Publications
259 results found
Johnson R, Djaafara B, Haw D, et al., 2023, The societal value of SARS-CoV-2 booster vaccination in Indonesia, VACCINE, Vol: 41, Pages: 1885-1891, ISSN: 0264-410X
DAeth J, Ghosal S, Grimm F, et al., 2023, Optimal hospital care scheduling during the SARS-CoV-2 pandemic, Management Science, 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.
Haw DJ, Morgenstern C, Forchini G, et al., 2022, Data needs for integrated economic-epidemiological models of pandemic mitigation policies, Epidemics: the journal of infectious disease dynamics, Vol: 41, Pages: 1-9, ISSN: 1755-4365
The COVID-19 pandemic and the mitigation policies implemented in response toit have resulted in economic losses worldwide. Attempts to understand therelationship between economics and epidemiology has lead to a new generation ofintegrated mathematical models. The data needs for these models transcend thoseof the individual fields, especially where human interaction patterns areclosely linked with economic activity. In this article, we reflect uponmodelling efforts to date, discussing the data needs that they have identified,both for understanding the consequences of the pandemic and policy responses toit through analysis of historic data and for the further development of thisnew and exciting interdisciplinary field.
Haw D, Forchini G, Doohan P, et al., 2022, Optimizing social and economic activity while containing SARS-CoV-2 transmission using DAEDALUS, Nature Computational Science, Vol: 2, Pages: 223-233, ISSN: 2662-8457
To study the trade-off between economic, social and health outcomes in the management of a pandemic, DAEDALUS integrates a dynamic epidemiological model of SARS-CoV-2 transmission with a multi-sector economic model, reflecting sectoral heterogeneity in transmission and complex supply chains. The model identifies mitigation strategies that optimize economic production while constraining infections so that hospital capacity is not exceeded but allowing essential services, including much of the education sector, to remain active. The model differentiates closures by economic sector, keeping those sectors open that contribute little to transmission but much to economic output and those that produce essential services as intermediate or final consumption products. In an illustrative application to 63 sectors in the United Kingdom, the model achieves an economic gain of between £161 billion (24%) and £193 billion (29%) compared to a blanket lockdown of non-essential activities over six months. Although it has been designed for SARS-CoV-2, DAEDALUS is sufficiently flexible to be applicable to pandemics with different epidemiological characteristics.
Street A, Smith P, 2021, How can we make valid and useful comparisons of different health care systems?, HEALTH SERVICES RESEARCH, Vol: 56, Pages: 1299-1301, ISSN: 0017-9124
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- Citations: 1
DAeth J, Ghosal S, Grimm F, et 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.
McGuire F, Kreif N, Smith PC, 2021, The effect of distance on maternal institutional delivery choice: Evidence from Malawi, HEALTH ECONOMICS, Vol: 30, Pages: 2144-2167, ISSN: 1057-9230
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- Citations: 3
Anderson M, Pitchforth E, Asaria M, et al., 2021, LSE-Lancet Commission on the future of the NHS: re-laying the foundations for an equitable and efficient health and care service after COVID-19, The Lancet, Vol: 397, Pages: 1915-1978, ISSN: 0140-6736
Charlesworth A, Anderson M, Donaldson C, et al., 2021, What is the right level of spending needed for health and care in the UK?, LANCET, Vol: 397, Pages: 2012-2022, ISSN: 0140-6736
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- Citations: 8
D'Aeth J, Ghosal S, Grimm F, et 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.
Haw D, Christen P, Forchini G, et al., 2020, DAEDALUS: An economic-epidemiological model to optimize economic activity while containing the SARS-CoV-2 pandemic
Haw D, Forchini G, Christen P, et al., 2020, Report 35: How can we keep schools and universities open? Differentiating closures by economic sector to optimize social and economic activity while containing SARS-CoV-2 transmission
There is a trade-off between the education sector and other economic sectors in the control of SARS-Cov-2 transmission. Here we integrate a dynamic model of SARS-CoV-2 transmission with a 63-sector economic model reflecting sectoral heterogeneity in transmission and economic interdependence between sectors. We identify COVID-19 control strategies which optimize economic production while keeping schools and universities operational and constraining infections such that emergency hospital capacity is not exceeded. The model estimates an economic gain of between £163bn and £205bn for the United Kingdom compared to a blanket lockdown of non-essential activity over six months, depending on hospital capacity. Sectors identified as potential priorities for closure are contact-intensive and/or less economically productive.
