Complexity in medicine and healthcare: people and systems, theory and practice

The challenges facing residential aged care homes to participate in quality food and nutrition research

BACKGROUND

There is a clear need for food and nutrition research to lead to pragmatic and sustainable solutions to the ongoing problems in residential aged care, particularly within foodservices. The present study aimed to identify systemic challenges for residential aged care homes in Australia to participate in quality food and nutrition research, using a complexity science lens.

METHODS

Qualitative data from three studies in residential aged care were gathered, which included 28 participants across 21 aged care homes. Qualitative data consisted of in-depth interviews, field notes and email communications with aged care staff. Thematic analysis was undertaken using both inductive and deductive approaches.

RESULTS

Four themes were identified: (1) complex staffing issues deter or impede participation in research; (2) external pressure on the aged care system leads to research not being a priority; (3) funding issues are variable and pose a barrier for some aged care homes; and (4) research processes and requirements can lead to biased samples.

CONCLUSIONS

Several challenges to undertaking quality empirical research in residential aged care in Australia were identified. Research needs to be part of usual business, similar to hospitals, and operate independently of staffing and funding issues. Issues within foodservices are system issues and there is a need for quality empirical research to determine solutions.

Using a complexity science approach to evaluate the effectiveness of just-in-time adaptive interventions: A meta-analysis

Objective

Just-in-time adaptive interventions (JITAIs), which allow individuals to receive the right amount of tailored support at the right time and place, hold enormous potential for promoting behavior change. However, research on JITAIs' implementation and evaluation is still in its early stages, and more empirical evidence is needed. This meta-analysis took a complexity science approach to evaluate the effectiveness of JITAIs that promote healthy behaviors and assess whether key design principles can increase JITAIs' impacts.

Methods

We searched five databases for English-language papers. Study eligibility required that interventions objectively measured health outcomes, had a control condition or pre-post-test design, and were conducted in the real-world setting. We included randomized and non-randomized trials. Data extraction encompassed interventions' features, methodologies, theoretical foundations, and delivery modes. RoB 2 and ROBINS-I were used to assess risk of bias.

Results

The final analysis included 21 effect sizes with 592 participants. All included studies used pre- and post-test design. A three-level random meta-analytic model revealed a medium effect of JITAIs on objective behavior change (g = 0.77 (95% confidence interval (CI); 0.32 to 1.22), p < 0.001). The summary effect was robust to bias. Moderator analysis indicated that design principles, such as theoretical foundations, targeted behaviors, and passive or active assessments, did not moderate JITAIs' effects. Passive assessments were more likely than a combination of passive and active assessments to relate to higher intervention retention rates.

Conclusions

This review demonstrated some evidence for the efficacy of JITAIs. However, high-quality randomized trials and data on non-adherence are needed.

New ways of seeing: supplementing existing competency framework development guidelines with systems thinking

Competency frameworks provide a link between professional practice, education, training, and assessment. They support and inform downstream processes such as curriculum design, assessment, accreditation and professional accountability. However, existing guidelines are limited in accounting for the complexities of professional practice potentially undermining utility of such guidelines and validity of outcomes. This necessitates additional ways of "seeing" situated and context-specific practice. We highlight what a conceptual framework informed by systems thinking can offer when developing competency frameworks. Mirroring shifts towards systems thinking in program evaluation and quality improvement, we suggest that similar approaches that identify and make use of the role and influence of system features and contexts can provide ways of augmenting existing guidelines when developing competency frameworks. We framed a systems thinking approach in two ways. First using an adaptation of Ecological Systems Theory which offers a realist perspective of the person and environment, and the evolving interaction between the two. Second, by employing complexity thinking, which obligates attention to the relationships and influences of features within the system, we can explore the multiple complex, unique, and context-embedded problems that exist within and have stake in real-world practice settings. The ability to represent clinical practice when developing competency frameworks can be improved when features that may be relevant, including their potential interactions, are identified and understood. A conceptual framework informed by systems thinking makes visible features of a practice in context that may otherwise be overlooked when developing competency frameworks using existing guidelines.

