ABSTRACT
BACKGROUND: Hospital antimicrobial stewardship (AMS) programmes are multidisciplinary initiatives to optimize antimicrobial use. Most hospitals depend on time-consuming manual audits to monitor clinicians' prescribing. But much of the information needed could be sourced from electronic health records (EHRs). OBJECTIVES: To develop an informatics methodology to analyse characteristics of hospital AMS practice using routine electronic prescribing and laboratory records. METHODS: Feasibility study using electronic prescribing, laboratory and clinical coding records from adult patients admitted to six specialities at Queen Elizabeth Hospital, Birmingham, UK (September 2017-August 2018). The study involved: (i) a review of AMS standards of care; (ii) their translation into concepts measurable from commonly available EHRs; and (iii) a pilot application in an EHR cohort study (n = 61679 admissions). RESULTS: We developed data modelling methods to characterize antimicrobial use (antimicrobial therapy episode linkage methods, therapy table, therapy changes). Prescriptions were linked into antimicrobial therapy episodes (mean 2.4 prescriptions/episode; mean length of therapy 5.8 days), enabling several actionable findings. For example, 22% of therapy episodes for low-severity community-acquired pneumonia were congruent with prescribing guidelines, with a tendency to use broader-spectrum antibiotics. Analysis of therapy changes revealed IV to oral therapy switching was delayed by an average 3.6 days (95% CI: 3.4-3.7). Microbial cultures were performed prior to treatment initiation in just 22% of antibacterial prescriptions. The proposed methods enabled fine-grained monitoring of AMS practice down to specialities, wards and individual clinical teams by case mix, enabling more meaningful peer comparison. CONCLUSIONS: It is feasible to use hospital EHRs to construct rapid, meaningful measures of prescribing quality with potential to support quality improvement interventions (audit/feedback to prescribers), engagement with front-line clinicians on optimizing prescribing, and AMS impact evaluation studies.
ABSTRACT
Background/Aim: We have a limited understanding of the broader determinants of health of international migrants and how these change over time since migration to the United Kingdom (UK). To address this knowledge gap, we aim to conduct a prospective cohort study with data acquisition via a smartphone application (app). In this pilot study, we aim to 1) determine the feasibility of the use of an app for data collection in international migrants, 2) optimise app engagement by quantifying the impact of specific design features on the completion rates of survey questionnaires and on study retention, 3) gather preliminary profile health status data, to begin to examine how risk factors for health are distributed among migrants. Methods: We will recruit 275 participants through a social media campaign and through third sector organisations that work with or support migrants in the UK. Following consent and registration, data will be collected via surveys. To optimise app engagement and study retention, we will quantify the impact of specific design features (i.e. the frequency of survey requests, the time of day for app notifications, the frequency of notifications, and the wording of notifications) via micro-randomised process evaluations. The primary outcome for this study is survey completion rates with numerator as the number of surveys completed and denominator as the total number of available surveys. Secondary outcomes are study retention rates and ratings of interest after app usage. Ethics and dissemination: We have obtained approval to use consented patient identifiable data from the University College London Ethics Committee. Improving engagement with the app and gathering preliminary health profile data will help us identify accessibility and usability issues and other barriers to app and study engagement prior to moving to a larger study.
