Assessing the impact of COVID-19 measures on COPD management and patients: A simulation-based decision support tool for COPD services in the UK

© 2022 The Author(s) or their employer(s). Published by BMJ. This is an open access article under the CC BY-NC-ND licence, https://creativecommons.org/licenses/by-nc-nd/4.0/Objectives To develop a computer-based decision support tool (DST) for key decision makers to safely explore the impact on chronic obstructive pulmonary disease (COPD) care of service changes driven by restrictions to prevent the spread of COVID-19.  Design The DST is powered by discrete event simulation which captures the entire patient pathway. To estimate the number of COPD admissions under different scenario settings, a regression model was developed and embedded into the tool. The tool can generate a wide range of patient-related and service-related outputs. Thus, the likely impact of possible changes (eg, COVID-19 restrictions and pandemic scenarios) on patients with COPD and care can be estimated.  Setting COPD services (including outpatient and inpatient departments) at a major provider in central London.  Results Four different scenarios (reflecting the UK government's Plan A, Plan B and Plan C in addition to a benchmark scenario) were run for 1 year. 856, 616 and 484 face-to-face appointments (among 1226 clinic visits) are expected in Plans A, B and C, respectively. Clinic visit quality in Plan A is found to be marginally better than in Plans B and C. Under coronavirus restrictions, lung function tests decreased more than 80% in Plan C as compared with Plan A. Fewer COPD exacerbation-related admissions were seen (284.1 Plan C vs 395.1 in the benchmark) associated with stricter restrictions. Although the results indicate that fewer quality-adjusted life years (in terms of COPD management) would be lost during more severe restrictions, the wider impact on physical and mental health must also be established.  Conclusions This DST will enable COPD services to examine how the latest developments in care delivery and management might impact their service during and beyond the COVID-19 pandemic, and in the event of future pandemics.Peer reviewe

Examining HIV and Tuberculosis Using a Decision Support Systems Computer Simulation Model: The Case of the Russian Federation

The aim of this paper is to describe the development and use of a computer simulation model that can be used as a Decision Support System (DSS) to tackle the critical public health issues of the chronic diseases, HIV and HIV related Tuberculosis in the Russian Federation. The model was developed to enable health officials and decision makers to determine the impact of policies to control the chronic diseases spread in an area of Russia. This area, like many others in Russia and elsewhere, have recently witnessed an explosion of HIV infections and a worrying spread of the Multi Drug Resistant form of Tuberculosis (MDRTB). The conclusions drawn is that a high population coverage with Highly Active Anti Retroviral Treatment (HAART) (75% or higher), allied with high MDRTB cure rates, reduces cumulative deaths by 60%, with limited impact below this level. The contributions that this research offers are the development of a simulation model that can be applied as a DSS by public health officials and managers in order to inform policy making. By doing so, ways of best controlling the spread of HIV and MDRTB and reduce the mortality rate from these serious public health threats is provided

Using system dynamics modelling to assess the economic efficiency of innovations in the public sector - a systematic review.

BackgroundDecision-makers for public policy are increasingly utilising systems approaches such as system dynamics (SD) modelling, which test alternative interventions or policies for their potential impact while accounting for complexity. These approaches, however, have not consistently included an economic efficiency analysis dimension. This systematic review aims to examine how, and in what ways, system dynamics modelling approaches incorporate economic efficiency analyses to inform decision-making on innovations (improvements in products, services, or processes) in the public sector, with a particular interest in health.Methods and findingsRelevant studies (n = 29) were identified through a systematic search and screening of four electronic databases and backward citation search, and analysed for key characteristics and themes related to the analytical methods applied. Economic efficiency analysis approaches within SD broadly fell into two categories: as embedded sub-models or as cost calculations based on the outputs of the SD model. Embdedded sub-models within a dynamic SD framework can reveal a clear allocation of costs and benefits to periods of time, whereas cost calculations based on the SD model outputs can be useful for high-level resource allocation decisions.ConclusionsThis systematic review reveals that SD modelling is not currently used to its full potential to evaluate the technical or allocative efficiency of public sector innovations, particularly in health. The limited reporting on the experience or methodological challenges of applying allocated efficiency analyses with SD, particularly with dynamic embedded models, hampers common learning lessons to draw from and build on. Further application and comprehensive reporting of this approach would be welcome to develop the methodology further