A systematic approach to public health - Novel application of the human factors analysis and classification system to public health and COVID-19

In this article, we argue for a novel adaptation of the Human Factors Analysis and Classification System (HFACS) to proactive incidence prevention in the public health and in particular, during and in response to COVID-19. HFACS is a framework of causal categories of human errors typically applied for systematic retrospective incident analysis in high-risk domains. By leveraging this approach proactively, appropriate, and targeted measures can be quickly identified and established to mitigate potential errors at different levels within the public health system (from tertiary and secondary healthcare workers to primary public health officials, regulators, and policymakers).

Measuring fundamental care using complexity science: A descriptive case study of a methodological innovation

AIMS AND OBJECTIVES

This paper presents an exploratory account of an innovative methodology to record and evaluate fundamental care. Fundamental care is defined as the care required by everyone for survival, health and welfare.

BACKGROUND

Fundamental care has been informed by the development and testing of the Fundamentals of Care Framework, which describes how fundamental care is complex and multidimensional, and consists of three interrelated dimensions and 38 elements. This accords with a broader re-examination of care provision as part of a complex adaptive system in which existing linear models of cause and effect are inadequate to describe the totality of activity.

DESIGN

Informed by graph theory and complexity science, this paper presents a novel methodological innovation. It uses the Fundamentals of Care Framework to create a Matrix to quantify the relationships between different elements within the Framework.

METHODS

We use a Matrix methodology to process care recipient narratives to generate three outputs: a heat map, a summary table and a network analysis.

CONCLUSIONS

The three outputs serve to quantify and evaluate fundamental care in a multidimensional manner. They capture different perspectives (care recipients and their families, direct care providers and care managers) to improve care outcomes. The future aim is to advance this exploration into digitalising and operationalising the Matrix in a user-friendly manner for it to become a real-time mechanism to evaluate and potentially predict patterns of fundamental care.

Rationale of an Advanced Integrative Approach Applied to Autism Spectrum Disorder: Review, Discussion and Proposal

The rationale of an Advanced Integrative Model and an Advanced Integrative Approach is presented. In the context of Allopathic Medicine, this model introduces the evaluation, clinical exploration, diagnosis, and treatment of concomitant medical problems to the diagnosis of Autism Spectrum Disorder. These may be outside or inside the brain. The concepts of static or chronic, dynamic encephalopathy and condition for Autism Spectrum Disorder are defined in this model, which looks at the response to the treatments of concomitant medical problemsto the diagnosis of Autism Spectrum Disorder. (1) Background: Antecedents and rationale of an Advanced Integrative Model and of an Advanced Integrative Approach are presented; (2) Methods: Concomitant medical problems to the diagnosis of Autism Spectrum Disorder and a discussion of the known responses of their treatments are presented; (3) Results: Groups in Autism are defined and explained, related to the responses of the treatments of the concomitant medical problems to ASD and (4) Conclusions: The analysis in the framework of an Advanced Integrative Model of three groups including the concepts of static encephalopathy; chronic, dynamic encephalopathy and condition for Autism Spectrum Disorder explains findings in the field, previously not understood.

Charting the life course: Emerging opportunities to advance scientific approaches using life course research

Life course research embraces the complexity of health and disease development, tackling the extensive interactions between genetics and environment. This interdisciplinary blueprint, or theoretical framework, offers a structure for research ideas and specifies relationships between related factors. Traditionally, methodological approaches attempt to reduce the complexity of these dynamic interactions and decompose health into component parts, ignoring the complex reciprocal interaction of factors that shape health over time. New methods that match the epistemological foundation of the life course framework are needed to fully explore adaptive, multilevel, and reciprocal interactions between individuals and their environment. The focus of this article is to (1) delineate the differences between lifespan and life course research, (2) articulate the importance of complex systems science as a methodological framework in the life course research toolbox to guide our research questions, (3) raise key questions that can be asked within the clinical and translational science domain utilizing this framework, and (4) provide recommendations for life course research implementation, charting the way forward. Recent advances in computational analytics, computer science, and data collection could be used to approximate, measure, and analyze the intertwining and dynamic nature of genetic and environmental factors involved in health development.

Accounting for complexity in medical education: a model of adaptive behaviour in medicine

CONTEXT

Medicine is practised in complex systems. Physicians engage in clinical and operational problems that are dynamic and lack full transparency. As a consequence, the behaviour of medical systems and diseases is often unpredictable. Medical science has equipped physicians with powerful tools to favourably impact health, but a reductionist approach alone is insufficient to optimally address the complex challenges posed by illness and public health. Concepts from complexity science, such as continuous quality improvement and teamwork, strive to fill the gap between biomedical knowledge and the realities of practice. However, the superficial treatment of these systems-thinking concepts in medical education has distorted their implementation and undermined their impact. 'Systems thinking' has been conflated with 'systematic thinking'; concepts which are adaptive in nature are being taught as standardised, reductionist tools.

