Alison Harper | University of Exeter (original) (raw)

Papers by Alison Harper

2022 Winter Simulation Conference (WSC), Dec 11, 2022

Health Systems, Feb 9, 2023

Journal of the Operational Research Society, May 26, 2022

Applied Health Economics and Health Policy, Dec 18, 2022

Background It is a stated ambition of many healthcare systems to eliminate delayed transfers of c... more Background It is a stated ambition of many healthcare systems to eliminate delayed transfers of care (DTOCs) between acute and step-down community services. Objective This study aims to demonstrate how, counter to intuition, pursual of such a policy is likely to be uneconomical, as it would require large amounts of community capacity to accommodate even the rarest of demand peaks, leaving much capacity unused for much of the time. Methods Some standard results from queueing theory-a mathematical discipline for considering the dynamics of queues and queueing systems-are used to provide a model of patient flow from the acute to community setting. While queueing models have a track record of application in healthcare, they have not before been used to address this question. Results Results show that 'eliminating' DTOCs is a false economy: the additional community costs required are greater than the possible acute cost saving. While a substantial proportion of DTOCs can be attributed to inefficient use of resources, the remainder can be considered economically essential to ensuring cost-efficient service operation. For England's National Health Service (NHS), our modelling estimates annual cost savings of £117m if DTOCs are reduced to the 12% of current levels that can be regarded as economically essential. Conclusion This study discourages the use of 'zero DTOC' targets and instead supports an assessment based on the specific characteristics of the healthcare system considered.

Real-time Simulation (RtS) and Digital Twins (DT) are terms generally associated with hybrid mode... more Real-time Simulation (RtS) and Digital Twins (DT) are terms generally associated with hybrid models that use real-time data to drive computational models. Additionally, in the case of DTs, real-time data is often used to create virtual replicas of the physical system as it progresses through real-time. There is an increasing volume of literature on RtS and DT; however, the field of OR/MS is yet to coalesce on accepted definitions and conceptualisations. This has arguably led to the cascading usage of these terms. The objective of the paper is threefold: (1) distinguish between RtS and DT, (2) present RtS-DT conceptualisation in four dimensions, and (3) present methodological and technical insights on developing RtS with limited data. We argue that the evolution of conventional simulation models to fully-fledged hybrid DTs may necessitate a focus on a transitional stage; namely, RtS models primarily driven using historical distributions with limited real-time data feeds.

The version presented here may differ from the published version. If citing, you are advised to c... more The version presented here may differ from the published version. If citing, you are advised to consult the published version for pagination, volume/issue and date of publication

This paper provides a framework for conceptualising levels of open science and open working withi... more This paper provides a framework for conceptualising levels of open science and open working within computer modelling and simulation. We aim to support researchers to share their models and working so that others are free to use, reproduce, adapt and build upon, and re-share their work. We introduce a six level framework of increasing complexity: not open, open access, open artefacts, open models, open environment and open infrastructure. For each we provide practical advice on what aspects of open science researchers must consider, what options are available to them, and what challenges they will need to overcome. We illustrate our open science framework using a stylised discrete-event simulation model. All code used in this paper is available, cloud executable and reusable under an MIT license.

2021 Winter Simulation Conference (WSC), Dec 12, 2021

Intermediate care supports timely discharge from hospital for patients with complex healthcare ne... more Intermediate care supports timely discharge from hospital for patients with complex healthcare needs. The purpose of 'step-down' care is to enable patients to leave hospital as soon as medically fit, avoiding costly discharge delays and consequent risks to patient health and wellbeing. Determining optimal intermediate care capacity requires balancing costs to both acute hospital and community care providers. Too much community capacity results in underutilized resources and poor economic efficiency, while too little risks excessive hospital discharge delays. Application of discrete-time simulation shows that total costs across the acute-community interface can be minimized by identifying optimal community capacity in terms of the maximum number of patients for which home visits can be provided by the service. To our knowledge, this is the first simulation study to model the patient pathway from hospital discharge through to community visits. Simulation modeling has supported short-term resource planning in a major English healthcare system.

