Feasibility study of hospital antimicrobial stewardship analytics using electronic health records

• Published in: JAC-antimicrobial resistance Vol. 3; no. 1; p. dlab018
• Main Authors: Dutey-Magni, P F, Gill, M J, McNulty, D, Sohal, G, Hayward, A, Shallcross, L, Anderson, Niall, Crayton, Elise, Forbes, Gillian, Jhass, Arnoupe, Richardson, Emma, Richardson, Michelle, Rockenschaub, Patrick, Smith, Catherine, Sutton, Elizabeth, Traina, Rosanna, Atkins, Lou, Conolly, Anne, Denaxas, Spiros, Fragaszy, Ellen, Horne, Rob, Kostkova, Patty, Lorencatto, Fabiana, Michie, Susan, Mindell, Jennifer, Robson, John, Royston, Claire, Tarrant, Carolyn, Thomas, James, West, Jonathan, Williams, Haydn, Elsay, Nadia, Fuller, Chris
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 01.03.2021
• Subjects: Original
• ISSN: 2632-1823; 2632-1823
• DOI: 10.1093/jacamr/dlab018

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.