METHODS

Using concepts from complexity science, the history of science and psychology, this problem is outlined and a theoretical model of professional development is proposed.

RESULTS

This model proposes that complex problem solving and adaptive behaviour, not technical expertise, are distinguishing features of professionalism.

DISCUSSION

The impact of this model on our understanding of physician autonomy, professionalism, teamwork and continuous quality improvement is discussed. This model has significant implications for the structure and content of medical education. Strategies for enhancing medical training, including interventions in recruitment, the curriculum and evaluation, are reviewed. Such adjustments would prepare trainees to more effectively utilise biomedical knowledge and tools in the complex high-stakes reality of medical practice.

The application of systems thinking concepts, methods, and tools to global health practices: An analysis of case studies

OBJECTIVES

This review of systems thinking (ST) case studies seeks to compile and analyse cases from ST literature and provide practitioners with a reference for ST in health practice. Particular attention was given to (1) reviewing the frequency and use of key ST terms, methods, and tools in the context of health, and (2) extracting and analysing longitudinal themes across cases.

METHODS

A systematic search of databases was conducted, and a total of 36 case studies were identified. A combination of integrative and inductive qualitative approaches to analysis was used.

RESULTS

Most cases identified took place in high-income countries and applied ST retrospectively. The most commonly used ST terms were agent/stakeholder/actor (n = 29), interdependent/interconnected (n = 28), emergence (n = 26), and adaptability/adaptation (n = 26). Common ST methods and tools were largely underutilized. Social network analysis was the most commonly used method (n = 4), and innovation or change management history was the most frequently used tool (n = 11). Four overarching themes were identified; the importance of the interdependent and interconnected nature of a health system, characteristics of leaders in a complex adaptive system, the benefits of using ST, and barriers to implementing ST.

CONCLUSIONS

This review revealed that while much has been written about the potential benefits of applying ST to health, it has yet to completely transition from theory to practice. There is however evidence of the practical use of an ST lens as well as specific methods and tools. With clear examples of ST applications, the global health community will be better equipped to understand and address key health challenges.

Thinking about complexity in health: A systematic review of the key systems thinking and complexity ideas in health

RATIONALE, AIMS, AND OBJECTIVES

As the Sustainable Development Goals are rolled out worldwide, development leaders will be looking to the experiences of the past to improve implementation in the future. Systems thinking and complexity science (ST/CS) propose that health and the health system are composed of dynamic actors constantly evolving in response to each other and their context. While offering practical guidance for steering the next development agenda, there is no consensus as to how these important ideas are discussed in relation to health. This systematic review sought to identify and describe some of the key terms, concepts, and methods in recent ST/CS literature.

METHOD

Using the search terms "systems thinkin * AND health OR complexity theor* AND health OR complex adaptive system* AND health," we identified 516 relevant full texts out of 3982 titles across the search period (2002-2015).

RESULTS

The peak number of articles were published in 2014 (83) with journals specifically focused on medicine/healthcare (265) and particularly the Journal of Evaluation in Clinical Practice (37) representing the largest number by volume. Dynamic/dynamical systems (n = 332), emergence (n = 294), complex adaptive system(s) (n = 270), and interdependent/interconnected (n = 263) were the most common terms with systems dynamic modelling (58) and agent-based modelling (43) as the most common methods.

CONCLUSIONS

The review offered several important conclusions. First, while there was no core ST/CS "canon," certain terms appeared frequently across the reviewed texts. Second, even as these ideas are gaining traction in academic and practitioner communities, most are concentrated in a few journals. Finally, articles on ST/CS remain largely theoretical illustrating the need for further study and practical application. Given the challenge posed by the next phase of development, gaining a better understanding of ST/CS ideas and their use may lead to improvements in the implementation and practice of the Sustainable Development Goals.

