ABSTRACTBackgroundThere were between 84,891 and 113,139 all-cause excess deaths in the United States (US) from February 1st to 25th May 2020. These deaths are widely attributed directly and indirectly to the COVID-19 pandemic. This surge in death necessitates a matched health system response to relieve serious health related suffering at the end of life (EoL) and achieve a dignified death, through timely and appropriate expertise, medication and equipment. Identifying the human and material resource needed relies on modelling resource and understanding anticipated surges in demand.MethodsA Discrete Event Simulation model designed in collaboration with health service funders, health providers, clinicians and modellers in the South West of England was created to estimate the resources required during the COVID-19 pandemic to care for deaths from COVID-19 in the community for a geographical area of nearly 1 million people. While our analysis focused on the UK setting, the model is flexible to changes in demand and setting.ResultsThe model predicts that a mean of 11.97 hours (0.18 hours Standard Error (SE), up to a max of 28 hours) of additional community nurse time, up to 33 hours of care assistant time (mean 9.17 hours, 0.23 hours SE), and up to 30 hours additional care from care assistant night-sits (mean of 5.74 hours per day, 0.22 hours SE) will be required per day as a result of out of hospital COVID-19 deaths. Specialist palliative care demand is predicted to increase up to 19 hours per day (mean of 9.32 hours per day, 0.12 hours SE). An additional 286 anticipatory medicine bundles or ‘just in case’ prescriptions per month will be necessary to alleviate physical symptoms at the EoL care for patients with COVID-19: an average additional 10.21 bundles (0.06 SE) of anticipatory medication per day. An average additional 9.35 syringe pumps (0.11 SE) could be needed to be in use per day (between 1 and 20 syringe pumps).ConclusionModelling provides essential data to prepare, plan and deliver a palliative care pandemic response tailored to local work patterns and resource. The analysis for a large region in the South West of England shows the significant additional physical and human resource required to relieve suffering at the EoL as part of a pandemic response.Why Was This Study Done?The resource required for the relief of suffering at the EoL in the community setting has been poorly described. The stark mortality resulting from the COVID-19 pandemic has highlighted the essential requirement to better understand the demand and available supply of EoL resource to prepare, plan and deliver a palliative care pandemic response.What Did the Researchers Do and Find?This manuscript describes the first open access model to describe EoL resource need during COVID-19 and presents an analysis based on a UK population of nearly 1 million people. The model identified a large increase in need for staff time, including registered community nurses, health care assistants and specialist palliative care nurses and doctors, as well as pressure on resources including syringe pumps and anticipatory medication (such as opioids) used at the EoL for symptom relief from breathlessness and delirium.What Do These Findings Mean?The model findings are critical in planning for a second wave of COVID-19. The open-access nature of the model allows researchers to tailor their analysis to low and middle income or high-income settings worldwide. The model ensures that EoL care is not an afterthought in pandemic planning, but an opportunity to ensure that the relief of suffering at the EoL is available to all.

OBJECTIVES: This feasibility study aimed to model in silico the current healthcare system for patients triaged to a primary care disposition following a call to National Health Service (NHS) 111 and determine the effect of reconfiguring the healthcare system to ensure a timely primary care service contact. DESIGN: Discrete event simulation. SETTING: Single English NHS 111 call centre in Yorkshire. PARTICIPANTS: Callers registered with a Bradford general practitioner who contacted the NHS 111 service in 2021 and were triaged to a primary care disposition. PRIMARY AND SECONDARY OUTCOME MEASURES: Face validity of conceptual model. Comparison between real and simulated data for quarterly counts (and 95% CIs) for patient contact with emergency ambulance (999), 111, and primary and secondary care services. Mean difference and 95% CIs in healthcare system usage between simulations and difference in mean proportion of avoidable admissions for callers who presented to an emergency department (ED). RESULTS: the simulation of the current system estimated that there would be 39 283 (95% CI 39 237 to 39 328) primary care contacts, 2042 (95% CI 2032 to 2051) 999 calls and 1120 (95% CI 1114 to 1127) avoidable ED attendances. Modifying the model to ensure a timely primary care response resulted in a mean percentage increase of 196.1% (95% CI 192.2% to 199.9%) in primary care contacts, and a mean percentage decrease of 78.0% (95% CI 69.8% to 86.2%) in 999 calls and 88.1% (95% CI 81.7% to 94.5%) in ED attendances. Avoidable ED attendances reduced by a mean of -26 (95% CI -35 to -17). CONCLUSION: in this simulated study, ensuring timely contact with a primary care service would lead to a significant reduction in 999 and 111 calls, and ED attendances (although not avoidable ED attendance). However, this is likely to be impractical given the need to almost double current primary care service provision. Further economic and qualitative research is needed to determine whether this intervention would be cost-effective and acceptable to both patients and primary care clinicians.

