Developing a Modeling Framework for Quantifying the Health and Cost Implications of Antibiotic Resistance for Surgical Procedures

Heather Davies; Joel Russell; Angel Varghese; Hayden Holmes; Marta O. Soares; B. Woods; Ruth Puig-Peiro; Stephanie Evans; Rory Tierney; Stuart Mealing; Mark Sculpher; Julie V. Robotham

doi:10.1177/23814683231152885

Developing a Modeling Framework for Quantifying the Health and Cost Implications of Antibiotic Resistance for Surgical Procedures

Heather Davies^*, Joel Russell, Angel Varghese, Hayden Holmes, Marta O. Soares, B. Woods, Ruth Puig-Peiro, Stephanie Evans, Rory Tierney, Stuart Mealing, Mark Sculpher, Julie V. Robotham

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

65 Downloads (Pure)

Abstract

Background. Antimicrobial resistance (AMR) is a global public health threat. The wider implications of AMR, such as the impact of antibiotic resistance (ABR) on surgical procedures, are yet to be quantified. The objective of this study was to produce a conceptual modeling framework to provide a basis for estimating the current and potential future consequences of ABR for surgical procedures in England.

Design. A framework was developed using literature-based evidence and structured expert elicitation. This was applied to populations undergoing emergency repair of the neck of the femur and elective colorectal resection surgery.

Results. The framework captures the implications of increasing ABR by allowing for higher rates of surgical site infection (SSI) as the effectiveness of antibiotic prophylaxis wanes and worsened outcomes following SSIs to reflect reduced antibiotic treatment effectiveness. The expert elicitation highlights the uncertainty in quantifying the impact of ABR, reflected in the results. A hypothetical SSI rate increase of 14% in a person undergoing emergency repair of the femur could increase costs by 39% (−2% to 108% credible interval [CI]) and decrease quality-adjusted life-years by 11% (0.4% to 62% CI) over 15 y.

Conclusions. The modeling framework is a starting point for addressing the implication of ABR on the outcomes and costs of surgeries. Due to clinical uncertainty highlighted in the expert elicitation process, the numerical outputs of the case studies should not be focused on but rather the framework itself, illustration of the evidence gaps, the benefit of expert elicitation in quantifying parameters with limited data, and the potential magnitude of the impact of ABR on surgical procedures. Implications. The framework can be used to support research surrounding the health and cost burden of ABR in England. The modeling framework is a starting point for assessing the health and cost impacts of antibiotic resistance on surgeries in England. Formulating a framework and synthesizing evidence to parameterize data gaps provides targets for future research. Once data gaps are addressed, this modeling framework can be used to feed into overall estimates of the health and cost burden of antibiotic resistance and evaluate control policies.

Original language	English
Journal	MDM Policy and Practice
Volume	8
Issue number	1
Early online date	4 Feb 2023
DOIs	https://doi.org/10.1177/23814683231152885
Publication status	Published - Jun 2023

Bibliographical note

Funding Information: Financial support for this study was provided entirely by Public Health England Funding from both the Health Economics Commissioning Framework, for undertaking the analysis, and the Statistics, Modelling and Economics Department for publication of this manuscript.

Open Access: This article is distributed under the terms of the Creative Commons
Attribution-NonCommercial 4.0 License (http://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and
Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).

Publisher Copyright: © The Author(s) 2023.

Citation: Davies H, Russell J, Varghese A, et al. Developing a Modeling Framework for Quantifying the Health and Cost Implications of Antibiotic Resistance for Surgical Procedures. MDM Policy & Practice. 2023;8(1). doi:10.1177/23814683231152885

DOI: 10.1177/23814683231152885

Keywords

Surgical site infection
antibiotic resistance
expert elicitation
modelling framework

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1177/23814683231152885Licence: CC BY-NC

Davies2023DevelopingAModelingFrameworkForQuantifyingTheHealthAndCostMDMPolicyPractFinal published version, 1.35 MBLicence: CC BY-NC

Cite this

Davies, H., Russell, J., Varghese, A., Holmes, H., Soares, M. O., Woods, B., Puig-Peiro, R., Evans, S., Tierney, R., Mealing, S., Sculpher, M., & Robotham, J. V. (2023). Developing a Modeling Framework for Quantifying the Health and Cost Implications of Antibiotic Resistance for Surgical Procedures. MDM Policy and Practice, 8(1). https://doi.org/10.1177/23814683231152885

