Development and application of simulation modelling for orthopaedic elective resource planning in England.

OBJECTIVES: This study aimed to develop a simulation model to support orthopaedic elective capacity planning. METHODS: An open-source, generalisable discrete-event simulation was developed, including a web-based application. The model used anonymised patient records between 2016 and 2019 of elective orthopaedic procedures from a National Health Service (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 and 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. RESULTS: A 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 an estimated 60%, allowing for additional theatre activity such as weekend working. Further, reducing the proportion of patients with a delayed discharge by 75% reduces bed utilisation to below 40%, even with weekend working. A range of other scenarios can also be investigated directly by NHS planners using the interactive web app. CONCLUSIONS: The simulation model is intended to support capacity planning of orthopaedic elective services by identifying a balance of capacity across theatres and beds and predicting the impact of productivity measures on capacity requirements. It is applicable beyond the study site and can be adapted for other specialties.

Protocol for a pragmatic cluster randomised controlled trial assessing the clinical effectiveness and cost-effectiveness of Electronic RIsk-assessment for CAncer for patients in general practice (ERICA).

INTRODUCTION: The UK has worse cancer outcomes than most comparable countries, with a large contribution attributed to diagnostic delay. Electronic risk assessment tools (eRATs) have been developed to identify primary care patients with a ≥2% risk of cancer using features recorded in the electronic record. METHODS AND ANALYSIS: This is a pragmatic cluster randomised controlled trial in English primary care. Individual general practices will be randomised in a 1:1 ratio to intervention (provision of eRATs for six common cancer sites) or to usual care. The primary outcome is cancer stage at diagnosis, dichotomised to stage 1 or 2 (early) or stage 3 or 4 (advanced) for these six cancers, assessed from National Cancer Registry data. Secondary outcomes include stage at diagnosis for a further six cancers without eRATs, use of urgent referral cancer pathways, total practice cancer diagnoses, routes to cancer diagnosis and 30-day and 1-year cancer survival. Economic and process evaluations will be performed along with service delivery modelling. The primary analysis explores the proportion of patients with early-stage cancer at diagnosis. The sample size calculation used an OR of 0.8 for a cancer being diagnosed at an advanced stage in the intervention arm compared with the control arm, equating to an absolute reduction of 4.8% as an incidence-weighted figure across the six cancers. This requires 530 practices overall, with the intervention active from April 2022 for 2 years. ETHICS AND DISSEMINATION: The trial has approval from London City and East Research Ethics Committee, reference number 19/LO/0615; protocol version 5.0, 9 May 2022. It is sponsored by the University of Exeter. Dissemination will be by journal publication, conferences, use of appropriate social media and direct sharing with cancer policymakers. TRIAL REGISTRATION NUMBER: ISRCTN22560297.

The False Economy of Seeking to Eliminate Delayed Transfers of Care: Some Lessons from Queueing Theory.

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.

Kailo: a systemic approach to addressing the social determinants of young people's mental health and wellbeing at the local level.

The mental health and wellbeing of children and young people is deteriorating. It is increasingly recognised that mental health is a systemic issue, with a wide range of contributing and interacting factors. However, the vast majority of attention and resources are focused on the identification and treatment of mental health disorders, with relatively scant attention on the social determinants of mental health and wellbeing and investment in preventative approaches. Furthermore, there is little attention on how the social determinants manifest or may be influenced at the local level, impeding the design of contextually nuanced preventative approaches. This paper describes a major research and design initiative called Kailo that aims to support the design and implementation of local and contextually nuanced preventative strategies to improve children's and young people's mental health and wellbeing. The Kailo Framework involves structured engagement with a wide range of local partners and stakeholders - including young people, community partners, practitioners and local system leaders - to better understand local systemic influences and support programmes of youth-centred and evidence-informed co-design, prototyping and testing. It is hypothesised that integrating different sources of knowledge, experience, insight and evidence will result in better embedded, more sustainable and more impactful strategies that address the social determinants of young people's mental health and wellbeing at the local level.

Identification of risk factors associated with prolonged hospital stay following primary knee replacement surgery: a retrospective, longitudinal observational study.

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.

Optimising the balance of acute and intermediate care capacity for the complex discharge pathway: Computer modelling study during COVID-19 recovery in England.