Zenodo (CERN European Organization for Nuclear Research), Mar 29, 2023

The freedom to run the program as you wish, for any purpose.

BMJ Open, Dec 1, 2022

Objectives To identify risk factors associated with prolonged length of hospital stay and staying... more Objectives To identify risk factors associated with prolonged length of hospital stay and staying in hospital longer than medically necessary following primary knee replacement surgery. Design Retrospective, longitudinal observational study. Setting Elective knee replacement surgeries between 2016 and 2019 were identified using routinely collected data from an NHS Trust in England. Participants There were 2295 knee replacement patients with complete data included in analysis. The mean age was 68 (SD 11) and 60% were female. Outcome measures We assessed a binary length of stay outcome (>7 days), a continuous length of stay outcome (≤30 days) and a binary measure of whether patients remained in hospital when they were medically fit for discharge. Results The mean length of stay was 5.0 days (SD 3.9), 15.4% of patients were in hospital for >7 days and 7.1% remained in hospital when they were medically fit for discharge. Longer length of stay was associated with older age (b=0.08, 95% CI 0.07 to 0.09), female sex (b=0.36, 95% CI 0.06 to 0.67), high deprivation (b=0.98, 95% CI 0.47 to 1.48) and more comorbidities (b=2.48, 95% CI 0.15 to 4.81). Remaining in hospital beyond being medically fit for discharge was associated with older age (OR=1.07, 95% CI 1.05 to 1.09), female sex (OR=1.71, 95% CI 1.19 to 2.47) and high deprivation (OR=2.27, 95% CI 1.27 to 4.06). Conclusions The regression models could be used to identify which patients are likely to occupy hospital beds for longer. This could be helpful in scheduling operations to aid hospital efficiency by planning these patients' operations for when the hospital is less busy.

Objectives: Discrete-event simulation is a widely used computational method in health services an... more Objectives: Discrete-event simulation is a widely used computational method in health services and health economic studies. This systematic scoping review investigates to what extent authors share computer models, and audits if sharing adheres to best practice. Data sources: The Web of Science, Scopus, PubMed, and ACM Digital Library databases were searched between 1st January 2019 till 31st December 2022.Eligibility criteria for selecting studies: Cost-effectiveness, Health service research and methodology studies in a health context were included.Data extraction and synthesis: The data extraction and best practice audit were performed by two reviewers. We developed best practice audit criteria based on the Turing Way and other published reproducibility guides.Main outcomes and measures: We measured the proportion of literature that shared models; we report analyses by publication type, year of publication, Covid-19 application; and free and open source versus commercial software. ...

ABSTRACTObjectivesTo develop a simulation model to support orthopaedic elective capacity planning... more ABSTRACTObjectivesTo develop a simulation model to support orthopaedic elective capacity planning.MethodsAn open-source, generalisable discrete-event simulation was developed, including a web-based application. The model used anonymised patient records between 2016-2019 of elective orthopaedic procedures from an NHS Trust in England. In this paper, it is used to investigate scenarios including resourcing (beds and theatres) and productivity (lengths-of-stay, delayed discharges, theatre activity) to support planning for meeting new NHS targets aimed at reducing elective orthopaedic surgical backlogs in a proposed ring fenced orthopaedic surgical facility. The simulation is interactive and intended for use by health service planners and clinicians.ResultsA higher number of beds (65-70) than the proposed number (40 beds) will be required if lengths-of-stay and delayed discharge rates remain unchanged. Reducing lengths-of-stay in line with national benchmarks reduces bed utilisation to ...