@article{d46bfa3c239e40efaaac68254d48f57c,

title = "Developing a Modeling Framework for Quantifying the Health and Cost Implications of Antibiotic Resistance for Surgical Procedures",

abstract = "Background. Antimicrobial resistance (AMR) is a global public health threat. The wider implications of AMR, such as the impact of antibiotic resistance (ABR) on surgical procedures, are yet to be quantified. The objective of this study was to produce a conceptual modeling framework to provide a basis for estimating the current and potential future consequences of ABR for surgical procedures in England. Design. A framework was developed using literature-based evidence and structured expert elicitation. This was applied to populations undergoing emergency repair of the neck of the femur and elective colorectal resection surgery. Results. The framework captures the implications of increasing ABR by allowing for higher rates of surgical site infection (SSI) as the effectiveness of antibiotic prophylaxis wanes and worsened outcomes following SSIs to reflect reduced antibiotic treatment effectiveness. The expert elicitation highlights the uncertainty in quantifying the impact of ABR, reflected in the results. A hypothetical SSI rate increase of 14% in a person undergoing emergency repair of the femur could increase costs by 39% (−2% to 108% credible interval [CI]) and decrease quality-adjusted life-years by 11% (0.4% to 62% CI) over 15 y. Conclusions. The modeling framework is a starting point for addressing the implication of ABR on the outcomes and costs of surgeries. Due to clinical uncertainty highlighted in the expert elicitation process, the numerical outputs of the case studies should not be focused on but rather the framework itself, illustration of the evidence gaps, the benefit of expert elicitation in quantifying parameters with limited data, and the potential magnitude of the impact of ABR on surgical procedures. Implications. The framework can be used to support research surrounding the health and cost burden of ABR in England. The modeling framework is a starting point for assessing the health and cost impacts of antibiotic resistance on surgeries in England. Formulating a framework and synthesizing evidence to parameterize data gaps provides targets for future research. Once data gaps are addressed, this modeling framework can be used to feed into overall estimates of the health and cost burden of antibiotic resistance and evaluate control policies.",

keywords = "Surgical site infection, antibiotic resistance, expert elicitation, modelling framework",

author = "Heather Davies and Joel Russell and Angel Varghese and Hayden Holmes and Soares, {Marta O.} and B. Woods and Ruth Puig-Peiro and Stephanie Evans and Rory Tierney and Stuart Mealing and Mark Sculpher and Robotham, {Julie V.}",

note = "Funding Information: Financial support for this study was provided entirely by Public Health England Funding from both the Health Economics Commissioning Framework, for undertaking the analysis, and the Statistics, Modelling and Economics Department for publication of this manuscript. Open Access: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). Publisher Copyright: {\textcopyright} The Author(s) 2023. Citation: Davies H, Russell J, Varghese A, et al. Developing a Modeling Framework for Quantifying the Health and Cost Implications of Antibiotic Resistance for Surgical Procedures. MDM Policy & Practice. 2023;8(1). doi:10.1177/23814683231152885 DOI: 10.1177/23814683231152885",

year = "2023",

month = jun,

doi = "10.1177/23814683231152885",

language = "English",

volume = "8",

journal = "MDM Policy and Practice",

issn = "2381-4683",

publisher = "SAGE Publications Inc.",

number = "1",

}

TY - JOUR

T1 - Developing a Modeling Framework for Quantifying the Health and Cost Implications of Antibiotic Resistance for Surgical Procedures

AU - Davies, Heather

AU - Russell, Joel

AU - Varghese, Angel

AU - Holmes, Hayden

AU - Soares, Marta O.

AU - Woods, B.

AU - Puig-Peiro, Ruth

AU - Evans, Stephanie

AU - Tierney, Rory

AU - Mealing, Stuart

AU - Sculpher, Mark

AU - Robotham, Julie V.

