Article Text
PDF
Abstract
Objectives To perform a model-based cost-effectiveness evaluation of a rapid antimicrobial susceptibility test.
Design A Markov model of a cohort of hospital inpatients with urinary tract infection (with inpatient numbers based on national administrative data from 1 April 2017 to 31 March 2019).
Setting Urinary tract infections (UTI) in acute National Health Service (NHS) Trusts in England, from the perspective of the NHS Healthcare system, at a national level.
Participants A simulated cohort of approximately 280 000 non-pregnant adult inpatients within secondary care with a clinical suspicion of UTI.
Interventions Evaluation of the implementation of a fast bacterial impedance cytometry test (BICT) compared with current practice.
Primary and secondary outcome measures Incremental cost, quality-adjusted life years, net monetary benefit, and bed days and appropriateness of antibiotic use per patient. Costs are presented in 2022 GBP.
Results Considering benefits arising from reduced time on inappropriate treatment, BICT gives an average net monetary benefit (NMB) over the simulation period of approximately £4.3 million and dominates culture methods (from the healthcare system perspective and with a willingness to pay threshold of £20 000 per quality-adjusted life year). Total inappropriate prescribing days due to the BICT test are reduced by 57%. The extent of the benefit from BICT implementation was strongly dependent on prevalence of resistance, with the NMB increasing sevenfold to over £30 million in a high (40%) resistance prevalence scenario. At the population level, the patient groups with the highest cost and quality-adjusted life year impacts were 65–100-year-old females, followed by males, with uncomplicated UTIs. At an individual patient level, however, 16–64-year-old females with complicated UTIs with oral treatment, followed by 65–100-year-old males with complicated UTIs with oral treatment, were impacted to the greatest degree by the rapid BICT.
Conclusions Under conservative assumptions and for wide parameter sensitivity, the implementation of BICT would be cost-effective from the NHS healthcare system perspective.
- Urinary tract infections
- HEALTH ECONOMICS
- Diagnostic microbiology
Data availability statement
All data relevant to the study are included in the article or uploaded as supplementary information. Hospital Episode Statistics (HES) data were used in this study under license. However, these data are subject to restrictions, are not publicly accessible, and require permission from NHS Digital for access. All code, model input data and outputs are available on GitHub repository https://github.com/rdbooton/iFAST.
This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
Statistics from Altmetric.com
Data availability statement
All data relevant to the study are included in the article or uploaded as supplementary information. Hospital Episode Statistics (HES) data were used in this study under license. However, these data are subject to restrictions, are not publicly accessible, and require permission from NHS Digital for access. All code, model input data and outputs are available on GitHub repository https://github.com/rdbooton/iFAST.
Supplementary materials
Supplementary Data
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Footnotes
JVR and NRN are joint senior authors.
X @nichola_naylor
Contributors All authors contributed to writing and editing the manuscript, interpretation and drafting the manuscript. RDB and NRN coded the model and simulated the results. JMS and JR received funding for the project and designed the cost-effectiveness analysis. JR, RDB, NRN, DP, SE, LJB and EA provided data analysis and evidence synthesis. All authors agree to the publication of this manuscript. JR is the guarantor.
Funding This project is funded by the National Institute for Health and Care Research (NIHR) under its Invention for Innovation (i4i) Programme (Grant Reference Number NIHR NIHR200968). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.
Competing interests None declared.
Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.