Views of health care professionals and policy-makers on the use of surveillance data to combat antimicrobial resistance

Abstract

Background: Providing healthcare professionals with health surveillance data aims to support professional and organisational behaviour change. The UK Five Year Antimicrobial Resistance (AMR) Strategy 2013 to 2018 identified better access to and use of surveillance data as a key component. Our aim was to determine the extent to which data on antimicrobial use and resistance met the perceived needs of health care professionals and policy-makers at national, regional and local levels, and how provision could be improved. Methods: We conducted 41 semi-structured interviews with national policy makers in the four Devolved Administrations and 71 interviews with health care professionals in six locations across the United Kingdom selected to achieve maximum variation in terms of population and health system characteristics. Transcripts were analysed thematically using a mix of a priori reasoning guided by the main topics in the interview guide together with themes emerging inductively from the data. Views were considered at three levels-primary care, secondary care and national- A nd in terms of availability of data, current uses, benefits, gaps and potential improvements. Results: Respondents described a range of uses for prescribing and resistance data. The principal gaps identified were prescribing in private practice, internet prescribing and secondary care (where some hospitals did not have electronic prescribing systems). Some respondents under-estimated the range of data available. There was a perception that the responsibility for collecting and analysing data often rests with a few individuals who may lack sufficient time and appropriate skills. Conclusions: There is a need to raise awareness of data availability and the potential value of these data, and to ensure that data systems are more accessible. Any skills gap at local level in how to process and use data needs to be addressed. This requires an identification of the best methods to improve support and education relating to AMR data systems.