In this study, we illustrated a novel quantitative method comprised of a structured decision-support procedure to systematically classify identified barriers in terms of how desirable each one would be to target as part of a behaviour change intervention. Not only was our data analysis model novel, the concept of using multidisciplinary clinicians and managers to consider barriers in a generic sense rather than relating them specifically to whether they were current barriers at their own individual clinical practice environment where some processes may be more or less advanced, also was novel. Further exploration mapping of how prioritisation of barriers at a generic level maps to opinions of clinicians about their local barriers would be of interest. Overall, the set of barriers prioritised for intervention by this method related predominantly to environmental and resource issues; whereas those classified as least desirable to target appeared to relate to social influences and social/professional role issues. The Theoretical Domains Framework  and an established coding framework previously developed by the research team were used to align the most appropriate theoretical domain for each sets of barriers best aligned to.
No one strategy is likely to overcome all barriers identified prior to implementing an intervention; it is likely that different approaches will be effective for different types of people and professional groups, and for different environments. Attempting to resolve barriers can consume limited resources, thus in order to guide the decision-making of hospitals to invest finite resources appropriately and ensure a systematic approach to planning implementation there is a need to prioritise barriers and have a system to identify the most feasible barriers to address [15, 16], even if only in the first instance.
While it is relatively straightforward for an individual expert to produce a ranked list of barriers for a given behaviour, the task of deriving a list based on the opinions of a panel of multidisciplinary experts is difficult, particularly as different members of the panel may have markedly different views . This approach has categorised the desirability of targeting barriers based on consideration of importance and difficulty as judged by a panel of multidisciplinary clinicians and managers.
For this study the barriers pre-specified for each of the targeted behaviours were identified from the literature and a previous clinical trial . If this approach were to be replicated it is important to note that the list of pre-specified barriers is dependent on an existing and comprehensive evidence base. Also, the generalisability of the barrier data populating the questionnaire would be reliant on the quality of included studies and the comprehensiveness of reporting from any source. Although, the content validity of the questionnaire was not formally tested, the research team are recognised experts in this field and the questions included were considered to have face validity in measuring what was intended i.e., influence and difficulty are key attributes for the prioritisation of barriers.
The composition and size of the expert panel, as well as the variable number of members in the professional groups may have implications for how representative the findings are in terms of capturing the views of larger multidisciplinary group of clinicians and managers. In addition, we only assessed the opinions of professional groups for behaviours they were considered to have some influence over, however, it is possible that the perceptions of professionals without direct responsibility for these behaviours may be as valid as those with direct responsibility for these behaviours in terms of ability to rank barriers. Nonetheless, guidance on use of an expert panel for the purpose of identifying and prioritising barriers is sparse, and the work presented here makes an important methodological contribution. This approach may be useful at a local level also to prioritise local barriers.
The paucity of barriers classified as most desirable to target (simultaneously greatest influence, and least difficult to change) highlights that the most influential barriers may also be those most difficult to overcome leading to a natural trade-off between these two attributes. For example, should priority be given to a barrier ranked of ‘quite high’ influence and ‘easy’ to overcome or to a barrier ranked of ‘high’ influence and ‘quite difficult’ to overcome? Therefore, one of the main limitations for this study was a lack of explicit information of how important a barrier’s influence was in relation to its difficulty. Therefore, trade-off decisions between influence and difficulty could not be made for some of the clinical behaviours as part of our study. Prioritisation between these elements might best be decided by clinicians based on their own clinical settings. Future studies that measure the success of overcoming barriers and correlate this with initial perceptions of barriers prior to implementation are required to validate the utility of this approach . It further would test the assumption that clinicians understand what drives their behaviours and what actions may lead to behaviour change. Data from the T3 trial currently are being collected to enable this analysis.
The application of this method is novel and is particularly relevant to the field of implementation science. Previous studies have identified a range of organisational and individual barriers. However, in the absence of a ranked list of prioritised barriers and details about the relative importance and influence of these barriers, previous studies do not provide sufficient detail to prioritise which barriers to target during implementation intervention development. Only two other studies were identified that had prioritised barriers using quantitative methods. One study  aimed to prioritise barriers for the successful implementation of hospital information systems ; participants were asked to prioritise each of the items using a 5-point Likert scale ranging from “very low importance” to “very important”. The other study used discrete choice experiments, a structured approach to investigating individuals’ preferences, to prioritise barrier and facilitators for the implementation of a guideline for breast cancer surgery .
Ascertaining these novel data about barriers has the potential to inform the development of implementation interventions and to assist in the preparation of clinical sites for organisational change. The utility of this method to prioritise barriers needs further investigation, including demonstration of the effectiveness of resultant interventions, such as the T3 trial. Further work to extend these methods could include a comparison of findings between national clinical stroke opinion leaders and stroke clinicians (potential adopters) working at hospitals where the intervention is to be implemented. Additionally, there remains a need to identify the impact of differences between professional groups on prioritisation; for example, to ascertain if barriers prioritised by a group with more responsibility over a particular behaviour are considered more significant than from groups with less authority. This would provide further evidence on how to conduct a barrier assessment and also the process of prioritising barriers. A mixed method approach to barrier prioritisation such as conducting multidisciplinary face-to-face barrier workshops in parallel to a survey may be advantageous. This has the potential to yield richer data about areas of agreement and disagreement, and to also provide an explanation of any differences in prioritisation. Multidisciplinary team discussion would give hospital staff the opportunity to collectively devise strategies to overcome barriers.
It would be also be advantageous to explore and apply alternative methods to identify a set of priority barriers such as the use of discrete choice experiments to investigate preferences . It works on the assumption that decisions are based on multiple criteria and not just one factor (attributes), forcing people to make choices and trade-offs (for example “influence-vs-difficulty”). There may also be benefit in studying the relationship between different types of barriers including gaining knowledge about the consequences or unintended consequences of resolving barriers. For example, would the resolution of the desirable barrier ‘lack of standardised swallow screening tools in ED’ eliminate the less desirable barrier ‘doctors reluctance to use formal swallowing screen’.