OBJECTIVES: While there has been significant research on the pressures facing acute hospitals during the COVID-19 pandemic, there has been less interest in downstream community services which have also been challenged in meeting demand. This study aimed to estimate the theoretical cost-optimal capacity requirement for 'step down' intermediate care services within a major healthcare system in England, at a time when considerable uncertainty remained regarding vaccination uptake and the easing of societal restrictions. METHODS: Demand for intermediate care was projected using an epidemiological model (for COVID-19 demand) and regressing upon public mobility (for non-COVID-19 demand). These were inputted to a computer simulation model of patient flow from acute discharge readiness to bedded and home-based Discharge to Assess (D2A) intermediate care services. Cost-optimal capacity was defined as that which yielded the lowest total cost of intermediate care provision and corresponding acute discharge delays. RESULTS: Increased intermediate care capacity is likely to bring about lower system-level costs, with the additional D2A investment more than offset by substantial reductions in costly acute discharge delays (leading also to improved patient outcome and experience). Results suggest that completely eliminating acute 'bed blocking' is unlikely economical (requiring large amounts of downstream capacity), and that health systems should instead target an appropriate tolerance based upon the specific characteristics of the pathway. CONCLUSIONS: Computer modelling can be a valuable asset for determining optimal capacity allocation along the complex care pathway. With results supporting a Business Case for increased downstream capacity, this study demonstrates how modelling can be applied in practice and provides a blueprint for use alongside the freely-available model code.

Estimates of regional infectivity of COVID-19 in the United Kingdom following imposition of social distancing measures.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reproduction number has become an essential parameter for monitoring disease transmission across settings and guiding interventions. The UK published weekly estimates of the reproduction number in the UK starting in May 2020 which are formed from multiple independent estimates. In this paper, we describe methods used to estimate the time-varying SARS-CoV-2 reproduction number for the UK. We used multiple data sources and estimated a serial interval distribution from published studies. We describe regional variability and how estimates evolved during the early phases of the outbreak, until the relaxing of social distancing measures began to be introduced in early July. Our analysis is able to guide localized control and provides a longitudinal example of applying these methods over long timescales. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

Factors influencing digital review of pathology test results in an inpatient setting: a cross-sectional study.

BACKGROUND: Delay or failure to view test results in a hospital setting can lead to delayed diagnosis, risk of patient harm, and represents inefficiency. Factors influencing this were investigated to identify how timeliness and completeness of test review could be improved through an evidence-based redesign of the use of clinical test review software. METHODS: A cross-section of all abnormal hematology and biochemistry results which were published on a digital test review platform over a 3-year period were investigated. The time it took for clinicians to view these results, and the results that were not viewed within 30 days, were analyzed relative to time of the week, the detailed type of test, and an indicator of patient record data quality. RESULTS: The majority of results were viewed within 90 min, and 93.9% of these results viewed on the digital platform within 30 days. There was significant variation in results review throughout the week, shown to be due to an interplay between technical and clinical workflow factors. Routine results were less likely to be reviewed, as were those with patient record data quality issues. CONCLUSION: The evidence suggests that test result review would be improved by stream-lining access to the result platform, differentiating between urgent and routine results, improving handover of responsibility for result review, and improving search for temporary patient records. Altering the timing of phlebotomy rounds and a review of the appropriateness of routine test requests at the weekend may also improve result review rates.

How can consultant-led childbirth care at time of delivery be maximised? A modelling study.

OBJECTIVE: The Royal College of Obstetricians and Gynaecologists has advised that consolidation of birth centres, where reasonable, into birth centres of at least 6000 admissions per year should allow constant consultant presence. Currently, only 17% of mothers attend such birth centres. The objective of this work was to examine the feasibility of consolidation of birth centres, from the perspectives of birth centre size and travel times for mothers. DESIGN: Computer-based optimisation. SETTING: Hospital-based births. POPULATION OR SAMPLE: 1.91 million admissions in 2014-2016. METHODS: A multiple-objective genetic algorithm. MAIN OUTCOME MEASURES: Travel time for mothers and size of birth centres. RESULTS: Currently, with 161 birth centres, 17% of women attend a birth centre with at least 6000 admissions per year. We estimate that 95% of women have a travel time of 30 min or less. An example scenario, with 100 birth centres, could provide 75% of care in birth centres with at least 6000 admissions per year, with 95% of women travelling 35 min or less to their closest birth centre. Planning at local level leads to reduced ability to meet admission and travel time targets. CONCLUSIONS: While it seems unrealistic to have all births in birth centres with at least 6000 admissions per year, it appears realistic to increase the percentage of mothers attending this type of birth centre from 17% to about 75% while maintaining reasonable travel times. Planning at a local level leads to suboptimal solutions.

The heterogeneous causal effects of neonatal care: a model of endogenous demand for multiple treatment options based on geographical access to care.

