A Method for Estimating Relative Complexity of Ambulatory Care

Complexity (science and theory) has been a significant theme in primary care conceptual work and qualitative research. The Annals of Family Medicine has, arguably, been the leading clinically oriented generalist journal in the exposition of complexity and is to be congratulated for publishing this work of Katerndahl and colleagues.(1) However, this analysis of comparing the work of outpatient care in three clinical disciplines – family medicine, cardiology and psychiatry using complexity science, has taken many years to be published. This is despite its subject matter and mathematical analysis being at the centre of the paradigm shift from simple linear to complexity based models in research, practice and policy.

Are we finally on the cusp of modelling health and health services using nonlinear mathematics and statistics?
Will Family Medicine take a lead? In fact, we have had a history of moving towards the polarities of linearity and reductionism in our quantitative and qualitative research rather than open ended nonlinearity and social constructionist approaches, while we openly espouse complexity. Thus there is much work to be done in order to really engage with complexity.(2)

Complexity science is a serious business and requires considerable intellectual effort, as much or more than ‘mainstream’ research, although not promising the ‘nirvana’ of certainty and generalizability.

This paper is highly concentrated and traverses different theories and concepts, as well as demonstrating lateral thinking and innovation. We are pioneering our way forward – through many processes – analysing, sensing, probing, reflecting, acting, feeding back etc. A way forward has been demonstrated by this paper, which opens the way for both the development of complexity science research processes and the utilization of complexity science to embrace the polarities of complexity science in order to address many of the paradoxes of primary care for policy and practice.(3)

The following are reflections in relation to this paper.

Theory
Complexity science encompasses a range of related theories from mathematical complexity, biological complexity, computational complexity, communication and informational complexity, organizational complexity to sociological complexity and others areas.(3) Thus in relation to this paper, we need to have further explicit discussion about what theories and concepts are invoked. Ideally a theoretical paper could be published with theories clearly articulated.

Conceptual framework
This work is located in the policy arena for the value of primary care cognitive and informational work.(4) Traditionally managing more severe disease is considered more cognitively challenging than the undifferentiated and common problems and diagnoses across the life span that make up the diversity of primary care. Thus the work of specialists is judged to have more value than generalists. This analysis uses the framework of work variability and diversity, as recorded in the NAMCS database. Its findings challenge this received wisdom in relation to the information processing from inputs to outputs. The paper goes some way to demonstrate that in primary care, in line with complex systems theory, as the information in the input increases linearly, the complexity of the system increases exponentially.

Analysis
In order to assess the impact of the complexity of the encounter on the physician cognitive complexity or work, the authors adjusted the estimated computational complexity by the duration-of-visit. "The complexity of each input/output is defined as the mean input/output quantity per clinical encounter weighted by its inter-encounter diversity (range of possibilities used) and variability (visit-to-visit change)".

This type of analysis would be very new to the majority of Family Medicine academics – thus there needs to be a series of papers about the type of analyses conducted. In order to embrace many aspects of quantitative complexity, we need to engage with the mathematics of complex systems. The mathematical analysis in this paper requires an explicit outline of the details of the analysis, so that the work could be replicated by others in other settings.

The Way Forward
We are (hopefully) on the cusp of a paradigm shift from linearity to nonlinearity and complexity in the understanding of our discipline. This entails theory, frameworks and concepts, and statistical and mathematical, and other shifts.

We need to have ongoing discussions about severity, diversity, variability and informational and cognitive complexity in relation to our work. Katerndahl et al use a particular database and policy context to demonstrate complexity. This is based on previous conceptual and analytical work.(5)

"Differences in severity of illness are important because, in some cases, the more severe the illness, the more periodic the dynamics. Thus, the nonlinearity decreases as the severity increases. Because diseases exhibiting periodic dynamics should have a more predictable response to therapy, we would expect more severe illnesses to respond more predictably. This pattern has indeed been observed. Prognosis and predictability of treatment response is related to severity of illness in CHF, acute myocardial infarction, depression, and agoraphobia." (5)

Perhaps- this phenomena explains why some of chronic disease management can be 'simple' and 'protocol' based, while much of such care needs active cognitive input and shared decision making. However we also need to recognize that there are other approaches to looking at he complexity of disease and illness care. These include the care of disease and illness in their broader social, environmental and health service contexts (6 7), and the stability and instability of the disease and illness trajectory. (8)

Katerndahl and colleagues are to be congratulated on this work, and pioneering these pathways for us to follow. There needs to be a series of papers to explain the work of this paper in greater detail in order to enable our discipline make sense of the way forward.

1. Katerndahl DA, Wood R, Jaen CR. A Method for Estimating Relative Complexity of Ambulatory Care. Ann Fam Med 2010;8(4):341-47.
2. Green LA. The Implications of Measuring Complexity. Ann Fam Med 2010;8(4):291-92.
3. Martin CM. Making sense of polarities in health organizations for policy and leadership Journal of Evaluation in Clinical Practice 2010;16(5):in press.
4. Stange KC, Ferrer RL. The Paradox of Primary Care. Ann Fam Med 2009;7(4):293-99.
5. Katerndahl DA. Is your practice really that predictable? Nonlinearity principles in family medicine. J Fam Pract 2005;54(11):970-7.
6. Martin CM, Peterson C. The social construction of chronicity:- A key to understanding chronic care transformations. Journal of Evaluation in Clinical Practice 2008;in press.
7. Jordon M, Lanham HJ, Anderson RA, McDaniel RR, Jr. Implications of complex adaptive systems theory for interpreting research about health care organizations. J Eval Clin Pract 2010;16(1):228-31.
8. Martin CM, Biswas R, Joshi A, Sturmberg J. Patient Journey Record Systems (PaJR): The development of a conceptual framework for a patient journey system. Part 1. In: Biswas R, Martin C, editors. User-Driven Healthcare and Narrative Medicine: Utilizing Collaborative Social Networks and Technologies. Hershey PA USA: IGI Global, 2010.

Competing interests:   None declared