Implementing shared decision-making into practice: Embracing complexity

Author:Sarah Munro

This post was originally published by the Evidence & Policy blog on 28 October 2020.

We have re-issued the article that has already been published by the Evidence & Policy blog. We would like to express gratitude to the kind offer of the editorial board of the Evidence & Policy blog.



Sarah Munro


How do we implement shared decision-making into routine practice? Health systems are struggling with this question worldwide. Instead of simplifying this challenge into barriers and facilitators, what if we embraced its complexity?


In recent years there have been increasing calls for the implementation of shared decision-making in routine clinical care. Shared decision-making is particularly helpful for decisions where there are multiple appropriate options, and the ‘best’ decision rests with the patient’s preferences.


Through shared decision-making, health care teams and patients exchange information to understand the pros and cons of health care options, consider the patient’s values and preferences, and decide on a healthcare strategy that includes best evidence and the patient’s preferences. Ideally, this results in a patient decision that is informed, matches their values, and is acted upon.


Shared decision-making has been called the ‘pinnacle of patient-centred care’, but its implementation in routine care has been slow and inconsistent. Why?


A growing body of research has taken a ‘barriers and facilitators’ approach to understanding the factors that influence implementation of shared decision-making. Issues identified include lack of time during short clinic appointments, lack of training in shared decision-making skills and behaviours, and power dynamics between patients and providers. However, a barriers-facilitators approach may not be enough to fully understand the impediments to poor implementation of shared decision-making.


Alternatively, we can take a complex adaptive systems perspective and investigate how context influences the implementation of shared decision-making. A complex adaptive system is a collection of people, organizations, and other influencers that act in unpredictable and interconnected ways. In implementation studies, complexity theory can help us understand how people interact, and how they self-organize to implement innovations in policy and practice.


In our recent Evidence & Policy article, ‘Implementation of shared decision-making in healthcare policy and practice: a complex adaptive systems perspective,’ we draw on the case example of how patients choose mode of birth after a previous caesarean section. We apply complex adaptive systems theory to look at relationships between barriers and enablers, and how these differ among different clinical settings, health professional groups, and geographic areas. The patterns we identified may explain why some patients who value and prefer vaginal delivery choose to plan elective repeat caesarean and why decision makers committed to supporting patients’ access to planned vaginal birth may simultaneously feel that it is an unsafe option.


Through interviews with 58 patients, care providers, and health system decision makers, one factor emerged as a key challenge to implementing shared decision-making in this context: lack of access to surgical and anaesthesia services to support both modes of delivery after caesarean. The lack of access to these services stems from care provider concerns about patient safety, media coverage of adverse events, decision makers’ concerns about litigation, and limited resources stemming from budget constraints.


The dynamic interaction between these barriers illustrates what implementation researchers have predicted: ‘there could be synergistic effects such that two seemingly minor barriers constitute an important obstacle to successful outcomes if they interact’.


Solving implementation challenges sometimes requires a complexity approach. Our approach demonstrates that it can be helpful to explore how complex patterns evolve within systems, how they self-organize, and the interactions between them.

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This post was originally published by Transforming Society on August 2020.


You can read the original research in Evidence & Policy:


Munro, S. Kornelsen, J. Wilcox, E. Kaufman, S. Bansback, N. Corbett, K. and Janssen, P. (2020). Implementation of shared decision-making in healthcare policy and practice: a complex adaptive systems perspective. Evidence & Policy, DOI: 10.1332/174426419X15468571657773.


Image credit:Photo by Emma Pasewald on Unsplash

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If you enjoyed this blog post, you may also be interested to read:


The debate over rational decision making in evidence-based medicine: Implications for evidence-informed policy


To what extent does evidence support decision making during infectious disease outbreaks? A scoping literature review [Open Access]


A qualitative exploration of evidence-based decision making in public health practice and policy: the perceived usefulness of a diabetes economic model for decision makers

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This post was originally published by Transforming Society on August 2020.

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