Methods or approaches from disciplines outside of OR Modeling and Simulation (M&S) can potentiall... more Methods or approaches from disciplines outside of OR Modeling and Simulation (M&S) can potentially increase the functionality of simulation models. In healthcare research, where simulation models are commonly used, we see few applications of models that can easily be deployed by other researchers or by healthcare stakeholders. Models are treated as disposable artifacts, developed to deliver a set of results for stakeholders or for publication. By utilising approaches from software engineering, M&S researchers can develop models that are intended to be deployed for re-use. We propose one potential solution to deploying free and open source simulations using containerisation with continuous integration. A container provides a self-contained environment that encapsulates the model and all its required dependencies including the operating system, software, and packages. This overcomes a significant barrier to sharing models developed in open source software, which is dependency manageme...

Proceedings of SW21 The OR Society Simulation Workshop, Mar 27, 2023

Proceedings of SW21 The OR Society Simulation Workshop, Mar 27, 2023

Real-time Simulation (RtS) and Digital Twins (DT) are terms generally associated with hybrid mode... more Real-time Simulation (RtS) and Digital Twins (DT) are terms generally associated with hybrid models that use real-time data to drive computational models. Additionally, in the case of DTs, real-time data is often used to create virtual replicas of the physical system as it progresses through real-time. There is an increasing volume of literature on RtS and DT; however, the field of OR/MS is yet to coalesce on accepted definitions and conceptualisations. This has arguably led to the cascading usage of these terms. The objective of the paper is threefold: (1) distinguish between RtS and DT, (2) present RtS-DT conceptualisation in four dimensions, and (3) present methodological and technical insights on developing RtS with limited data. We argue that the evolution of conventional simulation models to fully-fledged hybrid DTs may necessitate a focus on a transitional stage; namely, RtS models primarily driven using historical distributions with limited real-time data feeds.

Proceedings of SW21 The OR Society Simulation Workshop

Inadequate patient flow from hospitals into community care is often blamed for bed blockages in t... more Inadequate patient flow from hospitals into community care is often blamed for bed blockages in the acute setting. This is bad for patient experience and outcomes and has an upstream knock-on effect for Accident and Emergency performance and, in turn, ambulance offload delays and response times. Despite the large numbers of acute bed-days lost to delayed discharges and the ambition to expand home-based community care, there has been a deficit of modelling studies investigating the dynamics of this pathway and providing the relevant insights to service planners. Working closely with healthcare managers, this paper reports on the development and deployment of versatile simulation tools for modelling both the home-based and bedded community step-down pathways, known as 'Discharge to Assess' or D2A in England's NHS. Developed in open source 'R', these tools offer scalable solutions for exploring different scenarios relating to demand, capacity and patient length of stay.

BMJ Open, Dec 1, 2022

Objectives To identify risk factors associated with prolonged length of hospital stay and staying... more Objectives To identify risk factors associated with prolonged length of hospital stay and staying in hospital longer than medically necessary following primary knee replacement surgery. Design Retrospective, longitudinal observational study. Setting Elective knee replacement surgeries between 2016 and 2019 were identified using routinely collected data from an NHS Trust in England. Participants There were 2295 knee replacement patients with complete data included in analysis. The mean age was 68 (SD 11) and 60% were female. Outcome measures We assessed a binary length of stay outcome (>7 days), a continuous length of stay outcome (≤30 days) and a binary measure of whether patients remained in hospital when they were medically fit for discharge. Results The mean length of stay was 5.0 days (SD 3.9), 15.4% of patients were in hospital for >7 days and 7.1% remained in hospital when they were medically fit for discharge. Longer length of stay was associated with older age (b=0.08, 95% CI 0.07 to 0.09), female sex (b=0.36, 95% CI 0.06 to 0.67), high deprivation (b=0.98, 95% CI 0.47 to 1.48) and more comorbidities (b=2.48, 95% CI 0.15 to 4.81). Remaining in hospital beyond being medically fit for discharge was associated with older age (OR=1.07, 95% CI 1.05 to 1.09), female sex (OR=1.71, 95% CI 1.19 to 2.47) and high deprivation (OR=2.27, 95% CI 1.27 to 4.06). Conclusions The regression models could be used to identify which patients are likely to occupy hospital beds for longer. This could be helpful in scheduling operations to aid hospital efficiency by planning these patients' operations for when the hospital is less busy.

