Imperial College London
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DrLukeMoore

Faculty of Medicine, Department of Infectious Disease

Honorary Clinical Senior Lecturer
 
 
 
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Contact

 

l.moore Website CV

 
 
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Location

 

Chelsea and Westminster HospitalChelsea and Westminster Campus

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Summary

 

Publications

Citation

BibTex format

@article{Rawson:2021:cid/ciaa383,
author = {Rawson, TM and Hernandez, B and Moore, L and Herrero, P and Charani, E and Ming, D and Wilson, R and Blandy, O and Sriskandan, S and Toumazou, C and Georgiou, P and Holmes, A},
doi = {cid/ciaa383},
journal = {Clinical Infectious Diseases},
pages = {2103--2111},
title = {A real-world evaluation of a case-based reasoning algorithm to support antimicrobial prescribing decisions in acute care},
url = {http://dx.doi.org/10.1093/cid/ciaa383},
volume = {72},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - BackgroundA locally developed Case-Based Reasoning (CBR) algorithm, designed to augment antimicrobial prescribing in secondary care was evaluated.MethodsPrescribing recommendations made by a CBR algorithm were compared to decisions made by physicians in clinical practice. Comparisons were examined in two patient populations. Firstly, in patients with confirmed Escherichia coli blood stream infections (‘E.coli patients’), and secondly in ward-based patients presenting with a range of potential infections (‘ward patients’). Prescribing recommendations were compared against the Antimicrobial Spectrum Index (ASI) and the WHO Essential Medicine List Access, Watch, Reserve (AWaRe) classification system. Appropriateness of a prescription was defined as the spectrum of the prescription covering the known, or most-likely organism antimicrobial sensitivity profile.ResultsIn total, 224 patients (145 E.coli patients and 79 ward patients) were included. Mean (SD) age was 66 (18) years with 108/224 (48%) female gender. The CBR recommendations were appropriate in 202/224 (90%) compared to 186/224 (83%) in practice (OR: 1.24 95%CI:0.392-3.936;p=0.71). CBR recommendations had a smaller ASI compared to practice with a median (range) of 6 (0-13) compared to 8 (0-12) (p<0.01). CBR recommendations were more likely to be classified as Access class antimicrobials compared to physicians’ prescriptions at 110/224 (49%) vs. 79/224 (35%) (OR: 1.77 95%CI:1.212-2.588 p<0.01). Results were similar for E.coli and ward patients on subgroup analysis.ConclusionsA CBR-driven decision support system provided appropriate recommendations within a narrower spectrum compared to current clinical practice. Future work must investigate the impact of this intervention on prescribing behaviours more broadly and patient outcomes.
AU  - Rawson,TM
AU  - Hernandez,B
AU  - Moore,L
AU  - Herrero,P
AU  - Charani,E
AU  - Ming,D
AU  - Wilson,R
AU  - Blandy,O
AU  - Sriskandan,S
AU  - Toumazou,C
AU  - Georgiou,P
AU  - Holmes,A
DO  - cid/ciaa383
EP  - 2111
PY  - 2021///
SN  - 1058-4838
SP  - 2103
TI  - A real-world evaluation of a case-based reasoning algorithm to support antimicrobial prescribing decisions in acute care
T2  - Clinical Infectious Diseases
UR  - http://dx.doi.org/10.1093/cid/ciaa383
UR  - http://hdl.handle.net/10044/1/79074
VL  - 72
ER  -
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