Diagnosis - the limiting focus of taxonomy

Abstract

Rationale, aims and objectives: The focus on the diagnosis is a pivotal aspect of medical practice since antiquity. Diagnostic taxonomy helped to categorize ailments to improve medical care, and in its social sense resulted in validation of the sick role for some, but marginalization or stigmatization for others. In the medical industrial complex, diagnostic taxonomy structured health care financing, management and practitioner remuneration. However, with increasing demands from multiple agencies, there are increasing unintended and unwarranted consequences of our current taxonomies and diagnostic processes resulting from the conglomeration of underpinning concepts, theories, information and motivations.

Results: We argue that the increasing focus on the diagnosis resulted in excessive compartmentalization - 'partialism' - of medical practice, diminishing medical care and being naively simplistic in light of the emerging understanding of the interconnected nature of the diseasome. The human is a complex organic system of interconnecting dynamics and feedback loops responding to internal and external forces including genetic, epigenetic and environmental attractors, rather than the sum of multiple discrete organs which can develop isolated diseases or multiple morbidities. Solutions to these unintended consequences of many contemporary health system processes involve revisiting the nature of diagnostic taxonomies and the processes of their construction. A dynamic taxonomic framework would shift to more relevant attractors at personal, clinical and health system levels recognizing the non-linear nature of health and disease. Human health at an individual, group and population level is the ability to adapt to internal and external stressors with resilience throughout the life course, yet diagnostic taxonomies are increasingly constructed around fixed anchors.

Conclusions: Understanding diagnosis as dissecting, pigeonholing or bean counting (learning by dividing) is no longer useful, the challenge for the future is to understand the big picture (learning by connecting). Diagnostic categorization needs to embrace a meta-learning approach open to human variability.

Keywords: attractors; complexity in health; diagnosis; disease; diseasome; illness; knowledge in medicine; non-linear dynamics; partialism; taxonomy.