Difficult medical encounters and job satisfaction - results of a cross sectional study with general practitioners in Germany

Background

In primary care 15% of patient encounters are perceived as challenging by general practitioners (GP). However it is unknown what impact these encounters have regarding job satisfaction. The aim of this study was to evaluate which encounters are perceived as challenging by German GPs and whether they were associated with job satisfaction.

Methods

A total of 1538 questionnaires were sent to GPs in the federal state of Schleswig-Holstein, Germany. GPs should rate 14 medical conditions and 8 traits of patients on the perceived challenge using a Likert scale (1: ‘not challenging at all’ to 10: ‘extremely challenging’). Job satisfaction was measured with the Warr–Cook–Wall job satisfaction scale. A linear regression analyses were used to explore potential associations between for the primary outcome variable ‘overall job satisfaction’.

Results

Total response was 578 (38%). GPs perceived 16% of their patients as challenging. Psychiatric disorders such as somatization disorder (mean = 7.42), schizophrenia (mean = 6.83) and anxiety disorder (mean = 6.57) were ranked as high challenging while diabetes mellitus type 2 (mean = 4.87) and high blood pressure (mean = 3.22) were ranked as a rather low challenging condition. GPs were mostly satisfied with ‘colleagues’ (mean = 5.80) and mostly dissatisfied with their ‘hours of work’ (mean = 4.20). The linear regression analysis showed no association with challenging medical conditions and traits of patients but only with different aspects of job satisfaction concerning the outcome variable ‘overall job satisfaction’.

Conclusions

Especially psychiatric conditions are perceived as challenging the question arises, in what amount psychiatric competences are gained during the postgraduate specialty training in general practice and if GPs with a mandatory rotation in psychiatry perceive these conditions as less challenging. Interestingly this study indicates that challenging encounter in terms of challenging medical conditions and traits of patients do not affect GP’s job satisfaction.

Electronic supplementary material

The online version of this article (10.1186/s12875-018-0747-0) contains supplementary material, which is available to authorized users.

Predictive model of complexity in early palliative care: a cohort of advanced cancer patients (PALCOM study)

PROPOSAL

Model of early palliative care (PC) integrated in oncology is based on shared care from the diagnosis to the end of life and is mainly focused on patients with greater complexity. However, there is no definition or tools to evaluate PC complexity. The objectives of the study were to identify the factors influencing level determination of complexity, propose predictive models, and build a complexity scale of PC.

PATIENTS AND METHOD

We performed a prospective, observational, multicenter study in a cohort of advanced cancer patients with an estimated prognosis ≤ 6 months. An ad hoc structured evaluation including socio-demographic and clinical data, symptom burden, functional and cognitive status, psychosocial problems, and existential-ethic dilemmas was recorded systematically. According to this multidimensional evaluation, investigator classified patients as high, medium, or low palliative complexity, associated to need of basic or specialized PC. Logistic regression was used to identify the variables influencing determination of level of PC complexity and explore predictive models.

RESULTS

We included 324 patients; 41% were classified as having high PC complexity and 42.9% as medium, both levels being associated with specialized PC. Variables influencing determination of PC complexity were as follows: high symptom burden (OR 3.19 95%CI: 1.72-6.17), difficult pain (OR 2.81 95%CI:1.64-4.9), functional status (OR 0.99 95%CI:0.98-0.9), and social-ethical existential risk factors (OR 3.11 95%CI:1.73-5.77). Logistic analysis of variables allowed construct a complexity model and structured scales (PALCOM 1 and 2) with high predictive value (AUC ROC 76%).

CONCLUSION

This study provides a new model and tools to assess complexity in palliative care, which may be very useful to manage referral to specialized PC services, and agree intensity of their intervention in a model of early-shared care integrated in oncology.

The Affordable Care Act: a case study for understanding and applying complexity concepts to health care reform

RATIONALE, AIMS AND OBJECTIVES

The current health system in the United States is the result of a history of patchwork policy decisions and cultural assumptions that have led to persistent contradictions in practice, gaps in coverage, unsustainable costs, and inconsistent outcomes. In working toward a more efficient health system, understanding and applying complexity science concepts will allow for policy that better promotes desired outcomes and minimizes the effects of unintended consequences.

METHODS

This paper will consider three applied complexity science concepts in the context of the Patient Protection and Affordable Care Act (PPACA): developing a shared vision around reimbursement for value, creating an environment for emergence through simple rules, and embracing transformational leadership at all levels.