N1 - Funding Information: Financial support for this study was provided entirely by Public Health England Funding from both the Health Economics Commissioning Framework, for undertaking the analysis, and the Statistics, Modelling and Economics Department for publication of this manuscript. Open Access: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). Publisher Copyright: © The Author(s) 2023. Citation: Davies H, Russell J, Varghese A, et al. Developing a Modeling Framework for Quantifying the Health and Cost Implications of Antibiotic Resistance for Surgical Procedures. MDM Policy & Practice. 2023;8(1). doi:10.1177/23814683231152885 DOI: 10.1177/23814683231152885

PY - 2023/6

Y1 - 2023/6

N2 - Background. Antimicrobial resistance (AMR) is a global public health threat. The wider implications of AMR, such as the impact of antibiotic resistance (ABR) on surgical procedures, are yet to be quantified. The objective of this study was to produce a conceptual modeling framework to provide a basis for estimating the current and potential future consequences of ABR for surgical procedures in England. Design. A framework was developed using literature-based evidence and structured expert elicitation. This was applied to populations undergoing emergency repair of the neck of the femur and elective colorectal resection surgery. Results. The framework captures the implications of increasing ABR by allowing for higher rates of surgical site infection (SSI) as the effectiveness of antibiotic prophylaxis wanes and worsened outcomes following SSIs to reflect reduced antibiotic treatment effectiveness. The expert elicitation highlights the uncertainty in quantifying the impact of ABR, reflected in the results. A hypothetical SSI rate increase of 14% in a person undergoing emergency repair of the femur could increase costs by 39% (−2% to 108% credible interval [CI]) and decrease quality-adjusted life-years by 11% (0.4% to 62% CI) over 15 y. Conclusions. The modeling framework is a starting point for addressing the implication of ABR on the outcomes and costs of surgeries. Due to clinical uncertainty highlighted in the expert elicitation process, the numerical outputs of the case studies should not be focused on but rather the framework itself, illustration of the evidence gaps, the benefit of expert elicitation in quantifying parameters with limited data, and the potential magnitude of the impact of ABR on surgical procedures. Implications. The framework can be used to support research surrounding the health and cost burden of ABR in England. The modeling framework is a starting point for assessing the health and cost impacts of antibiotic resistance on surgeries in England. Formulating a framework and synthesizing evidence to parameterize data gaps provides targets for future research. Once data gaps are addressed, this modeling framework can be used to feed into overall estimates of the health and cost burden of antibiotic resistance and evaluate control policies.

AB - Background. Antimicrobial resistance (AMR) is a global public health threat. The wider implications of AMR, such as the impact of antibiotic resistance (ABR) on surgical procedures, are yet to be quantified. The objective of this study was to produce a conceptual modeling framework to provide a basis for estimating the current and potential future consequences of ABR for surgical procedures in England. Design. A framework was developed using literature-based evidence and structured expert elicitation. This was applied to populations undergoing emergency repair of the neck of the femur and elective colorectal resection surgery. Results. The framework captures the implications of increasing ABR by allowing for higher rates of surgical site infection (SSI) as the effectiveness of antibiotic prophylaxis wanes and worsened outcomes following SSIs to reflect reduced antibiotic treatment effectiveness. The expert elicitation highlights the uncertainty in quantifying the impact of ABR, reflected in the results. A hypothetical SSI rate increase of 14% in a person undergoing emergency repair of the femur could increase costs by 39% (−2% to 108% credible interval [CI]) and decrease quality-adjusted life-years by 11% (0.4% to 62% CI) over 15 y. Conclusions. The modeling framework is a starting point for addressing the implication of ABR on the outcomes and costs of surgeries. Due to clinical uncertainty highlighted in the expert elicitation process, the numerical outputs of the case studies should not be focused on but rather the framework itself, illustration of the evidence gaps, the benefit of expert elicitation in quantifying parameters with limited data, and the potential magnitude of the impact of ABR on surgical procedures. Implications. The framework can be used to support research surrounding the health and cost burden of ABR in England. The modeling framework is a starting point for assessing the health and cost impacts of antibiotic resistance on surgeries in England. Formulating a framework and synthesizing evidence to parameterize data gaps provides targets for future research. Once data gaps are addressed, this modeling framework can be used to feed into overall estimates of the health and cost burden of antibiotic resistance and evaluate control policies.

KW - Surgical site infection

KW - antibiotic resistance

KW - expert elicitation

KW - modelling framework

UR - http://www.scopus.com/inward/record.url?scp=85147445057&partnerID=8YFLogxK

U2 - 10.1177/23814683231152885

DO - 10.1177/23814683231152885

M3 - Article

AN - SCOPUS:85147445057

SN - 2381-4683

VL - 8

JO - MDM Policy and Practice

JF - MDM Policy and Practice

IS - 1

ER -

Developing a Modeling Framework for Quantifying the Health and Cost Implications of Antibiotic Resistance for Surgical Procedures

Abstract

Bibliographical note

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this