best to use complexity theory in health services research.

Taxonomy for complexity theory in the context of maternity care

BACKGROUND

The linear focus of 'normal science' is unable to adequately take account of the complex interactions that direct health care systems. There is a turn towards complexity theory as a more appropriate framework for understanding system behaviour. However, a comprehensive taxonomy for complexity theory in the context of health care is lacking.

OBJECTIVE

This paper aims to build a taxonomy based on the key complexity theory components that have been used in publications on complexity theory and health care, and to explore their explanatory power for health care system behaviour, specifically for maternity care.

METHOD

A search strategy was devised in PubMed and 31 papers were identified as relevant for the taxonomy.

FINDINGS

The final taxonomy for complexity theory included and defined 11 components. The use of waterbirth and the impact of the Term Breech trial showed that each of the components of our taxonomy has utility in helping to understand how these techniques became widely adopted. It is not just the components themselves that characterise a complex system but also the dynamics between them.

Mutual information measures applied to EEG signals for sleepiness characterization

Excessive daytime sleepiness (EDS) is one of the main symptoms of several sleep related disorders with a great impact on the patient lives. While many studies have been carried out in order to assess daytime sleepiness, the automatic EDS detection still remains an open problem. In this work, a novel approach to this issue based on non-linear dynamical analysis of EEG signal was proposed. Multichannel EEG signals were recorded during five maintenance of wakefulness (MWT) and multiple sleep latency (MSLT) tests alternated throughout the day from patients suffering from sleep disordered breathing. A group of 20 patients with excessive daytime sleepiness (EDS) was compared with a group of 20 patients without daytime sleepiness (WDS), by analyzing 60-s EEG windows in waking state. Measures obtained from cross-mutual information function (CMIF) and auto-mutual-information function (AMIF) were calculated in the EEG. These functions permitted a quantification of the complexity properties of the EEG signal and the non-linear couplings between different zones of the scalp. Statistical differences between EDS and WDS groups were found in β band during MSLT events (p-value < 0.0001). WDS group presented more complexity than EDS in the occipital zone, while a stronger nonlinear coupling between occipital and frontal zones was detected in EDS patients than in WDS. The AMIF and CMIF measures yielded sensitivity and specificity above 80% and AUC of ROC above 0.85 in classifying EDS and WDS patients.

Applying complexity theory: a review to inform evaluation design

Complexity theory has increasingly been discussed and applied within evaluation literature over the past decade. This article reviews the discussion and use of complexity theory within academic journal literature. The aim is to identify the issues to be considered when applying complexity theory to evaluation. Reviewing 46 articles, two groups of themes are identified. The first group considers implications of applying complexity theory concepts for defining evaluation purpose, scope and units of analysis. The second group of themes consider methodology and method. Results provide a starting point for a configuration of an evaluation approach consistent with complexity theory, whilst also identifying a number of design considerations to be resolved within evaluation planning.

Improving safety culture through the health and safety organization: a case study

INTRODUCTION

International research indicates that internal health and safety organizations (HSO) and health and safety committees (HSC) do not have the intended impact on companies' safety performance. The aim of this case study at an industrial plant was to test whether the HSO can improve company safety culture by creating more and better safety-related interactions both within the HSO and between HSO members and the shop-floor.

METHODS

A quasi-experimental single case study design based on action research with both quantitative and qualitative measures was used.

INTERVENTION

Based on baseline mapping of safety culture and the efficiency of the HSO three developmental processes were started aimed at the HSC, the whole HSO, and the safety representatives, respectively.

RESULTS

Results at follow-up indicated a marked improvement in HSO performance, interaction patterns concerning safety, safety culture indicators, and a changed trend in injury rates. These improvements are interpreted as cultural change because an organizational double-loop learning process leading to modification of the basic assumptions could be identified.

PRACTICAL APPLICATIONS

The study provides evidence that the HSO can improve company safety culture by focusing on safety-related interactions.

Innovation as emergence in healthcare: unpacking change from within

The contemporary healthcare literature suffers from a disproportionate focus on 'given' externally created innovations, and belief in ordered, planned and well-funded implementation processes. As an alternative, the present paper highlights the potential of emergent change processes, using the continuous invention and re-invention of the Rheumatology Quality Registry in Sweden as an example. This 19 year long process, which is still ongoing, does not exhibit the sequential steps that are allegedly determinants of success in the innovation and implementation literature. Yet, it has produced system-wide improvements. We draw on more than 100 informal and formal meetings with practitioners involved in the process studied, observations, documentation analysis and quantitative registry-data. A total of 67 interviews with registry-users and external stakeholders were also performed. The dissipative structures model (complexity theory) was used to analyze the data. The studied process illustrates an ongoing, practice-driven improvement process, which was sparked by abstract and indirect energies that interacted with more concrete innovations such as new drugs. For example, participants tapped new information technologies, changing perspectives and governmental priorities to challenge current ways of working and introduce new ideas. Ideas were realized and spread through various self-organized processes that involved the re-arrangement of existing resources rather than acquisition of new resources. Taken together, these processes brought Swedish rheumatology to new levels of functioning 1992-2011. An important implication of our work is that incremental and practice-driven change processes can significantly transform care systems in the long run. Policy makers need to acknowledge and foster such ongoing innovation processes at micro-level, rather than focusing exclusively on innovations as externally created 'things' that await 'implementation'.

Using complexity theory to analyse the organisational response to resurgent tuberculosis across London

We employ complexity theory to analyse the English National Health Service (NHS)'s organisational response to resurgent tuberculosis across London. Tennison (2002) suggests that complexity theory could fruitfully explore a healthcare system's response to this complex and emergent phenomenon: we explore this claim here. We also bring in established New Public Management principles to enhance our empirical analysis, which is based on data collected between late 2009 and mid-2011. We find that the operation of complexity theory based features, especially self-organisation, are significantly impacted by the macro context of a New Public Management-based regime which values control, measurement and risk management more than innovation, flexibility and lateral system building. We finally explore limitations and suggest perspectives for further research.

The capabilities of chaos and complexity

To what degree could chaos and complexity have organized a Peptide or RNA World of crude yet necessarily integrated protometabolism? How far could such protolife evolve in the absence of a heritable linear digital symbol system that could mutate, instruct, regulate, optimize and maintain metabolic homeostasis? To address these questions, chaos, complexity, self-ordered states, and organization must all be carefully defined and distinguished. In addition their cause-and-effect relationships and mechanisms of action must be delineated. Are there any formal (non physical, abstract, conceptual, algorithmic) components to chaos, complexity, self-ordering and organization, or are they entirely physicodynamic (physical, mass/energy interaction alone)? Chaos and complexity can produce some fascinating self-ordered phenomena. But can spontaneous chaos and complexity steer events and processes toward pragmatic benefit, select function over non function, optimize algorithms, integrate circuits, produce computational halting, organize processes into formal systems, control and regulate existing systems toward greater efficiency? The question is pursued of whether there might be some yet-to-be discovered new law of biology that will elucidate the derivation of prescriptive information and control. “System” will be rigorously defined. Can a low-informational rapid succession of Prigogine’s dissipative structures self-order into bona fide organization?