Martin S, Siciliani L, Smith P, 2020, Socioeconomic inequalities in waiting times for primary care across ten OECD countries, SOCIAL SCIENCE & MEDICINE, Vol: 263, ISSN: 0277-9536
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- Citations: 7
Cylus J, Smith P, 2020, The economy of wellbeing: what is it and what are the implications for health?, BMJ-BRITISH MEDICAL JOURNAL, Vol: 369, ISSN: 0959-535X
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- Citations: 9
Moreno-Serra R, Hole A, Smith PC, 2020, A new approach to measuring health development: From national income toward health coverage (and beyond), Global Health Economics: Shaping Health Policy In Low- And Middle-income Countries, Pages: 239-262, ISBN: 9789813272361
This chapter proposes an alternative approach to identify and constraints in countries, based on indicators that are broader than national income and more relevant to assess the stage of national development in health. A conceptual framework of "health coverage" underpins the construction of sub-indices of national performance in the dimensions of access to care, financial risk protection in health and domestic financial constraints, which are then used to construct overall indices of national health development. Country rankings in the health development scale vary substantially when the conditions of access to care, financial protection and domestic capacity to finance the health system are considered, compared to conventional income rankings. Furthermore, the decomposition of our health development indices sheds light on important aspects for health policy, including the identification of cases where there is a need for external support to maintain and expand current health coverage levels, as well as preliminary insights into specific support modalities by donor agencies that may be more efficient to promote health development in a particular setting. This chapter also demonstrates how our proposed indices can inform policy decisions at a higher granularity level subject to the availability of subnational level data.
qin VM, McPake B, Raban M, et al., 2020, Rural and urban differences in health system performance among older Chinese adults: cross-sectional analysis of a national sample, BMC Health Services Research, Vol: 20, ISSN: 1472-6963
Background Despite improvement in health outcomes over the past few decades, china still experiences striking urban-rural health inequalities. There is limited research on the rural-urban differences in health system performance in China. Method We conducted a cross-sectional analysis to compare health system performance between rural and urban areas in five key domains of the health system: effectiveness, cost, access, patient-centredness and equity, using data from the WHO Study on Global AGEing and adult health (SAGE), China. Multiple logistic and linear regression models were used to assess the first four domains, adjusting for individual characteristics, and a relative index of inequality (RII) was used to measure the equity domain. Findings Compared to urban areas, rural areas had poorer performance in the management and control of hypertension and diabetes, with more than 50% lower odds of having breast (AOR= 0.44; 95% CI: 0.30, 0.64) and cervical cancer screening (AOR= 0.49; 95% CI: 0.29, 0.83). There was better performance in rural areas in the patient-centredness domain, with more than twice higher odds of getting prompt attention, respect, clarity of the communication with health provider and involvement in decision making of the treatment in inpatient care (AOR=2.56, 2.15, 2.28, 2.28). Although rural residents incurred relatively less out-of-pocket expenditures (OOPE) for outpatient and inpatient services than urban residents, they were more likely to incur catastrophic expenditures on health (AOR=1.30; 95% CI 1.16, 1.44). Wealth inequality was found in many indicators related to the effectiveness, costs and access domains in both rural and urban areas. Rural areas had greater inequalities in the management of hypertension and coverage of cervical cancer (RII=7.45 vs 1.64).ConclusionOur findings suggest that urban areas have achieved better prevention and management of non-communicable disease than rural areas, but access to healthcare was equivalent. A
Ochalek J, Manthalu G, Smith PC, 2020, Squaring the cube: Towards an operational model of optimal universal health coverage, JOURNAL OF HEALTH ECONOMICS, Vol: 70, ISSN: 0167-6296
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- Citations: 3
Isaranuwatchai W, Teerawattananon Y, Archer RA, et al., 2020, Prevention of non-communicable disease: best buys, wasted buys, and contestable buys, BMJ-BRITISH MEDICAL JOURNAL, Vol: 368, ISSN: 0959-535X
