Interpretation and implications for the design and delivery of A&F
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Around 35% of eligible physicians signed up for the report. However, under 30% of the physicians who signed up subsequently downloaded their reports. We therefore could not answer our relatively intricate research questions due to a lack of engagement. Previous work with this report showed that antipsychotic prescribing was reduced only for those who signed up for and downloaded their report [Further research to establish strategies most likely to enhance engagement, particularly with physicians who may be most likely to benefit from feedback, would advance the science and practice of A&F. Clinical Performance Feedback Intervention Theory (CP-FIT) proposes that “pushing” A&F to providers rather than requiring the “pulling” of A&F, clearly demonstrating the potential benefits of the A&F, and targeting providers with positive attitudes to feedback all serve to enhance engagement and thereby A&F effectiveness [It is also worth noting that whilst most participants did not download their report, they did demonstrate some initial engagement by voluntarily signing up for the report in the first place. Whilst the strategies suggested above may help to sustain their engagement, there may also be other factors making it difficult for them to integrate the use of A&F into their day-to-day practice. In this case, it may be worthwhile to investigate the impact of supportive goal setting, action planning, problem-solving, and habit formation strategies designed to encourage continued review and use of feedback. In sum, future research should focus on evaluating the effectiveness of a range of strategies aiming to enhance both initial and sustained engagement with A&F interventions. In accordance with Goal Setting Theory [A key hypothesis of CP-FIT is that feedback is more effective when it fits alongside existing ways of working [The process evaluation also indicated that both factors minimally impacted our proposed mechanisms of effect. Most participants across all groups intended to adjust their prescribing, were confident in doing so, prioritized adjusting their prescribing, and believed that doing so would avoid unnecessary risks to their residents’ health. This may indicate that these constructs were not the key barriers preventing change [Since this trial, OH has updated the design and delivery of its report. The report is now directly emailed to physicians. The information is risk-framed, focusing on the number of residents prescribed high-risk medications. The median prescribing rate is provided as the comparator, and in addition, physicians’ prescribing rates are described in reference to their peers. Specifically, prescribing rates higher than the 60th percentile are noted and highlighted in red; prescribing rates between the 25th and 60th percentiles are noted and highlighted in yellow and prescribing rates lower than the 75th percentile are noted and highlighted in green. Prescribing rates are reported overall and for each home a physician works in. The CNS-active medications indicator is still included but no longer features on the summary page as a “headline” indicator. The impact of the updated report on prescribing rates will be the subject of future work.