Imperial College London

Dheeya Rizmie

Business School

Visiting Researcher
 
 
 
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dheeya.rizmie14

 
 
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455BACE ExtensionSouth Kensington Campus

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Summary

 

Publications

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11 results found

DAeth J, Ghosal S, Grimm F, Haw D, Koca E, Lau K, Liu H, Moret S, Rizmie D, Smith P, Forchini G, Miraldo M, Wiesemann Wet al., 2023, Optimal hospital care scheduling during the SARS-CoV-2 pandemic, Management Science, Vol: 69, Pages: 5923-5947, ISSN: 0025-1909

The COVID-19 pandemic has seen dramatic demand surges for hospital care that have placed a severe strain on health systems worldwide. As a result, policy makers are faced with the challenge of managing scarce hospital capacity so as to reduce the backlog of non-COVID patients whilst maintaining the ability to respond to any potential future increases in demand for COVID care. In this paper, we propose a nation-wide prioritization scheme that models each individual patient as a dynamic program whose states encode the patient’s health and treatment condition, whose actions describe the available treatment options, whose transition probabilities characterize the stochastic evolution of the patient’s health and whose rewards encode the contribution to the overall objectives of the health system. The individual patients’ dynamic programs are coupled through constraints on the available resources, such as hospital beds, doctors and nurses. We show that the overall problem can be modeled as a grouped weakly coupled dynamic program for which we determine near-optimal solutions through a fluid approximation. Our case study for the National Health Service in England shows how years of life can be gained by prioritizing specific disease types over COVID patients, such as injury & poisoning, diseases of the respiratory system, diseases of the circulatory system, diseases of the digestive system and cancer.

Journal article

Rizmie D, de Preux L, Miraldo M, Atun Ret al., 2022, Impact of extreme temperatures on emergency hospital admissions by age and socio-economic deprivation in England: Evidence from six diseases, Social Science & Medicine, Vol: 308, Pages: 115193-115193, ISSN: 0277-9536

Climate change poses an unprecedented challenge to population health and health systems’ resilience, with increasing fluctuations in extreme temperatures through pressures on hospital capacity. While earlier studies have estimated morbidity attributable to hot or cold weather across cities, we provide the first large-scale, population-wide assessment of extreme temperatures on inequalities in excess emergency hospital admissions in England. We used the universe of emergency hospital admissions between 2001 and 2012 combined with meteorological data to exploit daily variation in temperature experienced by hospitals (N = 29,371,084). We used a distributed lag model with multiple fixed-effects, controlling for seasonal factors, to examine hospitalisation effects across temperature-sensitive diseases, and further heterogeneous impacts across age and deprivation. We identified larger hospitalisation impacts associated with extreme cold temperatures than with extreme hot temperatures. The less extreme temperatures produce admission patterns like their extreme counterparts, but at lower magnitudes. Results also showed an increase in admissions with extreme temperatures that were more prominent among older and socioeconomically-deprived populations - particularly across admissions for metabolic diseases and injuries.

Journal article

de Preux L, Rizmie D, 2021, How is the healthcare sector dealing with climate change?, Economics Observatory, Vol: 2021

Healthcare systems face a growing burden from environmental hazards like air pollution and extreme weather events. As major contributors to greenhouse gas emissions, they are also seeking to reduce their carbon footprint.

Journal article

DAeth J, Ghosal S, Grimm F, Haw D, Koca E, Lau K, Moret S, Rizmie D, Deeny S, Perez-Guzman P, Ferguson N, Hauck K, Smith P, Forchini G, Wiesemann W, Miraldo Met al., 2021, Optimal national prioritization policies for hospital care during the SARS-CoV-2 pandemic, Nature Computational Science, Vol: 1, Pages: 521-531, ISSN: 2662-8457

In response to unprecedent surges in the demand for hospital care during the SARS-CoV-2 pandemic, health systems have prioritized COVID patients to life-saving hospital care to the detriment of other patients. In contrast to these ad hoc policies, we develop a linear programming framework to optimally schedule elective procedures and allocate hospital beds among all planned and emergency patients to minimize years of life lost. Leveraging a large dataset of administrative patient medical records, we apply our framework to the National Health System in England and show that an extra 50,750-5,891,608 years of life can be gained in comparison to prioritization policies that reflect those implemented during the pandemic. Significant health gains are observed for neoplasms, diseases of the digestive system, and injuries & poisoning. Our open-source framework provides a computationally efficient approximation of a large-scale discrete optimization problem that can be applied globally to support national-level care prioritization policies.