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- Citations: 13
Berman P, Moreno-Serra R, Hole A, et al., 2020, A New Approach to Measuring Health Development: From National Income Toward Health Coverage (and Beyond), World Scientific Series in Global Health Economics and Public Policy, Pages: 239-262
This chapter proposes an alternative approach to identify and constraints in countries, based on indicators that are broader than national income and more relevant to assess the stage of national development in health. A conceptual framework of "health coverage" underpins the construction of sub-indices of national performance in the dimensions of access to care, financial risk protection in health and domestic financial constraints, which are then used to construct overall indices of national health development. Country rankings in the health development scale vary substantially when the conditions of access to care, financial protection and domestic capacity to finance the health system are considered, compared to conventional income rankings. Furthermore, the decomposition of our health development indices sheds light on important aspects for health policy, including the identification of cases where there is a need for external support to maintain and expand current health coverage levels, as well as preliminary insights into specific support modalities by donor agencies that may be more efficient to promote health development in a particular setting. This chapter also demonstrates how our proposed indices can inform policy decisions at a higher granularity level subject to the availability of subnational level data.
McGuire F, Revill P, Twea P, et al., 2020, Allocating resources to support universal health coverage: development of a geographical funding formula in Malawi, BMJ GLOBAL HEALTH, Vol: 5, ISSN: 2059-7908
Jakab M, Smith P, 2019, 8. Cross-Sectoral Policies to Address Non-Communicable Diseases, Non-communicable Disease Prevention, Publisher: Open Book Publishers, Pages: 129-146
Quentin W, Eckhardt H, Smith P, 2019, "Pay for Quality'' (P4Q) as a quality strategy, Publisher: OXFORD UNIV PRESS, ISSN: 1101-1262
Gaudin S, Smith PC, Soucat A, et al., 2019, Common Goods for Health: Economic Rationale and Tools for Prioritization, HEALTH SYSTEMS & REFORM, Vol: 5, Pages: 280-292, ISSN: 2328-8604
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- Citations: 10
Moreno-Serra R, Anaya-Montes M, Smith PC, 2019, Potential determinants of health system efficiency: Evidence from Latin America and the Caribbean, PLOS ONE, Vol: 14, ISSN: 1932-6203
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- Citations: 16
Thomas R, Friebel R, Barker K, et al., 2019, Work and home productivity of people living with HIV in Zambia and South Africa, AIDS, Vol: 33, Pages: 1063-1071, ISSN: 0269-9370
Objective: To compare number of days lost to illness or accessing healthcare for HIV-positive and HIV-negative individuals working in the informal and formal sectors in South Africa and Zambia.Design: As part of the HPTN 071 (PopART) study, data on adults aged 18–44 years were gathered between in cross-sectional surveys of random general population samples in 21 communities in Zambia and South Africa. Data on the number of productive days lost in the last 3 months, laboratory-confirmed HIV status, labour force status, age, ethnicity, education, and recreational drug use was collected.Methods: Differences in productive days lost between HIV-negative and HIV-positive individuals (“excess productive days lost”) were estimated with negative binomial models, and results disaggregated for HIV-positive individuals after various durations on Anti-retroviral treatment (ART).Results: From samples of 19,330 respondents in Zambia and 18,004 respondents in South Africa, HIV-positive individuals lost more productive days to illness than HIV-negative individuals in both countries. HIV-positive individuals in Zambia lost 0.74 excess productive days (95%CI: 0.48–1.01; p < 0.001) to illness over a three-month period. HIV-positive in South Africa lost 0.13 excess days (95%CI: 0.04–0.23; p = 0.007). In Zambia, those on ART for less than one year lost most days, and those not on ART lost fewest days. In South Africa, results disaggregated by treatment duration were not statistically significant.Conclusions: There is a loss of work and home productivity associated with HIV, but it is lower than existing estimates for HIV-positive formal sector workers. The findings support policy makers in building an accurate investment case for HIV interventions.