Neonatal units in the UK are organised into three levels, from highest Neonatal Intensive Care Unit (NICU), to Local Neonatal Unit (LNU) to lowest Special Care Unit (SCU). We model the endogenous treatment selection of neonatal care unit of birth to estimate the average and marginal treatment effects of different neonatal designations on infant mortality, length of stay and hospital costs. We use prognostic factors, survival and hospital care use data on all preterm births in England for 2014-2015, supplemented by national reimbursement tariffs and instrumental variables of travel time from a geographic information system. The data were consistent with a model of demand for preterm birth care driven by physical access. In-hospital mortality of infants born before 32 weeks was 8.5% overall, and 1.2 (95% CI: -0.7, 3.2) percentage points lower for live births in hospitals with NICU or SCU compared to those with an LNU according to instrumental variable estimates. We find imprecise differences in average total hospital costs by unit designation, with positive unobserved selection of those with higher unexplained absolute and incremental costs into NICU. Our results suggest a limited scope for improvement in infant mortality by increasing in-utero transfers based on unit designation alone.

Case finding and therapy for chronic viral hepatitis in primary care (HepFREE): a cluster-randomised controlled trial.

BACKGROUND: The prevalence of viral hepatitis (hepatitis B virus and hepatitis C virus) in migrants is higher than among the general population in many high-income countries. We aimed to determine whether incentivising and supporting primary-care physicians in areas with a high density of migrants increases the numbers of adult migrants screened for viral hepatitis. METHODS: HepFREE was a multicentre, open, cluster-randomised controlled trial in general practices in areas of the UK with a high density of migrants (Bradford, Yorkshire, and northeast and southeast London). Participants were adult patients (aged 18 years or older) in primary care, who had been identified as a first or second generation migrant from a high-risk country. General practices were randomly assigned (1:2:2:2:2) to an opportunistic screening (control) group or to one of four targeted screening (interventional) groups: standard (ie, hospital-based) care and a standard invitation letter; standard care and an enhanced invitation letter; community care and a standard invitation letter; or community care and an enhanced invitation letter. In control screening, general practitioners (GPs) were given a teaching session on viral hepatitis and were asked to test all registered migrants. In the intervention, GPs were paid a nominal sum for setting up searches of records, reimbursed for signed consent forms, and supported by a dedicated clinician. Patients who were eligible for testing and tested positive for viral hepatitis in the intervention groups were eligible to enrol in a second embedded trial of community versus hospital based care. The primary outcomes were the proportion of patients eligible for screening, the proportion of those eligible who were sent an invitation letter in the intervention groups, the uptake of viral hepatitis screening (in the intention-to-treat population), the proportion of patients who tested positive for viral hepatitis, the proportion who complied with treatment, and the cost-effectiveness of the intervention. This trial is registered with ISRCTN, number ISRCTN54828633. FINDINGS: Recruitment and testing ran from Oct 31, 2013, to Feb 4, 2017, and each practice recruited for 18 consecutive calendar months. We approached 70 general practices in three areas with a high density of migrants, of which 63 general practices agreed to participate. Five practices withdrew and 58 practices were randomly assigned: eight to control and 50 to an intervention. In control practices, 26 046 (38·4%) of 67 820 patients who were initially registered were eligible for testing, as were 152 321 (43·3%) of 351 710 patients in the interventional groups in London and Bradford. Of 51 773 randomly selected eligible patients in the intervention groups in London and Bradford, letters were sent to 43 585 (84·2%) patients. In the eight control general practices, screening was taken up by 543 (1·7%) of 31 738 eligible participants, which included 5692 newly registered patients. However, in the 50 general practices that used the intervention, screening was taken up by 11 386 (19·5%) of 58 512 eligible participants (including 6739 newly registered patients; incidence rate ratio 3·70, 95% CI 1·30-10·51; p=0·014) and this intervention was cost-effective. 720 (4·5%) of 15 844 patients who received a standard letter versus 1032 (3·7%) of 28 095 patients who received the enhanced letter were tested (0·70, 0·38-1·31; p=0·26). In the control group, 17 patients tested positive for viral hepatitis, as did 220 patients (one with a co-infection) in the intervention groups. In the embedded study, 220 patients were randomly assigned to either hospital-based care or community care; 80 (87·9%) of 91 patients in the hospital setting complied with treatment versus 105 (81·4%) of 129 patients in the community setting. The intervention was cost-effective at willingness to pay thresholds in excess of £8540. One serious adverse event (thyroiditis) was noted. INTERPRETATION: Screening migrants for viral hepatitis in primary care is effective if doctors are incentivised and supported. Community care is expensive and there is no evidence that this offers benefits in this setting or that bespoke invitation letters add value. We suggest that bespoke invitation letters should not be used, and we suggest that outreach, community-based services for migrants should not be developed. FUNDING: National Institute for Health Research.