A Discrete Event Simulation model to evaluate the treatment pathways of patients with Cataract in the United Kingdom

Background The number of people affected by cataract in the United Kingdom (UK) is growing rapidly due to ageing population. As the only way to treat cataract is through surgery, there is a high demand for this type of surgery and figures indicate that it is the most performed type of surgery in the UK. The National Health Service (NHS), which provides free of charge care in the UK, is under huge financial pressure due to budget austerity in the last decade. As the number of people affected by the disease is expected to grow significantly in coming years, the aim of this study is to evaluate whether the introduction of new processes and medical technologies will enable cataract services to cope with the demand within the NHS funding constraints. Methods We developed a Discrete Event Simulation model representing the cataract services pathways at Leicester Royal Infirmary Hospital. The model was inputted with data from national and local sources as well as from a surgery demand forecasting model developed in the study. The model was verified and validated with the participation of the cataract services clinical and management teams. Results Four scenarios involving increased number of surgeries per half-day surgery theatre slot were simulated. Results indicate that the total number of surgeries per year could be increased by 40% at no extra cost. However, the rate of improvement decreases for increased number of surgeries per half-day surgery theatre slot due to a higher number of cancelled surgeries. Productivity is expected to improve as the total number of doctors and nurses hours will increase by 5 and 12% respectively. However, non-human resources such as pre-surgery rooms and post-surgery recovery chairs are under-utilized across all scenarios. Conclusions Using new processes and medical technologies for cataract surgery is a promising way to deal with the expected higher demand especially as this could be achieved with limited impact on costs. Non-human resources capacity need to be evenly levelled across the surgery pathway to improve their utilisation. The performance of cataract services could be improved by better communication with and proactive management of patients.Peer reviewedFinal Published versio

System Dynamics modelling to formulate policy interventions to optimise antibiotic prescribing in hospitals

© 2020 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Multiple strategies have been used in the National Health System (NHS) in England to reduce inappropriate antibiotic prescribing and consumption in order to tackle antimicrobial resistance. These strategies have included, among others, restricting dispensing, introduction of prescribing guidelines, use of clinical audit, and performance reviews as well as strategies aimed at changing the prescribing behaviour of clinicians. However, behavioural interventions have had limited effect in optimising doctors’ antibiotic prescribing practices. This study examines the determinants of decision-making for antibiotic prescribing in hospitals in the NHS. A system dynamics model was constructed to capture structural and behavioural influences to simulate doctors’ prescribing practices. Data from the literature, patient records, healthcare professional interviews and survey responses were used to parameterise the model. The scenario simulation shows maximum improvements in guideline compliance are achieved when compliance among senior staff is increased, combined with fast laboratory turnaround of blood cultures, and microbiologist review. Improving guideline compliance of junior staff alone has limited impact. This first use of system dynamics modelling to study antibiotic prescribing decision-making demonstrates the applicability of the methodology for design and evaluation of future policies and interventions.Peer reviewe

Adoption and use of e-government services in the Abu Dhabi police force : a qualitative study

Information and Communication Technologies (ICTs) are becoming increasingly prevalent in peoples’ daily lives due to the presence of e-government. This research-in-progress paper aims to identify and understand factors affecting the diffusion, adoption and use of e-services in a public sector organisation, in this case, Abu Dhabi Police Force (ADPF) in the United Arab Emirates (UAE). A qualitative approach involving 39 participants’ interviews was used in this study. The questions used in the interviews were based on a conceptual framework that applied certain constructs taken from Diffusion of Innovations Theory (DOI), Technology Acceptance Model (TAM) and e-Commerce’s Trustworthiness models. The research study results show that age, education, position within an organisation and the job that an individual is involved with inhibit or encourage the use and adoption of e-services. The contributions from this research are anticipated to be a better understanding of the diffusion, adoption and use of e-services in the UAE region. For industry the findings offer a diverse perspective as they provide some information on the impacts of e-services in public sector organisations of Abu Dhabi. Policymakers, particularly in the UAE and developing countries can learn of the impacts of e-government efforts in the public sector of Abu Dhabi.Final Published versio

