A Real-world Evaluation of a Case-based Reasoning Algorithm to Support Antimicrobial Prescribing Decisions in Acute Care

被引：29

作者：

Rawson, Timothy M. ^{[1
,2
]}

Hernandez, Bernard ^{[3
]}

Moore, Luke S. P. ^{[1
,2
,4
]}

Herrero, Pau ^{[3
]}

Charani, Esmita ^{[1
]}

Ming, Damien ^{[1
]}

Wilson, Richard C. ^{[1
,2
]}

Blandy, Oliver ^{[1
]}

Sriskandan, Shiranee ^{[1
]}

Gilchrist, Mark ^{[2
]}

Toumazou, Christofer ^{[3
]}

Georgiou, Pantelis ^{[3
]}

Holmes, Alison H. ^{[1
,2
]}

机构：

[1] Imperial Coll London, Natl Inst & Lealth Res, Hlth Protect Res Unit Healthcare Associated Infec, Hammersmith Campus, London, England

[2] Imperial Coll Healthcare NHS Trust, Hammersmith Hosp, London, England

[3] Imperial Coll London, Dept Elect & Elect Engn, South Kensington Campus, London, England

[4] Chelsea & Westminster NHS Fdn Trust, London, England

来源：

CLINICAL INFECTIOUS DISEASES | 2021年 / 72卷 / 12期

基金：

英国工程与自然科学研究理事会;

关键词：

Artificial intelligence; machine learning; sepsis; antimicrobial stewardship; clinical decision support systems; ANTIBIOTIC-THERAPY; SYSTEM; TREAT; MANAGEMENT; APPROPRIATENESS; PREDICTION; RETRIEVAL; PATHOGENS; PATTERNS; PROGRAM;

D O I：

10.1093/cid/ciaa383

中图分类号：

R392 [医学免疫学]; Q939.91 [免疫学];

学科分类号：

100102 ;

摘要：

Background. A locally developed case-based reasoning (CBR) algorithm, designed to augment antimicrobial prescribing in secondary care was evaluated. Methods. Prescribing recommendations made by a CBR algorithm were compared to decisions made by physicians in clinical practice. Comparisons were examined in 2 patient populations: first, in patients with confirmed Escherichia coli blood stream infections ("E. coli patients"), and second 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 World Health Organization 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. Results. In total, 224 patients (145 E. coli patients and 79 ward patients) were included. Mean (standard deviation) age was 66 (18) years with 108/224 (48%) female sex. The CBR recommendations were appropriate in 202/224 (90%) compared to 186/224 (83%) in practice (odds ratio [OR]: 1.24 95% confidence interval [CI]:.392-3.936; P = .71). CBR recommendations had a smaller ASI compared to practice with a median (range) of 6 (0-13) compared to 8 (0-12) (P < .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 < .01). Results were similar for E. coli and ward patients on subgroup analysis. Conclusions. A 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 behaviors more broadly and patient outcomes.

引用

页码：2103 / 2111

页数：9

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