OBJECTIVES: the WHO estimates that the COVID-19 pandemic has led to more than 1.3 million deaths (1 377 395) globally (as of November 2020). This surge in death necessitates identification of resource needs and relies on modelling resource and understanding anticipated surges in demand. Our aim was to develop a generic computer model that could estimate resources required for end-of-life (EoL) care delivery during the pandemic. SETTING: a discrete event simulation model was developed and used to estimate resourcing needs for a geographical area in the South West of England. While our analysis focused on the UK setting, the model is flexible to changes in demand and setting. PARTICIPANTS: We used the model to estimate resourcing needs for a population of around 1 million people. PRIMARY AND SECONDARY OUTCOME MEASURES: the model predicts the per-day 'staff' and 'stuff' resourcing required to meet a given level of incoming EoL care activity. RESULTS: a mean of 11.97 hours of additional community nurse time, up to 33 hours of care assistant time and up to 30 hours additional care from care assistant night sits will be required per day as a result of out of hospital COVID-19 deaths based on the model prediction. Specialist palliative care demand is predicted to increase up to 19 hours per day. An additional 286 anticipatory medicine bundles per month will be necessary to alleviate physical symptoms at the EoL care for patients with COVID-19: an average additional 10.21 bundles of anticipatory medication per day. An average additional 9.35 syringe pumps could be needed to be in use per day. CONCLUSIONS: the analysis for a large region in the South West of England shows the significant additional physical and human resource required to relieve suffering at the EoL as part of a pandemic response.

Background/Aims Urgent care centres provide a broad range of services in comparison to minor injury units. In order to establish new urgent care centres, the Sustainability and Transformation Partnership in Cornwall aimed to identify the optimal number and location for these centres, which could then help to reduce the volume of patients attending emergency departments. Methods a computer model that calculated average and maximum travel times, along with number of attendances, for over 4000 potential urgent care centre geographic configurations, was developed. The model predicted that establishing five urgent care centres would significantly minimise travel times for patients across the county. The model also predicted the locations for these centres that would minimise average travel times. Results the results from the model were used to directly inform a decision made by the Sustainability and Transformation Partnership. Conclusion the first urgent care centres in Cornwall, at Treliske, Bodmin Community Hospital and West Cornwall Hospital, were established in 2018. The urgent care centre in West Cornwall is now accepting patients; the two other sites are still under construction.

Objective: to develop a simulation model to identify key bottlenecks in the bladder cancer pathway at Royal Cornwall Hospital and predict the impact of potential changes to reduce these delays. Materials and methods: the diagnosis and treatment of muscle-invasive bladder cancer can suffer numerous delays, which can significantly affect patient outcomes. We developed a discrete event computer simulation model of the flow of patients through the bladder cancer pathway at the hospital, using anonymised patient records from 2014 and 2015. The changes tested in the model were for patients suspected to have muscle-invasive disease on flexible cystoscopy. Those patients were ‘fast-tracked’ to receive their transurethral resection of bladder tumour (TURBT) treatment using operating slots kept free for these patients. A staging computed tomography scan was booked in the haematuria clinic. Pathology requests were marked as 48 hour turnaround. The nurse specialist would then speak to the patient whilst they were on the ward following their TURBT to give information about their ongoing treatment and provide support. Results: the model predicted that if the changes were implemented, delays in the system could be reduced by around 5 weeks. The changes were implemented, and analysis of 3 months of the data post-implementation shows that the average time in the system was reduced by 5 weeks. The environment created by the changes in the pathway improved referral to treatment times in both muscle-invasive and non-muscle-invasive groups. Conclusion: the simulation model proved an invaluable tool for facilitating the implementation of changes. Simple changes to the pathway led to significant reductions in delays for bladder cancer patients at Royal Cornwall Hospital. Level of evidence: Not applicable for this cohort study.

ObjectiveWe sought to develop a simulation modelling method to help better understand the complex interplay of factors that lead to people with type 2 diabetes and asthma not taking all of their medication as prescribed when faced with multiple medications (polypharmacy).Research design and methodsIn collaboration with polypharmacy patients, general practitioners, pharmacists and polypharmacy researchers, we developed a map of factors that directly and indirectly affect somebody’s decision to take their medication as prescribed when faced with multiple type 2 diabetes and asthma medications. We then translated these behavioural influences into logical rules using data from the literature and developed a proof-of-concept agent-based simulation model that captures the medicine-taking behaviours of those with type 2 diabetes and asthma taking multiple medications and which predicts both the clinical effectiveness and rates of adherence for different combinations of medications.ConclusionsThe model we have developed could be used as a prescription support tool or a way of estimating medicine-taking behaviour in cost-effectiveness analyses.

