Modelling Organisational Resilience

Our current working model of organisational resilience in healthcare is shown below. It is based on resilience engineering theory. This model allows us to identify the key theoretical concepts that we are interested in and the relationships between them so that we can investigate them empirically. This model does not represent the real world in all its detail, but is an abstraction of the hypothesised concepts and relationships that we want to investigate in order to understand resilience better.


Demand and capacity are defined broadly and capture all aspects of the clinical work such as numbers of patients, acuity of patients, targets to be met and the numbers of staff, equipment, and procedures to follow to meet demands. The alignment between demand and capacity is a management task and represents work as it is imagined to be achieved, but it can never be perfect because there will always be unanticipated variation in the demands.

Clinicians’ ability to adjust and adapt their work to produce good outcomes despite the misalignment of demand and capacity is what enables the work system to function. This is what is described as work as done in resilience engineering terms. This concept reflects the idea that work at the sharp end is not completely specified by procedures and policies as working conditions are rarely completely aligned with how they are imagined to be in the procedures. According to resilience engineering theory these adjustments and adaptations in response to variability lead to both success and failure outcomes.

The model is dynamic and aims to capture the interactions between all components of the system. Feedback loops operate – experiences of success and failure can affect demand and capacity. For example, success might lead to reductions in the numbers of readmissions and therefore patient numbers, whereas failure might lead to increased demand in the form of checks and targets, or attempts to increase capacity by training staff. Feedback also occurs between outcomes and adaptations – peoples’ experiences of success may lead to over confidence in improvising procedures, failure may lead to reluctance to improvise and outcomes such as patient experience may suffer due to, for example, longer waiting times.

Adaptations made in situ as work is experienced may be incorporated into procedures and become codified as organisational responses to the misalignment of demand and capacity. For example, escalation policies in the emergency department are triggered to bring in more resources when demand is high, thus attempting to realign demand and capacity. Such policies are attempts to flexibly manage mismatches between demand and capacity.

This model is guiding our empirical work. In ongoing work we are investigating the concepts and their relationships both statistically using administrative data and qualitatively through ethnographic fieldwork and interviews.

This paper provides an overview of our research approach at the Centre for Applied Resilience in Healthcare.

Anderson, J. E., Ross, A., Back, J., Duncan, M., Snell, P., Walsh, K. and Jaye, P. (2016). Implementing resilience engineering for healthcare quality improvement using the CARE model: a feasibility study protocol. Pilot and Feasibility Studies. DOI: 10.1186/s40814-016-0103-x Download

Dr. Janet Anderson