Journal article

Christen P, D'Aeth J, Lochen A, McCabe R, Rizmie D, Schmit N, Nayagam S, Miraldo M, Aylin P, Bottle A, Perez Guzman P, Donnelly C, Ghani A, Ferguson N, White P, Hauck Ket al., 2021, The J-IDEA pandemic planner: a framework for implementing hospital provision interventions during the COVID-19 pandemic, Medical Care, Vol: 59, Pages: 371-378, ISSN: 0025-7079

Background : Planning for extreme surges in demand for hospital care of patientsrequiring urgent life-saving treatment for COVID-19, whilst retaining capacity for otheremergency conditions, is one of the most challenging tasks faced by healthcareproviders and policymakers during the pandemic. Health systems must be wellpreparedto cope with large and sudden changes in demand by implementinginterventions to ensure adequate access to care. We developed the first planning toolfor the COVID-19 pandemic to account for how hospital provision interventions (suchas cancelling elective surgery, setting up field hospitals, or hiring retired staff) will affectthe capacity of hospitals to provide life-saving care.Methods : We conducted a review of interventions implemented or considered in 12 European countries in March-April 2020, an evaluation of their impact on capacity, anda review of key parameters in the care of COVID-19 patients. This information wasused to develop a planner capable of estimating the impact of specific interventions ondoctors, nurses, beds and respiratory support equipment. We applied this to ascenario-based case study of one intervention, the set-up of field hospitals in England,under varying levels of COVID-19 patients.Results : The J-IDEA pandemic planner is a hospital planning tool that allows hospitaladministrators, policymakers and other decision-makers to calculate the amount ofcapacity in terms of beds, staff and crucial medical equipment obtained byimplementing the interventions. Flexible assumptions on baseline capacity, the numberof hospitalisations, staff-to-beds ratios, and staff absences due to COVID-19 make theplanner adaptable to multiple settings. The results of the case study show that whilefield hospitals alleviate the burden on the number of beds available, this intervention isfutile unless the deficit of critical care nurses is addressed first.Discussion : The tool supports decision-makers in delivering a fast and effectiveresponse to

Journal article

D'Aeth J, Ghosal S, Grimm F, Haw D, Koca E, Lau K, Moret S, Rizmie D, Deeny S, Perez Guzman P, Ferguson N, Hauck K, Smith P, Wiesemann W, Forchini G, Miraldo Met al., 2020, Report 40: Optimal scheduling rules for elective care to minimize years of life lost during the SARS-CoV-2 pandemic: an application to England

SummaryCountries have deployed a wide range of policies to prioritize patients to hospital care to address unprecedent surges in demand during the course of the pandemic. Those policies included postponing planned hospital care for non-emergency cases and rationing critical care.We develop a model to optimally schedule elective hospitalizations and allocate hospital general and critical care beds to planned and emergency patients in England during the pandemic. We apply the model to NHS England data and show that optimized scheduling leads to lower years of life lost and costs than policies that reflect those implemented in England during the pandemic. Overall across all disease areas the model enables an extra 50,750 - 5,891,608 years of life gained when compared to standard policies, depending on the scenarios. Especially large gains in years of life are seen for neoplasms, diseases of the digestive system, and injuries & poisoning.

