Testing a systematic approach to identify and prioritise barriers to successful implementation of a complex healthcare intervention

© 2017 The Author(s). Background: Multiple barriers may inhibit the adoption of clinical interventions and impede successful implementation. Use of standardised methods to prioritise barriers to target when selecting implementation interventions is an understudied area of implementation research. The aim of this study was to describe a method to identify and prioritise barriers to the implementation of clinical practice elements which were used to inform the development of the T3 trial implementation intervention (Triage, Treatment [thrombolysis administration; monitoring and management of temperature, blood glucose levels, and swallowing difficulties] and Transfer of stroke patients from Emergency Departments [ED] ). Methods: A survey was developed based on a literature review and data from a complementary trial to identify the commonly reported barriers for the nine T3 clinical care elements. This was administered via a web-based questionnaire to a purposive sample of Australian multidisciplinary clinicians and managers in acute stroke care. The questionnaire addressed barriers to each of the nine T3 trial clinical care elements. Participants produced two ranked lists: on their perception of: firstly, how influential each barrier was in preventing clinicians from performing the clinical care element (influence attribute); and secondly how difficult the barrier was to overcome (difficulty attribute). The rankings for both influence and difficulty were combined to classify the barriers according to three categories ('least desirable', desirable' or 'most desirable' to target) to assist interpretation. Results: All invited participants completed the survey; (n = 17; 35% medical, 35% nursing, 18% speech pathology, 12% bed managers). The barriers classified as most desirable to target and overcome were a 'lack of protocols for the management of fever' and 'not enough blood glucose monitoring machines'. Conclusions: A structured decision-support procedure has been illu