Evidence-based medicine: is it a bridge too far?

AIMS: This paper aims to describe the contextual factors that gave rise to evidence-based medicine (EBM), as well as its controversies and limitations in the current health context. Our analysis utilizes two frameworks: (1) a complex adaptive view of health that sees both health and healthcare as non-linear phenomena emerging from their different components; and (2) the unified approach to the philosophy of science that provides a new background for understanding the differences between the phases of discovery, corroboration, and implementation in science. RESULTS: The need for standardization, the development of clinical epidemiology, concerns about the economic sustainability of health systems and increasing numbers of clinical trials, together with the increase in the computer's ability to handle large amounts of data, have paved the way for the development of the EBM movement. It was quickly adopted on the basis of authoritative knowledge rather than evidence of its own capacity to improve the efficiency and equity of health systems. The main problem with the EBM approach is the restricted and simplistic approach to scientific knowledge, which prioritizes internal validity as the major quality of the studies to be included in clinical guidelines. As a corollary, the preferred method for generating evidence is the explanatory randomized controlled trial. This method can be useful in the phase of discovery but is inadequate in the field of implementation, which needs to incorporate additional information including expert knowledge, patients' values and the context. CONCLUSION: EBM needs to move forward and perceive health and healthcare as a complex interaction, i.e. an interconnected, non-linear phenomenon that may be better analysed using a variety of complexity science techniques.

Systems and complexity thinking in the general practice literature: an integrative, historical narrative review.

PURPOSE: Over the past 7 decades, theories in the systems and complexity sciences have had a major influence on academic thinking and research. We assessed the impact of complexity science on general practice/family medicine. METHODS: We performed a historical integrative review using the following systematic search strategy: medical subject heading [humans] combined in turn with the terms complex adaptive systems, nonlinear dynamics, systems biology, and systems theory, limited to general practice/family medicine and published before December 2010. A total of 16,242 articles were retrieved, of which 49 were published in general practice/family medicine journals. Hand searches and snowballing retrieved another 35. After a full-text review, we included 56 articles dealing specifically with systems sciences and general/family practice. RESULTS: General practice/family medicine engaged with the emerging systems and complexity theories in 4 stages. Before 1995, articles tended to explore common phenomenologic general practice/family medicine experiences. Between 1995 and 2000, articles described the complex adaptive nature of this discipline. Those published between 2000 and 2005 focused on describing the system dynamics of medical practice. After 2005, articles increasingly applied the breadth of complex science theories to health care, health care reform, and the future of medicine. CONCLUSIONS: This historical review describes the development of general practice/family medicine in relation to complex adaptive systems theories, and shows how systems sciences more accurately reflect the discipline's philosophy and identity. Analysis suggests that general practice/family medicine first embraced systems theories through conscious reorganization of its boundaries and scope, before applying empirical tools. Future research should concentrate on applying nonlinear dynamics and empirical modeling to patient care, and to organizing and developing local practices, engaging in community development, and influencing health care reform.

Measures that matter should define accountability and governance frameworks.

While the Royal Commission into Aged Care Quality and Safety has clearly identified the issues with our Australian residential aged care system, its recommendations-so far-have not been translated into policies that will ensure a framework in which nursing home operators and care staff are empowered to focus on what matters-ensuring vulnerable residents receive care that meets their needs and preserves their dignity. For this to be achievable the system requires measures that in the first instance reflect the system's purpose, and that all stakeholders can use to improve care. Such measures need to be easy to understand and implement, and most importantly reduce bureaucratic burden.

From cause and effect to causes and effects.

