Florida workers' compensation has made a shift to "objective medical evidence." Section 440.09, for example, uses "objective relevant medical findings" three times. It defines
"'objective relevant medical findings' are those objective findings that correlate to the subjective complaints of the injured employee and are confirmed by physical examination findings or diagnostic testing."
There are also references to "objective" elsewhere in the statute, notably in the requirements for our Florida Impairment Guides.
I was intrigued to run across a recent article When Complexity Science Meets Implementation Science: a theoretical and empirical analysis of systems change (April 2018). It is founded upon the study of implementation in "the evidence-based medicine movement" and the underlying "straight line," or "linear" process commonly relied upon in scientific progress. That is a process reminiscent of our recent COVID-19 experience: laboratory effort, clinical trials, and then "new tests, drugs, equipment, or procedures."
The authors describe this as a "knowledge pipeline," and concede that it has "deliver(ed) huge advances in medicine over the last two centuries." But, they warn that this linear approach is not suited to the overall complexity that is modern healthcare. Their conclusion is that for these complexities, science must adapt. Critical to the approach is a broader understanding of "systems-level behaviors" and reactions from a more macro view.
The authors are critical of the limited potential offered by this linear model (which they describe as Newtonian) because they perceive the "clinical frontlines" as resistant to change when the most successful innovations are ultimately made available. However, they are more critical of the current methodology of research funding, the propensity of various hypotheses to fail along the development pathway, and the challenges in implementation that result. They characterize the medical delivery system as "socio-technical," recognizing some element of humanistic implication, perhaps emotion, involved in or influencing the science itself. They believe these influences may come from the researchers, implementers, or consumers. The resistance and complications are multifaceted and multi-source.
They contend that a theoretical approach called "complexity science" can be applied to this traditional "implementation science" to empower "more effective" evidence-based care. They conclude that system change is possible in large and complex systems such as medical practice, but that it is dependent upon some "triggering mechanism" that may be regulatory (top-down) or participatory (market up). The authors concede that change is complicated because our medical care system is complicated with a multitude of "forces, variables, and social practices." Whether the stimulus thus comes through direction or consensus, there is potential for changes to take hold, increase in momentum, and deliver improvement on a systemic basis.
The complexity approach recognizes of these groups and their contributions to the science: "aggregating to be more than the sum of their parts." Their contributions or influences may be of varying intensities and particularities as regards any particular challenge or solution. Thus, progress is expected to occur in an environment of "variations, multiple pathways, unanticipated processes and results, and exhibit conflict between stakeholders." The participants and their humanity create and perpetuate uncertainties in substance, process, and pace. The seeming chaos of the human condition, coupled with the dynamic of both involved individuals and groups, thus makes progress somewhat unpredictable and a challenge to map or plan.
They describe "the Greenhalgh model" on "diffusion of innovation," suggesting "pivotal systems factors" upon which implementation of change depend: (1) "the innovation itself," (2) "the system’s . . . readiness for change, (3) the "implementation process," and (4) the existence of "external . . . context." That there is complexity does not mean that hypothesis cannot proceed to implementation ("from bench to bedside or test tube to needle"), it means that the path may not be the straight line that one might expect. The path may instead be "convoluted, imprecise, uncertain, ambiguous, and deceptive." We cannot conclude our trip from Colorado to Connecticut an unmitigated success if we describe our route through Anwar, Cape Town, and Beijing.
The authors suggest that energy is lost in the scientific process through independent and focused study on "parts of a system . . . as distinct variables" that are combined analytically into a composite whole on an assumption of completeness and overall comprehension. In other words, what we gather and combine we assume to be all there is. It is possible our model does not include all possible or appropriate parts, but instead, the ones we located and chose to include. From the resulting product, causes and proposed solutions to systemic behavior are conceived, designed, and implemented. These largely focus on particular, discreet, variables. If those are confronted and controlled, then the composite whole is altered and improved.
The authors do not decry that there is thus focus on these elements, but in fact concede "the agents and their artifacts, are important." Those may, seemingly, be any of the inputs whether theory, function, or the people that provide (or resist) implementation. However, they contend that it is more important to perceive and understand "the relationships between these components." In other words, it may be less about the ingredients in the recipe and more about the methodology or order of preparation and thereby the interaction of those ingredients.
This article is a fascinating read regarding systems and the challenges that science faces. It is practical to accept that there is incredible complexity in the field of science, the practice of medicine, and the deployment/implementation of change. It is also practical to reflect on the authors' suggestions in a broader context. Might their observations of complexity, ingredients, contributors, constituencies, and challenges be as aptly applied to amalgam that is workers' compensation?
It is difficult to conceive of anything as complex as the human body upon which science is focused. Various functional systems (circulatory, nervous, skeletal, etc.) coexist in concert, in balance, and in interdependence. However, that may as aptly describe workers' compensation. This thing we all too often refer to in a singular sense is at least 60 jurisdictional systems, each comprised of various parameters (rules, statutes, precedent), each subject to influences regional, professional, financial, functional, and human. In discussing the various statutory reforms, a common illustration is of Comp being a balloon: "When pressure is applied to one part, the balloon neither shrinks nor grows, the volume shifts to some other part of the balloon." That may aptly illustrate the authors' warning about a singular focus on a mere element of the whole.
The authors of this article provide insight into the potential for better scientific analysis through the adoption, or at least appreciation, of non-linear thinking. Their focus on the implementation of evidence-based medicine is critical in our community that has adopted such medicine into the standard. However, the broader appreciation of parts, interactions, complexity, and the resulting composition of the greater whole in our own system or community may be of greater value still.
The authors conclude with a warning that is therefore worthy of consideration:
"Complexity thinking adds a real-world, multidimensional appreciation of the system and its density and dynamics, but it does not make it easier to effect change; in fact, the opposite is true."
Thus, if we accept the applicability of these foundations, we may find a new and broader appreciation, itself another added complexity or challenge.