Report

McCabe R, Schmit N, Christen P, D'Aeth J, Løchen A, Rizmie D, Nayagam AS, Miraldo M, Aylin P, Bottle R, Perez-Guzman PN, Ghani A, Ferguson N, White P, Hauck Ket al., 2020, Adapting hospital capacity to meet changing demands during the COVID-19 pandemic, BMC Medicine, Vol: 18, Pages: 1-12, ISSN: 1741-7015

BackgroundTo calculate hospital surge capacity, achieved via hospital provision interventions implemented for the emergency treatment of coronavirus disease 2019 (COVID-19) and other patients through March to May 2020; to evaluate the conditions for admitting patients for elective surgery under varying admission levels of COVID-19 patients.MethodsWe analysed National Health Service (NHS) datasets and literature reviews to estimate hospital care capacity before the pandemic (pre-pandemic baseline) and to quantify the impact of interventions (cancellation of elective surgery, field hospitals, use of private hospitals, deployment of former medical staff and deployment of newly qualified medical staff) for treatment of adult COVID-19 patients, focusing on general and acute (G&A) and critical care (CC) beds, staff and ventilators.ResultsNHS England would not have had sufficient capacity to treat all COVID-19 and other patients in March and April 2020 without the hospital provision interventions, which alleviated significant shortfalls in CC nurses, CC and G&A beds and CC junior doctors. All elective surgery can be conducted at normal pre-pandemic levels provided the other interventions are sustained, but only if the daily number of COVID-19 patients occupying CC beds is not greater than 1550 in the whole of England. If the other interventions are not maintained, then elective surgery can only be conducted if the number of COVID-19 patients occupying CC beds is not greater than 320. However, there is greater national capacity to treat G&A patients: without interventions, it takes almost 10,000 G&A COVID-19 patients before any G&A elective patients would be unable to be accommodated.ConclusionsUnless COVID-19 hospitalisations drop to low levels, there is a continued need to enhance critical care capacity in England with field hospitals, use of private hospitals or deployment of former and newly qualified medical staff to allow some or all elective surge

Journal article

McCabe R, Schmit N, Christen P, D'Aeth J, Lochen A, Rizmie D, Nayagam AS, Miraldo M, Aylin P, Bottle R, Perez Guzman PN, Ghani A, Ferguson N, White PJ, Hauck Ket al., 2020, Report 27 Adapting hospital capacity to meet changing demands during the COVID-19 pandemic

To meet the growing demand for hospital care due to the COVID-19 pandemic, England implemented a range of hospital provision interventions including the procurement of equipment, the establishment of additional hospital facilities and the redeployment of staff and other resources. Additionally, to further release capacity across England’s National Health Service (NHS), elective surgery was cancelled in March 2020, leading to a backlog of patients requiring care. This created a pressure on the NHS to reintroduce elective procedures, which urgently needs to be addressed. Population-level measures implemented in March and April 2020 reduced transmission of SARS-CoV-2, prompting a gradual decline in the demand for hospital care by COVID-19 patients after the peak in mid-April. Planning capacity to bring back routine procedures for non-COVID-19 patients whilst maintaining the ability to respond to any potential future increases in demand for COVID-19 care is the challenge currently faced by healthcare planners.In this report, we aim to calculate hospital capacity for emergency treatment of COVID-19 and other patients during the pandemic surge in April and May 2020; to evaluate the increase in capacity achieved via five interventions (cancellation of elective surgery, field hospitals, use of private hospitals, and deployment of former and newly qualified medical staff); and to determine how to re-introduce elective surgery considering continued demand from COVID-19 patients. We do this by modelling the supply of acute NHS hospital care, considering different capacity scenarios, namely capacity before the pandemic (baseline scenario) and after the implementation of capacity expansion interventions that impact available general and acute (G&A) and critical care (CC) beds, staff and ventilators. Demand for hospital care is accounted for in terms of non-COVID-19 and COVID-19 patients. Our results suggest that NHS England would not have had sufficient daily capacity

Report

Christen P, D'Aeth J, Lochen A, McCabe R, Rizmie D, Schmit N, Nayagam AS, Miraldo M, White P, Aylin P, Bottle R, Perez Guzman PN, Donnelly C, Ghani A, Ferguson N, Hauck Ket al., 2020, Report 15: Strengthening hospital capacity for the COVID-19 pandemic