RESULTS AND CONCLUSIONS

Transforming the US health system, or any other health system, will be neither easy nor quick. Applying complexity concepts to health reform efforts, however, will facilitate long-term change in all levels, leading to health systems that are more effective, efficient, and equitable.

Organizational structures during SOA implementation: the case of a Greek healthcare organization

Purpose

– The purpose of this paper is to investigate service-oriented architecture organizational studies (SOA OS) in healthcare through a rigorous literature review, development and testing in an eGovernment health-care setting. The application of SOA paradigm to integrate information systems has been pursued mainly by private organizations. However, SOA starts to appear in the public agenda and specifically in health-care reengineering, as well. Recently, government strategies for eHealth have been slowly incorporating the SOA paradigm to integrate isolated systems, provide cost-effective solutions and expand the capabilities of their health-care information system. Yet, literature indicates that eHealth government strategies, including SOA, require the support of SOA OS to be successfully implemented.

Design/methodology/approach

– To investigate the less acknowledged phenomena like SOA OS in healthcare, the authors incorporate an interpretive, qualitative case study approach to conduct this research. This method will assist in examining the phenomenon in its natural setting, examine the in-depth complexities and health-care processes and provide rich qualitative data during interviews and observations.

Findings

– The authors critically review the literature and synthesize a SOA OS with specific attributes, sub-elements, guidelines and healthcare-specific parameters. This conceptual structure was tested in the practical arena leading to an evaluated SOA OS blueprint.

Research limitations/implications

– As the outcome of the research was based on a single case, the paper concludes that the SOA OS in health-care research needs to broaden its perspective with more empirical data.

Practical implications

– This research revealed empirical insights that can help practitioners and researchers focus their attention to the significant role that the SOA OS plays during SOA implementations.

Originality/value

– This paper focuses on critical success factors related to SOA implementations in health-care organizations and can be considered as novel as it identifies and structures a SOA OS element that can be part of a SOA governance approach in the area of healthcare.

Towards socio-material approaches in simulation-based education: lessons from complexity theory

CONTEXT

Review studies of simulation-based education (SBE) consistently point out that theory-driven research is lacking. The literature to date is dominated by discourses of fidelity and authenticity - creating the 'real' - with a strong focus on the developing of clinical procedural skills. Little of this writing incorporates the theory and research proliferating in professional studies more broadly, which show how professional learning is embodied, relational and situated in social - material relations. A key concern for medical educators concerns how to better prepare students for the unpredictable and dynamic ambiguity of professional practice; this has stimulated the movement towards socio-material theories in education that address precisely this question.

OBJECTIVES AND METHODS

Among the various socio-material theories that are informing new developments in professional education, complexity theory has been of particular importance for medical educators interested in updating current practices. This paper outlines key elements of complexity theory, illustrated with examples from empirical study, to argue its particular relevance for improving SBE.

RESULTS

Complexity theory can make visible important material dynamics, and their problematic consequences, that are not often noticed in simulated experiences in medical training. It also offers conceptual tools that can be put to practical use. This paper focuses on concepts of emergence, attunement, disturbance and experimentation. These suggest useful new approaches for designing simulated settings and scenarios, and for effective pedagogies before, during and following simulation sessions.

CONCLUSIONS

Socio-material approaches such as complexity theory are spreading through research and practice in many aspects of professional education across disciplines. Here, we argue for the transformative potential of complexity theory in medical education using simulation as our focus. Complexity tools open questions about the socio-material contradictions inherent in SBE, draw attention to important material dynamics of emergence, and suggest practical educative ways to expand and deepen student learning.

Using logic model methods in systematic review synthesis: describing complex pathways in referral management interventions

BACKGROUND

There is increasing interest in innovative methods to carry out systematic reviews of complex interventions. Theory-based approaches, such as logic models, have been suggested as a means of providing additional insights beyond that obtained via conventional review methods.

METHODS

This paper reports the use of an innovative method which combines systematic review processes with logic model techniques to synthesise a broad range of literature. The potential value of the model produced was explored with stakeholders.

