Complex treatment systems such as palliative care, public health, integrative medicine, rehabilitative medicine or traditional Chinese medicine, and interventions within those systems, are an important part of healthcare around the world. However, these approaches to healthcare are not always well served by the biomedical model of diagnosing, treating, understanding and evaluating diseases which emphasizes the evaluation of single-component interventions. The applicability of this model for investigating healthcare as it is actually practiced is limited. Hence, a broader perspective is necessary.
Complementary and alternative medicine (CAM) researchers have a particular interest in driving the debate about how best to assess complex healthcare systems, as they struggle with demands from regulators, insurers, purchasers, providers and patients for ‘evidence’ of effectiveness and efficacy in order to meet the standards of ‘evidence-based medicine’. The debate regarding these research design issues within conventional medicine has risen in parallel with the growing emphasis on team-based medicine and integrative medical teams, and, related to this, the increasing complexity of treatment interventions. In addition, there is increased recognition that explanatory (placebo-controlled) randomized clinical trials (RCTs) alone cannot adequately assess these interventions and their outcomes. Explanatory RCTs are conducted under conditions that are as controlled as possible and include the following characteristics: administration of a placebo to the control group in an attempt to hold all possible causal elements constant except for the intervention under investigation; standardization of inclusion and exclusion criteria; standardization of the intervention under investigation; randomized allocation of the participants to the intervention or the control group(s); blinding (allocation concealment) of the participants and investigators (if possible) (1
A number of descriptive articles have attempted to explain how one might begin to assess these complex interventions. Each approach has developed its own language and concepts to describe the phenomena, making communication and consensus building difficult across approaches. For example, a variety of terminologies has been proposed to describe what appears to be essentially the same phenomenon. In this paper we use the term ‘complex healthcare systems’. We define these as complex interventions to improve or enhance health and well-being as well as to prevent disease. ‘Complex’ denotes the entangled interrelationships among multiple ‘active’ components of the intervention. In addition, it highlights that, in general, the effects of the ‘whole’ intervention or system are interactive rather than additive (2
), with the potential that the whole is more than the sum of the parts. This reasoning reflects the theory that complex systems have an inherent self-organizing property and that the elements of complex systems themselves interact in such a way that through the interplay of the elements new properties emerge that cannot be seen when investigating only the component parts. In our view, both the human body and systems of healthcare have to be seen as complex, self-organizing systems that create new, emerging properties through the interplay of their component elements (5
The purpose of this paper is to compare, contrast and critique four different approaches to the assessment of complex healthcare interventions or systems, also identified as ‘whole’ systems. Terms such as whole systems, complex systems, CAM systems and whole medical systems appear to describe similar concepts. However, this divergence in terminology reflects some unique features with respect to how each is defined and also the cultural context in which each arose. The present paper aims to bring some clarity to the field and helps to establish a broader awareness and understanding of the issues, as well as to facilitate interdisciplinary research.