It is now-at least loosely-acknowledged that most health and clinical outcomes are influenced by different interacting causes. Surprisingly, medical research studies are nearly universally designed to study-usually in a binary way-the effect of a single cause. Recent experiences during the coronavirus disease 2019 pandemic brought to the forefront that most of our challenges in medicine and healthcare deal with systemic, that is, interdependent and interconnected problems. Understanding these problems defy simplistic dichotomous research methodologies. These insights demand a shift in our thinking from 'cause and effect' to 'causes and effects' since this transcends the classical way of Cartesian reductionist thinking. We require a shift to a 'causes and effects' frame so we can choose the research methodology that reflects the relationships between variables of interest-one-to-one, one-to-many, many-to-one or many-to-many. One-to-one (or cause and effect) relationships are amenable to the traditional randomized control trial design, while all others require systemic designs to understand 'causes and effects'. Researchers urgently need to re-evaluate their science models and embrace research designs that allow an exploration of the clinically obvious multiple 'causes and effects' on health and disease. Clinical examples highlight the application of various systemic research methodologies and demonstrate how 'causes and effects' explain the heterogeneity of clinical outcomes. This shift in scientific thinking will allow us to find the necessary personalized or precise clinical interventions that address the underlying reasons for the variability of clinical outcomes and will contribute to greater health equity.

Complex adaptive organisations: How three-dimensional visualisations can help to understand their structures and behaviours.

Many organisations struggle to achieve their true potential. In part it is a problem of organisational design, which is an outcome of a particularly common-command and control-leadership philosophy. The traditional linear hierarchical structure of organisations suggests that all knowledge and power concentrates at the top organisational layer, and that people in the lower layers need to be told what to do and when. These arrangements disempower people at the lower level, preventing them from providing the necessary feedback to pre-emptively address emerging concerns. Systems and complexity thinking provide different ways of understanding organisations and their complex adaptive behaviours. In this paper, we first describe the key characteristics of complex adaptive organisations-their structure and dynamic behaviours-and then propose a three-dimensional visualisation of a complex adaptive organisation that allows its members to clearly see and appreciate its interdependencies.

Fit-for-purpose-The bottom-up redesign of the nursing home system: The Australian Aged Care System.

Nursing homes struggle to meet the needs of their residents as they become older and frailer, live with more complex co-morbidity, and are impacted by memory impairment and dementia. Moreover, the nursing home system is overwhelmed with significantly constraining organisational and regulatory demands that stand in the way of achieving resident-focused outcomes. These issues are compounded by the perceptions of poor working environments, poor remuneration, and poor satisfaction amongst staff. The system is beyond the state of 'reform' and requires a fundamental redesign based on first organisational systems understandings: a clearly defined purpose and goal, shared values, and system-wide agreed "simple (or operating) rules". A 'fit-for-purpose' future requires a complex adaptive nursing home system characterised by seamless 'bottom-up and top-down' information flows to ensure that the necessary 'work that needs to be done' is done, and a governance structure that focuses on quality improvement and holds the system accountable for the quality of care that is provided.

Systemic failures in nursing home care-A scoping study.

Nursing homes (also referred to as residential aged care facilities, or long-term care facilities) cater for older people on a respite or long-term basis for those who are no longer able to live independently at home. Globally the sector struggles to meet societal expectations since it is torn between three competing agendas-meeting the needs of residents, meeting the demands of regulators, and meeting the financial imperatives of nursing home proprietors. Competing demands indicate that the system lacks a clear understanding of its purpose-without a clearly understood purpose any system will become dysfunctional overall and across all its levels of organisation. This scoping study aims to summarise and synthesise what is already known about the systemic function and failures in the nursing home system, and the impact this has on the wider health and aged care system. METHOD: MEDLINE, EMBASE, PSYCHINFO, CINAHL and SCOPUS were searched using the terms: (nursing home care OR residential aged care OR nursing home) AND (organisational failure OR institutional failure OR systemic failure), limited to English language articles, including all years up to the end of February 2021. In addition, we used snowballing of article references and Google searches of the grey literature. System-focused articles were defined as those that explored how an issue at one system level impacted other system levels, or how an issue impacted at least two different agents at the same system level. RESULT: Thirty-eight articles addressed systemic issues as defined in four different contexts: United States (14), Canada (2), Australia (11) and European countries (11). Only four studies reported whole-of-system findings, whereas the remaining 34 more narrowly addressed systemic features of specific nursing home issues. The thematic analysis identified 29 key systemic issues across five system layers which consistently appear across every country/health system context. The negative outcomes of these systemic failings include: high rates of regulatory reprimands for unacceptable or unsafe practices; dissatisfaction in care experiences on the part of residents, families, and care staff-including a fear of being sent to a nursing home; and the perception amongst staff that nursing homes are not preferred places to work. CONCLUSIONS: The key issues affecting nursing home residents, and the care home sector more generally, are systemic in nature arising from two key issues: first, the lack of shared agreement on the care home system's purpose; and second, the lack of clear governance and accountability frameworks for system regulation and performance at a national level. Addressing these two key issues must be the starting point for any 'real' nursing home system redesign that can achieve a seamlessly integrated system that delivers the outcomes nursing home residents and their families expect. 'Systems thinking' is required to simultaneously improve care quality and outcomes for residents, strengthen regulation and accountability, and enable financial viability.