Verguet S, Feldhaus I, Kwete XJ, et al., 2019, Health system modelling research: towards a whole-health-system perspective for identifying good value for money investments in health system strengthening, BMJ GLOBAL HEALTH, Vol: 4, ISSN: 2059-7908
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- Citations: 13
Mannion R, Goddard M, Smith PC, 2019, On the limitations and pitfalls o f performance measurement systems in health care, Quality in Health Care: Strategic Issues in Health Care Management, Pages: 158-169, ISBN: 9781138724198
Formal performance measurement systems are increasingly a prominent feature of health systems concerned with raising quality and containing costs. This chapter describes the rise of performance indicators in the NHS. It then examines the role of ‘hard’ and ‘soft information in assessing hospital performance and explores the possible unintended and adverse consequences associated with the use of performance indicators. A clear and dominant theme arising from our study is that hard information, used in isolation, is seen as an inadequate and sometimes misleading indicator of Trust performance. Regional office staff reported that they examined closely the hard financial information provided by individual Trusts in order to assess whether they are meeting their targets. Informal social networks should be valued in their own right as a form of ‘social capital’ which has been shown to be a vital lubricant of complex economic relationships. The chapter advocates a cautious approach to the use of performance indicators in the NHS.
Hauck K, Morton A, Chalkidou K, et al., 2019, How can we evaluate the cost-effectiveness of health system strengthening? A typology and illustrations, Social Science and Medicine, Vol: 220, Pages: 141-149, ISSN: 0277-9536
Health interventions often depend on a complex system of human and capital infrastructure that is shared with other interventions, in the form of service delivery platforms, such as healthcare facilities, hospitals, or community services. Most forms of health system strengthening seek to improve the efficiency or effectiveness of such delivery platforms. This paper presents a typology of ways in which health system strengthening can improve the economic efficiency of health services. Three types of health system strengthening are identified and modelled: (1) investment in the efficiency of an existing shared platform that generates positive benefits across a range of existing interventions; (2) relaxing a capacity constraint of an existing shared platform that inhibits the optimization of existing interventions; (3) providing an entirely new shared platform that supports a number of existing or new interventions. Theoretical models are illustrated with examples, and illustrate the importance of considering the portfolio of interventions using a platform, and not just piecemeal individual analysis of those interventions. They show how it is possible to extend principles of conventional cost-effectiveness analysis to identify an optimal balance between investing in health system strengthening and expenditure on specific interventions. The models developed in this paper provide a conceptual framework for evaluating the cost-effectiveness of investments in strengthening healthcare systems and, more broadly, shed light on the role that platforms play in promoting the cost-effectiveness of different interventions.
Cecchini M, Smith P, 2018, Assessing the dose-response relationship between number of office-based visits and hospitalizations for patients with type II diabetes using generalized propensity score matching, PLoS ONE, Vol: 13, ISSN: 1932-6203
BackgroundWhether inpatient services can be successfully substituted by office-based services has been debated for many decades, but the evidence is still inconclusive. This study aims to investigate the effect of office-based care on use and the expenditure for other healthcare services in patients with type II diabetes (T2D).MethodsA generalized propensity score matching approach was used on pooled Medical Expenditure Panel Survey (MEPS) data for 2000–2012 to explore a dose-response effect. Patients were matched by using a comprehensive set of variables selected following a standard model on access to care.FindingsOffice-based care (up to 5 visits/year) acts as a substitute for other healthcare services and is associated with lower use and expenditure for inpatient, outpatient and emergency care. After five visits, office-based care becomes a complement to other services and is associated with increases in expenditure for T2D. Above 20 to 26 visits per year, depending on the healthcare service under consideration, the marginal effect of an additional office-based visit becomes non-statistically significant.ConclusionsOffice-based visits appear to be an effective instrument to reduce use of inpatient care and other services, including outpatient and emergency-care, in patients with T2D without any increase in total healthcare expenditure.
Chi Y-L, Gad M, Bauhoff S, et al., 2018, Mind the costs, too: towards better cost-effectiveness analyses of PBF programmes, BMJ Global Health, Vol: 3, Pages: e000994-e000994, ISSN: 2059-7908
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