One of the problems noted regarding the ability to research complexity is the failure to develop methods that allow the research of scenarios relevant to the reality of the real world (Blackman et al., 2013). Configurational comparative methods offer an opportunity to address this issue and it has been suggested that they could be applied to researching hospital error and in particular examine unusual cases in order to develop better understanding of the underlying complexity which may then assist in improving error management (Bell, 2007).
The term CCM generally refers to a group of methods. For the purposes of this research the term will be used in reference to the associated with the two most common set-theoretic methods of crisp and fuzzy set qualitative comparative analysis (csQCA and fsQCA). When discussing the detail in relation to analysis using each of these methods reference will be made to the particular form of QCA being used. This clear differentiation between terminology relating to research design and the process of analysis is to clearly separate the two and to assist in avoiding
confusion which may occur if the terms are used interchangeably.
These methods use comparative approaches to study diversity as opposed to qualitative approaches which are used to study commonality and quantitative approaches used to study covariance (Ragin, 1987; Ragin & Amoroso, 2011). They are also case-based.
There are a variety of ways in which case research is applied. Casesmay be a theoretical construct or identified through empirical units (Ragin, 1992). Ultimately,
76 it is important for a researcher to clearly indicate what a case is “of” (Luck et al., 2006).
Configurational comparative methods study cases by considering configurations of the presence (or absence) of conditions of interest and determines those which may be causal for the presence (or absence) of an outcome (Ragin & Amoroso, 2011). Hence, use of the term configurational comparative methods. The
mathematical underpinnings of these methods reside in fuzzy set theory leading to them also being referred to as set theoretic methods.
These methods contrast with both quantitative and qualitative methods (Ragin, 1987). Quantitative research emphasises the relationship between different variables, whereas configurational methods focus upon the cases themselves and how the conditions of interest relate to each case. Qualitative research focuses on identifying variables or conditions but how their presence or absence impacts upon a particular outcome on a case-by-case basis is not understood. It is possible to understand this impact through a CCM approach.
Central to CCMs are the concepts of conjunctural causality and equifinality. The intersection of more than one factor (that is a configuration of conditions) leading to an outcome is referred to as conjunctural causality (Ragin, 1987). That is, a single element alone does not cause an outcome but the outcome is the result of that element acting with other factors (Schneider & Wagemann, 2012). The term
equifinality refers to the possibility that more than one configuration (that is alternative configurations of the same conditions) may also lead to the same outcome (Schneider & Wagemann, 2012).
There are several ways that CCM may be used for research. These include summarising data, checking data coherence, checking a hypothesis or existing theory, testing conjecture and for developing new theoretical arguments. Analysis with CCM leads to the researcher moving between inductive and deductive
77 Configurational comparative methods are valuable for understanding context, interactions and causal complexity (Collier, 2014). This makes them useful for researching the complexity of patient safety within health care.
A systems approach to patient safety is about enhancing the capacity for those who work within the system to do the right thing through more than just standardised approaches such as checklists but recognising that behaviour is influenced by context (Dekker & Leveson, 2014). The literature review presented in the previous chapter identified a possible influence of workplace setting, work role and other elements upon safety climate, error reporting and disclosure. Each of these is an example of how context may influence behaviour.
Current approaches to research have merely identified these issues that exist, with no capacity to understand how they impact upon the individual clinician whose behaviour in doing the right thing is crucial to the delivery of safe patient care. Configurational comparative methods therefore offer an opportunity to fill this gap in how knowledge is formed in relation to the way clinicians think and behave. Causal relationships may work differently in different contexts (Denk & Lehtinen, 2013). Therefore the use of CCM for this research may assist in understanding why different workplace settings or work roles show differences relating to safety climate, error and disclosure.
It is the configurations of the conditions of each case that matter, specific to that case (Denk & Lehtinen, 2013). It is often unusual cases or outliers that provide new information in health care (Runciman, 2002). The use of configurational
comparative methods allows for the identification of different states of a similar system that enables the researcher to look at the cases that are of interest, whether that be in relation to a particular outcome or the identification and examination of those cases that are unusual.
78 Focus on effectality
Arguments have also been put forward of a need for greater focus on the nature of effect as much as that of causality. This is termed effectality and it is achieved through thinking about the actions needed towards the achievement of a desired outcome rather than actions as a cause of what has happened. Such an approach is considered retroductive (Byrne, 2011).
Four types of effectality have been defined with respect to a system. These are the specifying of the original position (the nature of the space when it came into existence), staying the same (whilst some aspects may change the system remains the same), undergoing phase shift (although the system remains there is a change in its character) and terminating (whereby the system ceases to exist in any form and loses its inherent integrity) (Byrne, 2011).
Evidence based medicine tends to promote deductive reasoning using quantitative methods and is useful for researching simple/complicated systems. In contrast complexity science leans towards a more inductive approach using qualitative methods to assist understanding a complex/chaotic system. Through use of a CCM the recognition of effectality and approaches to more inductive theory
development may also be a means of adding knowledge and understanding of complexity within health care settings.
The use of CCM is growing. Two reviews have found increasing numbers of studies in a variety of disciplines including health (Rihoux & Marx, 2013; Thiem & Dusa, 2013). Publications have increased substantially in the past ten years with greatest growth occurring in the more developed analysis of fuzzy set QCA (fsQCA).
An example of the use of CCM for health care research is an analysis undertaken with respect to conditions observed for the successful implementation of a smoking cessation program. This research specifically looked at the conditions present amongst the individuals who participated in the program who ceased smoking. This study determined that whilst education was a required condition, in all cases where
79 an individual ceased smoking access to employment opportunities and housing were conditions that were also needed to be present for the desired outcome (Blackman, 2008).
Without these additional conditions as well as the education provided with the program there was no success for individuals who participated in the smoking cessation program. That is, the research considered each condition with respect to the individual case, rather than comparing the relationship between variables and as a result was able to establish which elements were required for individuals to succeed and cease smoking. These methods have also been used in organisational studies. It has been suggested that as organisational parts are inter-connected then configurational approaches to research are appropriate (Ragin, 2013).
An example from organisational research found that managers with
transformational leadership characteristics were likely to successfully implement change within an organisation. However, through the use of CCM it was also identified that in the absence of such a leadership style the same achievement was possible through a combination of other characteristics by a leader (Whittington & Goodwin, 2013).
These examples demonstrate the use of CCM to generate knowledge of complexity. In addition, they are examples of the use of CCM within both health care and organisational research.
Therefore use of CCM shows promise in order to understand the complexity of safety climate, error reporting and disclosure. Having established this, it is necessary to now consider the development of research sub-questions to inform the overall research question and research aims of this research. Once this has been undertaken it is possible to discuss in detail how CCM may be used for this research. This discussion will be presented in the following chapter.
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