2022 Winter Simulation Conference (WSC), Dec 11, 2022

Health Systems, Feb 9, 2023

Journal of the Operational Research Society, May 26, 2022

Applied Health Economics and Health Policy, Dec 18, 2022

Background It is a stated ambition of many healthcare systems to eliminate delayed transfers of c... more Background It is a stated ambition of many healthcare systems to eliminate delayed transfers of care (DTOCs) between acute and step-down community services. Objective This study aims to demonstrate how, counter to intuition, pursual of such a policy is likely to be uneconomical, as it would require large amounts of community capacity to accommodate even the rarest of demand peaks, leaving much capacity unused for much of the time. Methods Some standard results from queueing theory-a mathematical discipline for considering the dynamics of queues and queueing systems-are used to provide a model of patient flow from the acute to community setting. While queueing models have a track record of application in healthcare, they have not before been used to address this question. Results Results show that 'eliminating' DTOCs is a false economy: the additional community costs required are greater than the possible acute cost saving. While a substantial proportion of DTOCs can be attributed to inefficient use of resources, the remainder can be considered economically essential to ensuring cost-efficient service operation. For England's National Health Service (NHS), our modelling estimates annual cost savings of £117m if DTOCs are reduced to the 12% of current levels that can be regarded as economically essential. Conclusion This study discourages the use of 'zero DTOC' targets and instead supports an assessment based on the specific characteristics of the healthcare system considered.

Real-time Simulation (RtS) and Digital Twins (DT) are terms generally associated with hybrid mode... more Real-time Simulation (RtS) and Digital Twins (DT) are terms generally associated with hybrid models that use real-time data to drive computational models. Additionally, in the case of DTs, real-time data is often used to create virtual replicas of the physical system as it progresses through real-time. There is an increasing volume of literature on RtS and DT; however, the field of OR/MS is yet to coalesce on accepted definitions and conceptualisations. This has arguably led to the cascading usage of these terms. The objective of the paper is threefold: (1) distinguish between RtS and DT, (2) present RtS-DT conceptualisation in four dimensions, and (3) present methodological and technical insights on developing RtS with limited data. We argue that the evolution of conventional simulation models to fully-fledged hybrid DTs may necessitate a focus on a transitional stage; namely, RtS models primarily driven using historical distributions with limited real-time data feeds.

The version presented here may differ from the published version. If citing, you are advised to c... more The version presented here may differ from the published version. If citing, you are advised to consult the published version for pagination, volume/issue and date of publication

This paper provides a framework for conceptualising levels of open science and open working withi... more This paper provides a framework for conceptualising levels of open science and open working within computer modelling and simulation. We aim to support researchers to share their models and working so that others are free to use, reproduce, adapt and build upon, and re-share their work. We introduce a six level framework of increasing complexity: not open, open access, open artefacts, open models, open environment and open infrastructure. For each we provide practical advice on what aspects of open science researchers must consider, what options are available to them, and what challenges they will need to overcome. We illustrate our open science framework using a stylised discrete-event simulation model. All code used in this paper is available, cloud executable and reusable under an MIT license.

2021 Winter Simulation Conference (WSC), Dec 12, 2021

Intermediate care supports timely discharge from hospital for patients with complex healthcare ne... more Intermediate care supports timely discharge from hospital for patients with complex healthcare needs. The purpose of 'step-down' care is to enable patients to leave hospital as soon as medically fit, avoiding costly discharge delays and consequent risks to patient health and wellbeing. Determining optimal intermediate care capacity requires balancing costs to both acute hospital and community care providers. Too much community capacity results in underutilized resources and poor economic efficiency, while too little risks excessive hospital discharge delays. Application of discrete-time simulation shows that total costs across the acute-community interface can be minimized by identifying optimal community capacity in terms of the maximum number of patients for which home visits can be provided by the service. To our knowledge, this is the first simulation study to model the patient pathway from hospital discharge through to community visits. Simulation modeling has supported short-term resource planning in a major English healthcare system.

