Original Research

Practice Jazz: Understanding Variation in Family Practices Using Complexity Science

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Much variation exists in family practices. There is also much that is constant and deeply resistant to change.


 

References

Much variation exists in family practices. There is also much that is constant and deeply resistant to change. In this paper we present the current state of an ongoing 4-year process of applying the concepts of complexity science to help interpret the results of 3 studies of the content and process of family practice. We use 2 case studies from these data sets to illustrate the application of complexity science to understanding variation and the process of change in generalist practice.

Our emerging understanding conceptualizes family practices as local professional complex adaptive systems. These systems exist for the purpose of seeing patients for everyday health concerns and assisting them in getting on with their daily lives. Each family practice is unique because of history and initial conditions, particular agents (eg, physicians, staff, patients, systems), nonlinear interactions among agents, the local ecology, and regional and global influences. How all these factors manifest in a particular practice can be understood using 3 complexity science properties: self-organization, emergence, and co-evolution. The concepts of sensemaking and improvisation can be used to understand how practices deal with variation.

We conclude that complexity science concepts can provide a useful framework for understanding variation and change in family practices. The challenge is to differentiate error from relational variation and to improve practices’ sensemaking and improvisational skills. Future efforts to improve practice should focus on optimizing a practice’s care as a whole and enhancing reflective practice and relationship-centered care.

One major focus of health services research and quality improvement efforts is to identify and reduce variation.1-4 Standardization is the approach usually offered to minimize variation, thus reducing errors and increasing quality.5,6 These interventions are often based on an industrial quality improvement paradigm7 using linear interventions that assume that inputs reliably lead to proportionate responses.8 These interventions include re-engineering and expanded information systems.9,10 If the application of linear Newtonian views is correct, then standardization is the key to quality improvement, and effective practices will look much alike. The search for and attempt to implement best practice guidelines11-14 are examples of efforts to bring practices into conformity and to establish process standards for best behavior. However, the search for simple, easily transportable interventions has not been as successful as traditional logic might suggest.15-19

Emerging views of organizations derived from complexity science bring the key understanding that practices are more than commodity-delivering businesses—they are complex adaptive systems.20 These systems involve connected participants interacting in ways that generate the spontaneous emergence of new structures and behaviors. In complex adaptive systems, we expect to see variation in practice patterns, even when the outcomes of practices are similar.

In a previous issue of JFP,21 we proposed a model of primary care practices as complex adaptive systems and suggested implications and strategies for change. Since then we have begun applying this theoretical framework to other studies designed to understand and advance generalist practice. Our present purpose is to advance the application of complexity science to understanding and improving primary care practices and their co-evolving health care systems.

The theory application process

The 3 studies that this theory application builds on began with the Direct Observation of Primary Care (DOPC) study, a 3-year (1994-1997) multimethod descriptive investigation of the content of 4454 patient visits to 138 family physicians in 84 family practices.22,23 One of the outcomes of this study was a model for understanding change in family practice based on complexity science.21 Subsequently, The Prevention and Competing Demands in Primary Care Study (PCDPC) was a 3-year (1996-1999) in-depth descriptive case study of 1637 outpatient visits to 56 clinicians in18 family practices purposefully sampled to include diversity in geographic location, size of practice, and intensity of delivery of preventive services.24 We also implemented a 4-year (1997-2001) multimethod clinical trial, the Study to Enhance Prevention by Understanding and Practice (STEP-UP), to understand and improve the delivery of preventive health services in 77 family practices.25

We conducted an explicit theory application and refinement process consisting of 10 meetings to analyze data from DOPC, PCDPC, and STEP-UP, informed by a literature review of complexity science. The developing model was explicitly tested in 3 Nebraska family practices in 1999 in an effort to improve diabetes care.26 The resulting specific theory application to family practices was then evaluated using 2 cases from these studies.

Application of complexity science to family practice

Synthesizing our observations of the family practices and the literature review, we developed the following theoretical model. Family practices are local professional complex adaptive systems with the primary purpose of seeing patients for everyday health concerns to assist “them” in getting on with their daily lives. “Them” refers to the patients and their families, the clinicians, and the office staff. Practice leaders and managers usually describe their practices in terms of efficiency, productivity, adherence to standards of care, and patient satisfaction. Increasingly, practices function in interactive ways with managers or owners from local health care systems. Still, these practices behaved more like complex adaptive systems operating within a professional milieu than like businesses.27

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