How the health-seeking behaviour of pregnant women affects neonatal outcomes: findings of system dynamics modelling in Pakistan

Background: Limited studies have explored how health-seeking behaviour during pregnancy through to delivery affect neonatal outcomes. We modelled health-seeking behaviour across urban and rural settings in Pakistan, where poor neonatal outcomes persist with wide disparities. Methods and findings: A system dynamics model was developed and parameterised. Following validation tests, the model was used to determine neonatal mortality for pregnant women considering their decisions to access, refuse and switch antenatal care services in four provider sectors: public, private, traditional and charitable. Four health-seeking scenarios were tested across different pregnancy trimesters. Health-seeking behaviour in different subgroups by geographical locations and social network effect was modelled. The largest reduction in neonatal mortality was achieved with antenatal care provided by skilled providers in public, private or charitable sectors, combined with the use of institutional delivery. Women’s social networks had strong influences on if, when and where to seek care. Interventions by Lady Health Workers had a minimal impact on health-seeking behaviour and neonatal outcomes after trimester 1. Optimal benefits were achieved for urban women when antenatal care was accessed within trimester 2, but for rural women within trimester 1. Antenatal care access delayed to trimester 3 had no protective impact on neonatal mortality. Conclusions: System dynamics modelling enables capturing the complexity of health-seeking behaviours and impact on outcomes, informing intervention design, implementation of targeted policies and uptake of services specific to urban/rural settings considering structural enablers/barriers to access, cultural contexts and strong social network influences

How the health-seeking behaviour of pregnant women affects neonatal outcomes: findings of System Dynamics modelling in Pakistan

Background: Limited studies have explored how health-seeking behaviour during pregnancy through to delivery affect neonatal outcomes. We modelled health-seeking behaviour across urban and rural settings in Pakistan, where poor neonatal outcomes persist with wide disparities. Methods and Findings: A System Dynamics model was developed and parameterised. Following validation tests, the model was used to determine neonatal mortality for pregnant women considering their decisions to access, refuse, and switch antenatal care services in four provider sectors: public, private, traditional, and charitable. Four health-seeking scenarios were tested across different pregnancy trimesters. Health-seeking behaviour in different sub-groups by geographic locations, and social network effect was modelled. The largest reduction in neonatal mortality was achieved with antenatal care provided by skilled providers in public, private or charitable sectors, combined with the use of institutional delivery. Women’s social networks had strong influences on if, when and where to seek care. Interventions by Lady Health Workers had a minimal impact on health-seeking behaviour and neonatal outcomes after Trimester 1. Optimal benefits were achieved for urban women when antenatal care was accessed within Trimester 2, but for rural women within Trimester 1. Antenatal care access delayed to Trimester 3 had no protective impact on neonatal mortality. Conclusions: System Dynamics modelling enables capturing complexity of health-seeking behaviours and impact on outcomes, informing: intervention design, implementation of targeted policies, and uptake of services specific to urban/rural settings considering structural enablers/barriers to access, cultural contexts, and strong social network influences

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

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

Background Decision-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 findings Relevant 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. Conclusions This 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

Investigating infection management and antimicrobial stewardship in surgery: a qualitative study from India and South Africa

Appendix A. Supplementary data: The following is the Supplementary data to this article: Multimedia component 1. Avalable online at https://www.sciencedirect.com/science/article/pii/S1198743X20307734#appsec1 .This work was supported by the Economic and Social Science Research Council (ESRC) and the National Institute for Health Research, UK Department of Health (HPRU-2012-10047) in partnership with Public Health England. This study is part of the ASPIRES project (Antibiotic use across Surgical Pathways—Investigating, Redesigning and Evaluating Systems) (https://www.imperial.ac.uk/arc/aspires/). ASPIRES aims to address antimicrobial resistance and improve clinical outcomes optimizing antibiotic usage along surgical pathways. The support of ESRC as part of the Antimicrobial Cross Council initiative supported by the seven UK research councils, and also the support of the Global Challenges Research Fund, is gratefully acknowledged

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

Investigating infection management and antimicrobial stewardship in surgery: a qualitative study from India and South Africa

OBJECTIVES: To investigate the drivers for infection management and antimicrobial stewardship (AMS) across high-infection-risk surgical pathways. METHODS: A qualitative study-ethnographic observation of clinical practices, patient case studies, and face-to-face interviews with healthcare professionals (HCPs) and patients-was conducted across cardiovascular and thoracic and gastrointestinal surgical pathways in South Africa (SA) and India. Aided by Nvivo 11 software, data were coded and analysed until saturation was reached. The multiple modes of enquiry enabled cross-validation and triangulation of findings. RESULTS: Between July 2018 and August 2019, data were gathered from 190 hours of non-participant observations (138 India, 72 SA), interviews with HCPs (44 India, 61 SA), patients (six India, eight SA), and case studies (four India, two SA). Across the surgical pathway, multiple barriers impede effective infection management and AMS. The existing implicit roles of HCPs (including nurses and senior surgeons) are overlooked as interventions target junior doctors, bypassing the opportunity for integrating infection-related care across the surgical team. Critically, the ownership of decisions remains with the operating surgeons, and entrenched hierarchies restrict the inclusion of other HCPs in decision-making. The structural foundations to enable staff to change their behaviours and participate in infection-related surgical care are lacking. CONCLUSIONS: Identifying the implicit existing HCP roles in infection management is critical and will facilitate the development of effective and transparent processes across the surgical team for optimized care. Applying a framework approach that includes nurse leadership, empowering pharmacists and engaging surgical leads, is essential for integrated AMS and infection-related care

Factors controlling the performance of horizontal flow roughing filters

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