Zenodo (CERN European Organization for Nuclear Research), Mar 29, 2023

The freedom to run the program as you wish, for any purpose.

BMJ Open, Dec 1, 2022

Objectives To identify risk factors associated with prolonged length of hospital stay and staying... more Objectives To identify risk factors associated with prolonged length of hospital stay and staying in hospital longer than medically necessary following primary knee replacement surgery. Design Retrospective, longitudinal observational study. Setting Elective knee replacement surgeries between 2016 and 2019 were identified using routinely collected data from an NHS Trust in England. Participants There were 2295 knee replacement patients with complete data included in analysis. The mean age was 68 (SD 11) and 60% were female. Outcome measures We assessed a binary length of stay outcome (>7 days), a continuous length of stay outcome (≤30 days) and a binary measure of whether patients remained in hospital when they were medically fit for discharge. Results The mean length of stay was 5.0 days (SD 3.9), 15.4% of patients were in hospital for >7 days and 7.1% remained in hospital when they were medically fit for discharge. Longer length of stay was associated with older age (b=0.08, 95% CI 0.07 to 0.09), female sex (b=0.36, 95% CI 0.06 to 0.67), high deprivation (b=0.98, 95% CI 0.47 to 1.48) and more comorbidities (b=2.48, 95% CI 0.15 to 4.81). Remaining in hospital beyond being medically fit for discharge was associated with older age (OR=1.07, 95% CI 1.05 to 1.09), female sex (OR=1.71, 95% CI 1.19 to 2.47) and high deprivation (OR=2.27, 95% CI 1.27 to 4.06). Conclusions The regression models could be used to identify which patients are likely to occupy hospital beds for longer. This could be helpful in scheduling operations to aid hospital efficiency by planning these patients' operations for when the hospital is less busy.

Objectives: Discrete-event simulation is a widely used computational method in health services an... more Objectives: Discrete-event simulation is a widely used computational method in health services and health economic studies. This systematic scoping review investigates to what extent authors share computer models, and audits if sharing adheres to best practice. Data sources: The Web of Science, Scopus, PubMed, and ACM Digital Library databases were searched between 1st January 2019 till 31st December 2022.Eligibility criteria for selecting studies: Cost-effectiveness, Health service research and methodology studies in a health context were included.Data extraction and synthesis: The data extraction and best practice audit were performed by two reviewers. We developed best practice audit criteria based on the Turing Way and other published reproducibility guides.Main outcomes and measures: We measured the proportion of literature that shared models; we report analyses by publication type, year of publication, Covid-19 application; and free and open source versus commercial software. ...

ABSTRACTObjectivesTo develop a simulation model to support orthopaedic elective capacity planning... more ABSTRACTObjectivesTo develop a simulation model to support orthopaedic elective capacity planning.MethodsAn open-source, generalisable discrete-event simulation was developed, including a web-based application. The model used anonymised patient records between 2016-2019 of elective orthopaedic procedures from an NHS Trust in England. In this paper, it is used to investigate scenarios including resourcing (beds and theatres) and productivity (lengths-of-stay, delayed discharges, theatre activity) to support planning for meeting new NHS targets aimed at reducing elective orthopaedic surgical backlogs in a proposed ring fenced orthopaedic surgical facility. The simulation is interactive and intended for use by health service planners and clinicians.ResultsA higher number of beds (65-70) than the proposed number (40 beds) will be required if lengths-of-stay and delayed discharge rates remain unchanged. Reducing lengths-of-stay in line with national benchmarks reduces bed utilisation to ...

Methods or approaches from disciplines outside of OR Modeling and Simulation (M&S) can potentiall... more Methods or approaches from disciplines outside of OR Modeling and Simulation (M&S) can potentially increase the functionality of simulation models. In healthcare research, where simulation models are commonly used, we see few applications of models that can easily be deployed by other researchers or by healthcare stakeholders. Models are treated as disposable artifacts, developed to deliver a set of results for stakeholders or for publication. By utilising approaches from software engineering, M&S researchers can develop models that are intended to be deployed for re-use. We propose one potential solution to deploying free and open source simulations using containerisation with continuous integration. A container provides a self-contained environment that encapsulates the model and all its required dependencies including the operating system, software, and packages. This overcomes a significant barrier to sharing models developed in open source software, which is dependency manageme...