The Clinical Role of Heart Rate Variability Assessment in Cognitively Impaired Patients and Its Applicability in Community Care Settings: A Systematic Review of the Literature.

Heart rate variability (HRV) correlates well with a person's overall physiological function. Clinically, HRV is successfully used in acute care to identify impending infections, but little is known about its potential in the management of chronic diseases like cognitive decline/dementia. The aim of this study was to identify the best available knowledge about HRV in cognitively impaired populations that might be applied to improve clinical practice in community settings. We conducted a systematic literature search in PubMed, Embase, and Cochrane databases published from January 2009 to August 2022. Eligible studies were selected using Covidence and each study underwent qualitative assessment using the Mixed Method Appraisal Tool. At each stage of selection, each study was reviewed independently by two members of the team, and any disputes were discussed along the way. The literature identified that the brain regions controlling HRV are also those affected by dementias of Alzheimer's type (AD) and Lewy body types (DLB). HRV was impaired in both types, with DLB showing greater impairment in all HRV parameters compared to AD. No studies explored the temporal changes of HRV or its use in the clinical management of people with cognitive impairment (CI). The current lack of standardization of HRV recording and analysis limits its use in clinical practice. HRV may emerge as a potentially useful tool to identify people with early/preclinical memory impairment and help to differentiate AD from DLB. Longitudinal HRV measurement is emerging as a useful way to monitor disease progression and treatment response, and continuous HRV measurement may prove useful in the early identification of sepsis and its complications in patients no longer able to communicate their illness experiences.

The need for a change in medical research thinking. Eco-systemic research frames are better suited to explore patterned disease behaviors.

Many practicing physicians struggle to properly evaluate clinical research studies - they either simply do not know them, regard the reported findings as 'truth' since they were reported in a 'reputable' journal and blindly implement these interventions, or they disregard them as having little pragmatic impact or relevance to their daily clinical work. Three aspects for the latter are highlighted: study populations rarely reflect their practice population, the absolute average benefits on specific outcomes in most controlled studies, while statistically significant, are so small that they are pragmatically irrelevant, and overall mortality between the intervention and control groups are unaffected. These observations underscore the need to rethink our research approaches in the clinical context - moving from the predominant reductionist to an eco-systemic research approach will lead to knowledge better suited to clinical decision-making for an individual patient as it takes into account the complex interplay of multi-level variables that impact health outcomes in the real-world setting.

Who is "anti-science"?

Objectives: "Anti-science" accusations are common in medicine and public health, sometimes to discredit scientists who hold opposing views. However, there is no such thing as "one science". Epistemology recognizes that any "science" is sociologically embedded, and therefore contextual and intersubjective. In this paper, we reflect on how "science" needs to adopt various perspectives to give a comprehensive and nuanced understanding of a phenomenon. Study design: Opinion paper. Methods: Based on a targeted literature survey, we first clarify the known limits of traditional scientific methods and then reflect on how the scientific reporting about Covid-19 mRNA vaccines has evolved. Results: The first reports of the Covid-19 mRNA vaccines randomised controlled trial results showed impressive efficacy. Nevertheless, an abundant literature has since depicted a far more nuanced picture of the effectiveness and safety of those vaccines over the medium-term. We organise them around five themes: (i) differentiating between relative and absolute reduction; (ii) taking account of time in reporting effectiveness; (iii) taking account of all outcomes, including adverse effects; (iv) stratifying effectiveness and considering other decision criteria (efficiency, equity, and acceptance); (v) changing the outcome of concern and assessing vaccines' effectiveness on mortality. Conclusions: Science offers a wide range of perspectives on a given study object. Only the process of deliberation amongst scientists and other stakeholders can result in accepted new knowledge useful to support decision-making. Unfortunately, by trying to reduce "science" to simple messages set in stone, scientists can become the worse enemies of science.