Introduction: Demonstration of cost-effectiveness is an established hurdle for new treatments and technologies. However, evidence synthesis, including simulation modelling, can be very difficult in the absence of good quality research that addresses pertinent questions, and people with rare conditions may have to forego the best available treatments. We illustrate this point with regard to the current choice between intravitreal ranibizumab, verteporfin photodynamic therapy (VPDT) or combinations of these (combination therapy) for polypoidal choroidal vasculopathy. Methods: We developed a Markov model to simulate equivalent cohorts of 65-year-old patients over a lifetime horizon. We obtained costs from the NHS national tariff, and utility values based on unilateral visual function deterioration. We carried out deterministic and probabilistic sensitivity analyses to investigate the sensitivity of the results to uncertainty in the model parameters. Results: Our model predicts that both VPDT and combination therapy offer cost savings but lower clinical efficacy over a lifetime horizon at δ81 165 and δ14 826 per quality-adjusted life year (QALY) respectively. VPDT monotherapy has a 99% chance of cost-effectiveness at a willingness to pay of δ30 000 per QALY gained. Combination therapy has a low (29%) probability of cost-effectiveness, however, this is heavily dependent on the modelled incidence of haemorrhagic adverse events. Conclusion: Based on the results of our model, VPDT might be commissioned according to a strict decision rule interpretation. The outcome regarding combination therapy is uncertain. These conclusions are dependent on the available evidence. There is considerable modelling and parameter uncertainty, which needs to be urgently addressed.

Demand for district nursing services is increasing significantly. With increasing economic pressures, services are struggling to meet increases in demand, and are looking to become more proactive in planning for future demand. Traditional quantitative forecasting methods have limited use, because of the complexity of inter-linking factors that potentially drive demand for community services. Qualitative system dynamics approaches can be useful to model the complex interplay of causal factors leading to an effect, such as increased demand for services, and identify particular areas of concern for future focus. We ran a facilitated qualitative system dynamics workshop with representatives working across community nursing services in Cornwall. The generated models identified 7 key areas of concern that could be significantly contributing to demand for district nursing services. We outline the identified problem areas in this paper, and discuss potential recommendations to reduce their effects based on causal links identified in the models.

Ambulance demand in South West England is increasing year-on-year, but the driving forces behind such increases are poorly understood. We developed a system dynamics model to simulate the factors that influence a call being made for an ambulance. We used data from the South West Ambulance Service NHS Foundation Trust (SWAST), the Office of National Statistics (ONS) and quantitative relationship data in both national and international literature to parameterise the model. We compared predicted ambulance demand over 12 months in the base case model with scenarios in which each influencing factor was removed in turn. The model predicts that the prevalence of regular falls among older people most influences the level of demand for ambulances. The model also predicts that the number of users of adult mental health services could be a significant contributor to ambulance demand. Additional focus on, and investment in, falls prevention strategies could help to significantly alleviate increasing levels of demand for ambulance services in South West England. Additionally, efforts to understand why those with mental health needs tend to use ambulances more than those without such needs could also be beneficial.

BACKGROUND: Keratoconus is a progressive degenerative corneal disorder of children and young adults that is traditionally managed by refractive error correction, with corneal transplantation reserved for the most severe cases. UVA collagen crosslinking is a novel procedure that aims to prevent disease progression, currently being considered for use in the UK NHS. We assess whether it might be a cost-effective alternative to standard management for patients with progressive keratoconus. METHODS: We constructed a Markov model in which we estimated disease progression from prospective follow-up studies, derived costs derived from the NHS National Tariff, and calculated utilities from linear regression models of visual acuity in the better-seeing eye. We performed deterministic and probabilistic sensitivity analyses to assess the impact of possible variations in the model parameters. RESULTS: Collagen crosslinking is cost effective compared with standard management at an incremental cost of £ 3174 per QALY in the base case. Deterministic sensitivity analysis shows that this could rise above £ 33,263 per QALY if the duration of treatment efficacy is limited to 5 years. Other model parameters are not decision significant. Collagen crosslinking is cost effective in 85% of simulations at a willingness-to-pay threshold of £ 30,000 per QALY. CONCLUSION: UVA collagen crosslinking is very likely to be cost effective, compared with standard management, for the treatment of progressive keratoconus. However, further research to explore its efficacy beyond 5 years is desirable.