Proceedings of SW21 The OR Society Simulation Workshop, Mar 27, 2023

Proceedings of SW21 The OR Society Simulation Workshop, Mar 27, 2023

Real-time Simulation (RtS) and Digital Twins (DT) are terms generally associated with hybrid mode... more Real-time Simulation (RtS) and Digital Twins (DT) are terms generally associated with hybrid models that use real-time data to drive computational models. Additionally, in the case of DTs, real-time data is often used to create virtual replicas of the physical system as it progresses through real-time. There is an increasing volume of literature on RtS and DT; however, the field of OR/MS is yet to coalesce on accepted definitions and conceptualisations. This has arguably led to the cascading usage of these terms. The objective of the paper is threefold: (1) distinguish between RtS and DT, (2) present RtS-DT conceptualisation in four dimensions, and (3) present methodological and technical insights on developing RtS with limited data. We argue that the evolution of conventional simulation models to fully-fledged hybrid DTs may necessitate a focus on a transitional stage; namely, RtS models primarily driven using historical distributions with limited real-time data feeds.

Proceedings of SW21 The OR Society Simulation Workshop

Inadequate patient flow from hospitals into community care is often blamed for bed blockages in t... more Inadequate patient flow from hospitals into community care is often blamed for bed blockages in the acute setting. This is bad for patient experience and outcomes and has an upstream knock-on effect for Accident and Emergency performance and, in turn, ambulance offload delays and response times. Despite the large numbers of acute bed-days lost to delayed discharges and the ambition to expand home-based community care, there has been a deficit of modelling studies investigating the dynamics of this pathway and providing the relevant insights to service planners. Working closely with healthcare managers, this paper reports on the development and deployment of versatile simulation tools for modelling both the home-based and bedded community step-down pathways, known as 'Discharge to Assess' or D2A in England's NHS. Developed in open source 'R', these tools offer scalable solutions for exploring different scenarios relating to demand, capacity and patient length of stay.

BMJ Open, Dec 1, 2022

Objectives To identify risk factors associated with prolonged length of hospital stay and staying... more Objectives To identify risk factors associated with prolonged length of hospital stay and staying in hospital longer than medically necessary following primary knee replacement surgery. Design Retrospective, longitudinal observational study. Setting Elective knee replacement surgeries between 2016 and 2019 were identified using routinely collected data from an NHS Trust in England. Participants There were 2295 knee replacement patients with complete data included in analysis. The mean age was 68 (SD 11) and 60% were female. Outcome measures We assessed a binary length of stay outcome (>7 days), a continuous length of stay outcome (≤30 days) and a binary measure of whether patients remained in hospital when they were medically fit for discharge. Results The mean length of stay was 5.0 days (SD 3.9), 15.4% of patients were in hospital for >7 days and 7.1% remained in hospital when they were medically fit for discharge. Longer length of stay was associated with older age (b=0.08, 95% CI 0.07 to 0.09), female sex (b=0.36, 95% CI 0.06 to 0.67), high deprivation (b=0.98, 95% CI 0.47 to 1.48) and more comorbidities (b=2.48, 95% CI 0.15 to 4.81). Remaining in hospital beyond being medically fit for discharge was associated with older age (OR=1.07, 95% CI 1.05 to 1.09), female sex (OR=1.71, 95% CI 1.19 to 2.47) and high deprivation (OR=2.27, 95% CI 1.27 to 4.06). Conclusions The regression models could be used to identify which patients are likely to occupy hospital beds for longer. This could be helpful in scheduling operations to aid hospital efficiency by planning these patients' operations for when the hospital is less busy.