What Complexity Science Predicts About the Potential of Artificial Intelligence/Machine Learning to Improve Primary Care.

Primary care physicians are likely both excited and apprehensive at the prospects for artificial intelligence (AI) and machine learning (ML). Complexity science may provide insight into which AI/ML applications will most likely affect primary care in the future. AI/ML has successfully diagnosed some diseases from digital images, helped with administrative tasks such as writing notes in the electronic record by converting voice to text, and organized information from multiple sources within a health care system. AI/ML has less successfully recommended treatments for patients with complicated single diseases such as cancer; or improved diagnosing, patient shared decision making, and treating patients with multiple comorbidities and social determinant challenges. AI/ML has magnified disparities in health equity, and almost nothing is known of the effect of AI/ML on primary care physician-patient relationships. An intervention in Victoria, Australia showed promise where an AI/ML tool was used only as an adjunct to complex medical decision making. Putting these findings in a complex adaptive system framework, AI/ML tools will likely work when its tasks are limited in scope, have clean data that are mostly linear and deterministic, and fit well into existing workflows. AI/ML has rarely improved comprehensive care, especially in primary care settings, where data have a significant number of errors and inconsistencies. Primary care should be intimately involved in AI/ML development, and its tools carefully tested before implementation; and unlike electronic health records, not just assumed that AI/ML tools will improve primary care work life, quality, safety, and person-centered clinical decision making.

Generalist solutions to complex problems: generating practice-based evidence--the example of managing multi-morbidity.

BACKGROUND: A growing proportion of people are living with long term conditions. The majority have more than one. Dealing with multi-morbidity is a complex problem for health systems: for those designing and implementing healthcare as well as for those providing the evidence informing practice. Yet the concept of multi-morbidity (the presence of >2 diseases) is a product of the design of health care systems which define health care need on the basis of disease status. So does the solution lie in an alternative model of healthcare? DISCUSSION: Strengthening generalist practice has been proposed as part of the solution to tackling multi-morbidity. Generalism is a professional philosophy of practice, deeply known to many practitioners, and described as expertise in whole person medicine. But generalism lacks the evidence base needed by policy makers and planners to support service redesign. The challenge is to fill this practice-research gap in order to critically explore if and when generalist care offers a robust alternative to management of this complex problem. We need practice-based evidence to fill this gap. By recognising generalist practice as a 'complex intervention' (intervening in a complex system), we outline an approach to evaluate impact using action-research principles. We highlight the implications for those who both commission and undertake research in order to tackle this problem. SUMMARY: Answers to the complex problem of multi-morbidity won't come from doing more of the same. We need to change systems of care, and so the systems for generating evidence to support that care. This paper contributes to that work through outlining a process for generating practice-based evidence of generalist solutions to the complex problem of person-centred care for people with multi-morbidity.

Systemic Reflections on Knowledge Transfer Comment on "Sustaining Knowledge Translation Practices: A Critical Interpretive Synthesis".

The systemic failure of organisational learning should not come as a surprise - after all every system delivers exactly what it is designed for. Knowledge management/transfer is a property of the organisational system rather than a particular technique. Hence, knowledge management/transfer is about the contextual framing in which learning focused on understanding can occur. Looking through a system lens any research field can be defined as a complex adaptive organisation, and its culture determines if and how learning and knowledge transfer (or shared learning) can occur. Creating and maintain a learning culture requires leadership that perpetuates continuous dialogues to achieve tacit and explicit knowledge exchange.

A sustainable vision for general practice: Understanding the challenges.

BACKGROUND: The COVID-19 pandemic has revealed the full extent of the crisis in general practice, which has emerged as nothing more than the tip of the iceberg of a health system in crisis. OBJECTIVE: This article introduces the systems and complexity thinking that frame the problems affecting general practice and the systemic challenges inherent in redesigning it. DISCUSSION: The authors show how embedded general practice is in the overall complex adaptive organisation of the health system. They allude to some of the key concerns that need to be dissolved in its redesign to achieve an effective, efficient, equitable and sustainable general practice system within a redesigned overall health system to achieve the best possible desired health experiences for patients.