Planning for extreme surges in demand for hospital care of patients requiring urgent life-saving treatment for COVID-19, and other conditions, is one of the most challenging tasks facing healthcare commissioners and care providers during the pandemic. Due to uncertainty in expected patient numbers requiring care, as well as evolving needs day by day, planning hospital capacity is challenging. Health systems that are well prepared for the pandemic can better cope with large and sudden changes in demand by implementing strategies to ensure adequate access to care. Thereby the burden of the pandemic can be mitigated, and many lives saved. This report presents the J-IDEA pandemic planner, a hospital planning tool to calculate how much capacity in terms of beds, staff and ventilators is obtained by implementing healthcare provision interventions affecting the management of patient care in hospitals. We show how to assess baseline capacity, and then calculate how much capacity is gained by various healthcare interventions using impact estimates that are generated as part of this study. Interventions are informed by a rapid review of policy decisions implemented or being considered in 12 European countries over the past few months , an evaluation of the impact of the interventions on capacity using a variety of research methods, and by a review of key parameters in the care of COVID-19 patients.The J-IDEA planner is publicly available, interactive and adaptable to different and changing circumstances and newly emerging evidence. The planner estimates the additional number of beds, medical staff and crucial medical equipment obtained under various healthcare interventions using flexible inputs on assumptions of existing capacities, the number of hospitalisations, beds-to-staff ratios, and staff absences due to COVID-19. A detailed user guide accompanies the planner. The planner was developed rapidly and has limitations which we will address in future iterations. It support

Report

Rizmie D, Miraldo M, Atun R, de Preux Let al., 2019, The effect of extreme temperature on emergency admissions across vulnerable populations in England: an observational study, Lancet Public Health Science 2019 Conference, Publisher: Elsevier, Pages: S7-S7

BackgroundClimate change poses an unfamiliar challenge to population health and health-systems resilience. Although previous studies have estimated morbidity attributable to heat or cold across cities, we provide, to our knowledge, the first large-scale, population-wide assessment of the effect of extreme temperatures on excess emergency admissions in England and among vulnerable populations, who could be disproportionately affected.MethodsIn this observational study, we combined all daily inpatient admissions during 2001–12 in England with meteorological data using inverse distance weighting. We exploited random daily variation in temperature experienced by hospitals and a 30-day lag period, using a distributed lag model with multiple fixed-effects controlling for seasonal factors, to examine interaction effects across diseases with age and the indices of multiple deprivation.FindingsWe analysed 29 371 084 emergency admissions. A day with temperature above 30°C was associated with 3·5 more admissions per hospital (SE 0·45), relative to a 10–15°C day. This increased to 14·1 excess admissions per hospital (SE 5·56) over the following 30 days, generating 786 excess admissions across England per heatwave day. A day under –5°C generated 3·8 more admissions per hospital (SE 0·33), or 966 excess admissions across England. This increased to 62·3 admissions per hospital (SE 4·83) over the following 30 days. These effects were heterogeneous across age and deprivation level. Populations older than 74 years were up to 8 times more affected by extreme temperatures. Individuals living in low-employment and low-income areas were 2–10 times more likely to be admitted during a temperature shock. These results were statistically significant (p<0·0001) and passed several robustness and falsification tests.InterpretationTo our knowledge, this is the first study to determine heterogene

Conference paper

de Preux LB, Rizmie D, 2018, Beyond financial efficiency to support environmental sustainability in economic evaluations, Future Healthcare Journal, Vol: 5, Pages: 103-107, ISSN: 2055-3323

The healthcare sector is one of the largest pollutersin the United Kingdom, accounting for 25% of total emissions of carbon dioxideof the public sector.Ironically,it is the healthcare sector itself that is primarily affected by any deterioration in the environmentaffectingindividuals’ health and their demand for healthcare.Therefore thehealthcare sector is a direct beneficiary of its own steps towards sustainabilityand is more and more viewed as the one who should lead the change. In this article, we first review the concepts of financial and environmental sustainability.Second,we discuss the existing evidence of sustainablechanges withinthis sector. Third, we propose a simple adaptation of the classic cost-effectivenessanalysis to incorporate carbon footprinting to account for these external costs. We illustrate our method using the case of in-centre versushome haemodialysis. We conclude that home dialysis is always a preferable alternative to in-centre treatment. Finally, we discuss the limitations of our approach, and the future research agenda.

Journal article

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