title: Antimicrobial resistance in the United Kingdom: a mixed-methods dissertation on diagnostics, discourse, and decision-making
Creators: name: Glover, RE
Publisher: name: London School of Hygiene & Tropical Medicine
Year: 2021

description: Background: Antimicrobial resistance (AMR) is the focus of ongoing global health policy attention. A key policy lever in the United Kingdom is the wide-scale adoption of rapid diagnostic tests (RDTs) in hospitals, laboratories, and communities. I sought to analyse the evidence for the effectiveness of certain rapid diagnostic tests, health care providers’ perceptions thereof, the framing of discourses surrounding AMR, and whether key indicators in combatting AMR such as ‘appropriate prescribing’ were helpful, or indeed the right outcomes to measure. Methods: I conducted (i) a systematic review and meta-analysis of the evidence underpinning rapid diagnostic tests for bacterial identification and antibiotic susceptibility testing, (ii) qualitative, semi-structured interviews of health care providers and senior managers in six study sites across the UK, underpinned by Diffusion of Innovation Theory (iii) a critical discourse analysis of submissions to the UK Health and Social Care Committee on AMR, and (iv) a secondary analysis of the qualitative interview data, guided by meso-level theory drawn from Strauss and Abbott in order to problematise the concept of ‘appropriate’ antibiotic prescribing. Results: (i) rapid diagnostic tests for bacterial identification and antibiotic susceptibility testing were not readily amenable to meta-analysis due to a variety of methodological problems in the primary studies. Where it was possible to undertake aggregate effect estimates, the meta-analysis showed that the introduction of rapid diagnostic tests did not significantly reduce in-hospital mortality (RR 0.83, 95% CI 0.60 - 1.15) or length of stay (weighted mean difference = -0.36, 95% CI -1.67 to 0.96) for experimental studies. (ii) The analysis of the 71 qualitative interviews, drawing on Diffusion of Innovation Theory, found that, though there was support for certain types of testing in specific contexts, interviewees had serious concerns about the unintended consequences linked with testing adoption, including the development of superlabs, centralisation, and privatisation. (iii) I identified dominant narratives in the submissions to the UK House of Commons Committee on AMR and found that industries used ‘market paradoxical’ discursive strategies; on the one hand, asking for subsidies and incentives, but on the other hand explaining that regulation would be detrimental to 'innovation'. (iv) My secondary qualitative analysis found that while some solutions to the AMR crisis appear value-neutral, such as improving ‘appropriate’ prescribing, they are in fact contributing to a narrative of corporate capture in public health. Discussion: As the dissertation progressed, it became clear that rapid diagnostic tests for AMR could helpfully be contextualised within the field of the Commercial Determinants of Health (CDoH). This is because corporations and governments alike deploy crisis narratives in order to divert public sector funds to the private sector in a low-regulation environment. Industries in AMR adopt several strategies that are well-known to researchers in CDoH, and this suggests that the definition of CDoH research should be widened beyond an interest in products or commodities that cause only non-communicable diseases. I also consider the material effects of privileging of the private sector in public health, and link my research with the ongoing COVID-19 pandemic response. The thesis concludes with a summary of the main strengths and limitations, and suggestions for further research, including the need for research on the use of evidence by industry; further analysis of industry narratives in public discourse; qualitative research with stakeholders and experts on industry influence in research; and analysis of industry messaging in social media in comparison to that of public health organisations