A sustainable vision for general practice: Addressing the challenges

BACKGROUND: The systemic problems and challenges of general practice within the health system require systemic solutions. OBJECTIVE: Noting the complex adaptive nature of health, illness and disease, and its distribution within communities and general practice work, this article suggests a model for general practice that allows the full scope of practice to be developed while creating seamlessly integrated general practice colleges that support general practitioners on their journey to 'mastery' in their chosen discipline. DISCUSSION: The authors discuss the complex dynamics underpinning knowledge and skills development throughout doctors' careers, and the need for policy makers to evaluate health improvement and resourcing based on their interdependencies with all societal activity. To succeed, the profession would have to adopt the principles that form the foundation of generalism and complex adaptive organisations to strengthen its ability to successfully interact with all its stakeholders.

Shared decision-making in the realm of uncertainty: The example of coronary artery disease through an EBM and complexity science lens.

Patients look to their clinicians for explanations and treatments that achieve predictable cures with certainty. Clinicians usually respond accordingly. Acknowledging uncertainty, while necessary, is difficult, anxiety-provoking and at times overwhelming for patients and clinicians alike. We here present three case studies to illustrate the uncertainties of managing patients with potentially life-threatening illnesses. Research aims to provide answers to clinical problems. But, conducting research almost inevitably entails a reduction of real-world complexities. Research ultimately can only provide 'partial or in general answers' mostly revealing new questions. Due to the complexity of clinical care, research cannot really achieve certainty and predictability for an individual within his specific living context and values. In an unavoidably uncertain environment, instead of oversimplifying, clinicians like patients-as far as possible-ought to better embrace a complexity thinking frame. This provides a deeper understanding how living bodies function as-a-whole within their living contexts. Uncertainty and unpredictability, being inherent elements of complexity thinking, cannot be overcome. However, it may be made easier to cope with uncertainty by at least adopting the thinking in probabilities for benefits and harms of patient related outcomes as introduced in Sackett's Evidence-Based Medicine framework. Through the lenses of evidence-based medicine and complexity sciences this paper critically explores the clinical management of three patients diagnosed as having coronary artery disease. They all received the same treatment even though they presented with very different clinical complaints arising from different disease manifestations. Looking at these case studies the authors reflect on the reasons behind this astonishing, but widely seen medical behaviour of 'one size fits all'. They critically reflect the importance of research and evidence in view of a person-centred solution.

Perspectives of (/memorandum for) systems thinking on COVID-19 pandemic and pathology.

Is data-driven analysis sufficient for understanding the COVID-19 pandemic and for justifying public health regulations? In this paper, we argue that such analysis is insufficient. Rather what is needed is the identification and implementation of over-arching hypothesis-related and/or theory-based rationales to conduct effective SARS-CoV2/COVID-19 (Corona) research. To that end, we analyse and compare several published recommendations for conceptual and methodological frameworks in medical research (e.g., public health, preventive medicine and health promotion) to current research approaches in medical Corona research. Although there were several efforts published in the literature to develop integrative conceptual frameworks before the COVID-19 pandemic, such as social ecology for public health issues and systems thinking in health care, only a few attempts to utilize these concepts can be found in medical Corona research. For this reason, we propose nested and integrative systemic modelling approaches to understand Corona pandemic and Corona pathology. We conclude that institutional efforts for knowledge integration and systemic thinking, but also for integrated science, are urgently needed to avoid or mitigate future pandemics and to resolve infection pathology.

There is More to 'Making Connections to Improve Health Outcomes'.

Langevin1 rightly points to the reductionist mindset being the stumbling block for providing person-centered care. While considering the interconnections between the various domains underpinning health is a necessary first step towards more person-centered care, it ultimately is not sufficient. Person-centered care arises from the appreciation of the interdependencies and interactions between the various domains across its large-scale supersystems as much as its small-scale subsystems. Viewed with a complex-adaptive systems mindset health and disease are the phenotypical outcome categorisations of a person's whole-of-systems dynamics across all scales of organisation.2,3.