Typically, fractured neck of femur patients admitted to an acute hospital are discharged to a community hospital for a period of rehabilitation after their treatment. However, there is concern that this might unnecessarily extend the total period of hospitalisation for these patients. Using data from a local acute hospital, we used discrete event simulation to predict the practicability of fractured neck of femur patients remaining in an acute hospital for their entire superspell (the overall length of stay across hospitals). We tested scenarios in which patient superspell duration was shortened, as well as a scenario in which no reduction in superspell length was observed. The model predicts that - even assuming that the superspell of fractured neck of femur patients could be significantly reduced - bed occupancy levels at the acute hospital would increase to operationally infeasible levels. Therefore, it is unlikely that fractured neck of femur patients could remain in a typical acute hospital unless there were sufficient increases in available resources.

Geographic modelling techniques provide a means of optimising the location of services, or understanding the potential impact of geographic service reconfigurations. In response to commissioner queries, we assessed the potential impact on patient travel time and attendances of the closure of four minor injury units (MIUs) in a locality of South West England. We used the MPMileCharter add-in for Microsoft MapPoint and the attendance records of 90252 minor injury unit patients to calculate car travel time data to the units in the locality. We then built a geographic model of the existing configuration of MIUs in Microsoft Excel, and used 'what if' analysis to determine the potential impact of the proposed closures. The model predicted that if the four MIUs were closed, there would be only a trivial increase in average travel time across all patients, but a significant increase of around 20 minutes per patient for those whose nearest unit was closed. The model also predicted that the closure of one of the MIUs could lead to significant increased demand at the walk-in centre located at the acute hospital. Using these results, the local commissioners decided to close only three of the four units.

A Markov model was developed to predict the outcomes and cost-effectiveness of bevacizumab compared to macular laser therapy for diabetes patients with clinically significant macular oedema (CSMO). This study used outcome data from a randomised controlled trial, utility data and health states from a ranibizumab health technology assessment, and costs from the UK national tariff. A total of 37.73% of patients treated with bevacizumab in the model had a visual acuity of at least 76 Early Treatment Diabetic Retinopathy Study Research Group (ETDRS) letters after four years, compared with 4.09% of laser therapy patients. Only 0.11% of bevacizumab patients were blind after four years compared with 6.45% of laser therapy patients. However, with an incremental cost-effectiveness ratio of £51,182, we predict that bevacizumab would not be cost-effective compared to laser therapy because of the influence of the NHS national tariff costs for monitoring patients and administering bevacizumab, and the inability of the EQ-5D measure to capture the impact of sensory deprivation on quality of life sufficiently. This study recommends significant caution when interpreting the results of cost-effectiveness analyses of interventions that involve vision-related interventions.

The authors produced a seasonalised forecast using a linear regression trendline to predict the level of demand for ophthalmology services at Royal Devon and Exeter hospital between 2013 and 2017. The model predicts an average annual increase in demand of 9.92%, but a significant proportion of this predicted increased demand is for glaucoma services. Given the historical patterns of demand observed in the data, it is possible that the increases in demand for glaucoma services have arisen because of dramatically increased referral rates from community optometrists, following the publication by the National Institute for Clinical Excellence (NICE) of clinical guidelines on the diagnosis and management of glaucoma and ocular hypertension (NICE, 2009). As this patient cohort may be best served by assessment outside of secondary care, we would encourage other hospital managers and analysts to produce similar forecasts and consider alternative pathways of care for this patient group.

OBJECTIVE: in the U.K. people with diabetes are typically screened for retinopathy annually. However, diabetic retinopathy sometimes has a slow progression rate. We developed a simulation model to predict the likely impact of screening patients with type 2 diabetes, who have not been diagnosed with diabetic retinopathy, every 2 years rather than annually. We aimed to assess whether or not such a policy would increase the proportion of patients who developed retinopathy-mediated vision loss compared with the current policy, along with the potential cost savings that could be achieved. RESEARCH DESIGN AND METHODS: We developed a model that simulates the progression of retinopathy in type 2 diabetic patients, and the screening of these patients, to predict rates of retinopathy-mediated vision loss. We populated the model with data obtained from a National Health Service Foundation Trust. We generated comparative 15-year forecasts to assess the differences between the current and proposed screening policies. RESULTS the simulation model predicts that implementing a 2-year screening interval for type 2 diabetic patients without evidence of diabetic retinopathy does not increase their risk of vision loss. Furthermore, we predict that this policy could reduce screening costs by ~25%. CONCLUSIONS: Screening people with type 2 diabetes, who have not yet developed retinopathy, every 2 years, rather than annually, is a safe and cost-effective strategy. Our findings support those of other studies, and we therefore recommend a review of the current National Institute for Health and Clinical Excellence (NICE) guidelines for diabetic retinopathy screening implemented in the U.K.