Redesigning the diagnostic pathway for chest pain patients in emergency departments.

Patients presenting with chest pain at an emergency department in the United Kingdom receive troponin tests to assess the likelihood of an acute myocardial infarction (AMI). Until recently, serial testing with two blood samples separated by at least six hours was necessary in order to analyse the change in troponin levels over time. New high-sensitivity troponin tests, however, allow the inter-test time to be shortened from six to three hours. Recent evidence also suggests that the new generation of troponin tests can be used to rule out AMI on the basis of a single test if patients at low risk of AMI present with very low cardiac troponin levels more than three hours after onset of worst pain. This paper presents a discrete event simulation model to assess the likely impact on the number of hospital admissions if emergency departments adopt strategies for serial and single testing based on the use of high-sensitivity troponin. Data sets from acute trusts in the South West of England are used to quantify the resulting benefits.

A modelling tool for capacity planning in acute and community stroke services.

BACKGROUND: Mathematical capacity planning methods that can take account of variations in patient complexity, admission rates and delayed discharges have long been available, but their implementation in complex pathways such as stroke care remains limited. Instead simple average based estimates are commonplace. These methods often substantially underestimate capacity requirements. We analyse the capacity requirements for acute and community stroke services in a pathway with over 630 admissions per year. We sought to identify current capacity bottlenecks affecting patient flow, future capacity requirements in the presence of increased admissions, the impact of co-location and pooling of the acute and rehabilitation units and the impact of patient subgroups on capacity requirements. We contrast these results to the often used method of planning by average occupancy, often with arbitrary uplifts to cater for variability. METHODS: We developed a discrete-event simulation model using aggregate parameter values derived from routine administrative data on over 2000 anonymised admission and discharge timestamps. The model mimicked the flow of stroke, high risk TIA and complex neurological patients from admission to an acute ward through to community rehab and early supported discharge, and predicted the probability of admission delays. RESULTS: An increase from 10 to 14 acute beds reduces the number of patients experiencing a delay to the acute stroke unit from 1 in every 7 to 1 in 50. Co-location of the acute and rehabilitation units and pooling eight beds out of a total bed stock of 26 reduce the number of delayed acute admissions to 1 in every 29 and the number of delayed rehabilitation admissions to 1 in every 20. Planning by average occupancy would resulted in delays for one in every five patients in the acute stroke unit. CONCLUSIONS: Planning by average occupancy fails to provide appropriate reserve capacity to manage the variations seen in stroke pathways to desired service levels. An appropriate uplift from the average cannot be based simply on occupancy figures. Our method draws on long available, intuitive, but underused mathematical techniques for capacity planning. Implementation via simulation at our study hospital provided valuable decision support for planners to assess future bed numbers and organisation of the acute and rehabilitation services.

Systems modelling and simulation in health service design, delivery and decision making.

The ever increasing pressures to ensure the most efficient and effective use of limited health service resources will, over time, encourage policy makers to turn to system modelling solutions. Such techniques have been available for decades, but despite ample research which demonstrates potential, their application in health services to date is limited. This article surveys the breadth of approaches available to support delivery and design across many areas and levels of healthcare planning. A case study in emergency stroke care is presented as an exemplar of an impactful application of health system modelling. This is followed by a discussion of the key issues surrounding the application of these methods in health, what barriers need to be overcome to ensure more effective implementation, as well as likely developments in the future.

The 7th IMA international conference on quantitative modelling in the management of health and social care: IMA health 2013 special issue.

Health and social care systems are facing major challenges worldwide, due in part to changes in demography and advances in technology and in part to changes in the structure and organisation of care delivery. The IMA Health 2013 conference brought together health care managers, clinicians, management consultants, and mathematicians, operational and health service researchers, statisticians and health economists from across the world with a view to bridging the gap between the respective communities, to exploring recent developments and identifying opportunities for further research. The eight selected papers of this special issue have been grouped into two broad categories. First, there are five papers that report on studies conducted in or relevant to care provision within hospitals. The three remaining papers concern studies aimed at problems related to care provided outside the hospital including long-term care, community based care services and public health. A key learning point arising from these papers and the discussions that took place during the conference is that the systems modelling community need not only to focus their efforts in developing new and improving the performance of existing algorithms, but also in achieving better integration with qualitative research methods and with various relevant strands of the social sciences (ethnography, organisation behaviour etc.). In any case, collaborative projects which engage directly with those involved both in delivering and receiving health care is key if modelling is to make a difference in tackling the messy and complex problems of health and social care.