RESULTS

The review identified 295 papers that met the inclusion criteria. The papers consisted of 141 intervention studies and 154 non-intervention quantitative and qualitative articles. A logic model was systematically built from these studies. The model outlines interventions, short term outcomes, moderating and mediating factors and long term demand management outcomes and impacts. Interventions were grouped into typologies of practitioner education, process change, system change, and patient intervention. Short-term outcomes identified that may result from these interventions were changed physician or patient knowledge, beliefs or attitudes and also interventions related to changed doctor-patient interaction. A range of factors which may influence whether these outcomes lead to long term change were detailed. Demand management outcomes and intended impacts included content of referral, rate of referral, and doctor or patient satisfaction.

CONCLUSIONS

The logic model details evidence and assumptions underpinning the complex pathway from interventions to demand management impact. The method offers a useful addition to systematic review methodologies.

TRIAL REGISTRATION NUMBER

PROSPERO registration number: CRD42013004037.

Many-models medicine: diversity as the best medicine

Many medicines have been proposed to cure various ills of biomedicine including evidence-based medicine, evolutionary medicine, narrative medicine, and complexity medicine, among others. To the extent that all models are idealizations or abstractions, all of these model medicines are imperfect in some respects. In the absence of a single unified model, if indeed unification is possible or even desirable, and despite the relative advantages of one model or another, in practice many models and methods are necessary in medicine. In this article, I consider the value of such diversity in models and methods. I briefly describe several models. Then I discuss simulations of agents who use diverse models. Advocates of models such as those discussed here typically claim that we should use their preferred model because it is the best. Evidence-based medicine, for instance, has been promoted as the single best model of medicine while other models have been cast as lesser models or in opposition to it and each other. But isolated models and methods may never be as good as groups of models and methods. Debates about various individual models may result in better outcomes, but explicitly choosing to use many models is likely to produce even better outcomes.

Measuring the range of services clinicians are responsible for in ambulatory practice

RATIONALE, AIMS AND OBJECTIVES

At present, the range of services delivered in a health system is not known. Currently there are no accepted methods for defining the scope of ambulatory care. Therefore we used data from the electronic medical record and billing system of a large non-profit multi-specialty group practice to measure the number of different diagnoses that clinicians managed as well as the number of different medications, laboratory tests, imaging studies, referrals and procedures ordered.

METHODS

All patient encounters and clinicians in the group practice in 2008 were eligible for inclusion in the analysis. Data were analysed cumulatively for the practice and by specialty. Quantile regression models were used to adjust for differences in full-time equivalents (FTE) among physicians at the practice.

RESULTS

In one year for this practice, with 324,229 patients who made 3,193,917 office visits to 578 physicians and 248 other clinicians, patients presented with 5638 primary and 6411 secondary diagnoses. Overall, patient management resulted in unique orders for 9481 medications, 1182 laboratory tests, 613 referrals, 284 imaging studies and 1701 procedures. After adjusting for FTE, physicians managed a median of 249 primary diagnoses and 347 secondary diagnoses. They ordered a median of 278 medications, 128 laboratory tests, 51 referrals, 29 imaging studies and 39 procedures.

CONCLUSION

Physicians routinely manage a substantial variety of diagnoses, medications, and other tests and procedures. Quality improvement and health services researchers have generally focused on individual services but also must consider the wide variety and range of services delivered.

Leadership and transitions: maintaining the science in complexity and complex systems

It is the 'moral compass', however subtle, that underpins leadership. Leadership, meaning showing the way, demands as much conviction as gentile diplomacy in the discourse with supporters and detractors. In particular, leadership defends the goal by safeguarding its principles from its detractors. The authors writing in the Forum on Complexity in Medicine and Healthcare since its inception are leaders in an intellectual transition to complex systems thinking in medicine and health.

Complexity and categorical analysis may improve the interpretation of agreement studies using continuous variables

RATIONALE

Complex clinical scenarios involving a high degree of uncertainty frequently lead to a poor agreement over diagnosis and management. However, inconsistent results can be found with the most widely used measures of agreement for continuous variables - the limits of agreement and the intraclass correlation coefficient.

AIMS AND OBJECTIVES

We aim to improve the interpretation of agreement studies using continues variables.

METHODS AND RESULTS

Evaluation of agreement may be improved by complexity analysis and by categorization of variables, followed by the use of the proportions of agreement.

CONCLUSIONS

The average never characterizes a complex phenomenon and the methods used to access agreement in continuous variables are based on the mean. For future agreement studies, involving complex continuous variables, we recommend a complexity and categorical analysis.