Impact of coordination on post-earthquake last mile relief distribution operations in India

© 2023 Inderscience Enterprises Ltd. This is the accepted manuscript version of an article which has been published in final form at https://dx.doi.org/10.1504/IJEM.2023.132390The operations to deliver relief to disaster affected populations are complex requiring careful planning, execution, and coordination especially during the Last Mile Relief Distribution (LMRD) phase. This paper investigates the impact of coordination on LMRD performance in the context of India, one of the most affected countries in the world by natural disasters. The research was carried out in two phases. First, qualitative interviews were conducted with Indian government, national, and international non-governmental organizations involved in disaster relief operations in the country. Second, an Agent-Based Simulation model representing Indian LMRD operations was developed and used to evaluate the impact of three coordination scenarios on the total level of inventory in distribution centers (TLIDC) and the logistics chain responsiveness during the 45 days period following an earthquake. Findings indicate that better coordination can reduce TLIDC by up to 16% and improves responsiveness by up to 13%. The practical implications of these findings are discussed.Peer reviewe

Modelling length of stay and patient flows : Methodological case studies from the UK neonatal care services

Copyright and all rights therein are retained by the authors. All persons copying this information are expected to adhere to the terms and conditions invoked by each author's copyright. These works may not be re-posted without the explicit permission of the copyright holdersThe number of babies needing neonatal care is increasing due mainly to technological and therapeutic advances. These advances have implied a decreasing neonatal mortality rate for low birth weight infants and also a falling incidence of preterm stillbirth. Given the structural changes in the National Health Service in England, coupled with recession and capacity constraints, the neonatal system is facing some serious challenges, such as nurse shortages and the lack of cots, which could inevitably impact neonates length of stay, and the performance of the system as a whole. These constraints have forced neonatal managers to better understand their organisation and operations in order to optimize their systems. As a result, we have developed three unique methodologies based on length of stay modelling, physical patient pathways, and system dynamics modelling. This paper evaluates these techniques applied to neonatal services in London, and showcases their usefulness and implications in practice, particularly focusing on patient flow to determine major drivers of the system, which could reduce inefficiencies, improve patient experience, and reduce cos

A decision support tool with health economic modelling for better management of DVT patients

© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License. https://creativecommons.org/licenses/by/4.0/Background: Responding to the increasing demand for Deep Vein Thrombosis (DVT) treatment in the United Kingdom (UK) at times of limited budgets and resources is a great challenge for decision-makers. Therefore, there is a need to find innovative policies, which improve operational efficiency and achieve the best value for money for patients. This study aims to develop a Decision Support Tool (DST) that assesses the impact of implementing new DVT patients’ management and care policies aiming at improving efficiency, reducing costs, and enhancing value for money. Methods: With the involvement of stakeholders from a number of DVT services in the UK, we developed a DST combining discrete event simulation (DES) for DVT pathways and the Socio Technical Allocation of Resources (STAR) approach, an agile health economics technique. The model was inputted with data from the literature, local datasets from DVT services, and interviews conducted with DVT specialists. The tool was validated and verified by various stakeholders and two policies, namely shifting more patients to community services (CSs) and increasing the usage of the Novel Oral Anticoagulant (NOAC) drug were selected for testing on the model. Results: Sixteen possible scenarios were run on the model for a period of 5 years and generated treatment activity, human resources, costing, and value for money outputs. The results indicated that hospital visits can be reduced by up to 50%. Human resources’ usage can be greatly lowered driven mainly by offering NOAC treatment to more patients. Also, combining both policies can lead to cost savings of up to 50%. The STAR method, which considers both service and patient perspectives produced findings that implementing both policies provide a significantly higher value for money compared to the situation when neither is applied. Conclusions: The combination of DES and STAR can help decision-makers determine the interventions that have the highest benefits from service providers' and patients’ perspectives. This is important given the mismatch between care demand and resources and the resulting need for improving operational and economic outcomes. The DST tool has the potential to inform policymaking in DVT services in the UK to improve performance.Peer reviewe