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Nhleko ML, Edoka I, Musenge E. Pancreatic cancer mortality in South Africa: A case-control study. S Afr Med J 2023; 114:27-32. [PMID: 38525629 DOI: 10.7196/samj.2024.v114i1.1132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Indexed: 03/26/2024] Open
Abstract
BACKGROUND There are variations in the numbers of pancreatic cancer deaths reported annually in South Africa (SA). Since pancreatic cancer deaths in SA from 1997 to 2016, the number of cases has hugely increased, and reached 23 581 in both sexes. Sex differences are likely to contribute to the variations in the strength of associations between the risk factors and pancreatic cancer mortality. OBJECTIVE To identify factors associated with an increased risk of pancreatic cancer mortality in SA. METHODS A matched case-control study with 1:1 matching was conducted using data collected by Statistics SA from 1997 to 2016. Controls were randomly selected to be as similar as possible to the cases, and matched by age, sex and year of death. Conditional logistic regression was used to identify factors associated with pancreatic cancer mortality. RESULTS This case-control study comprised a final selection of 23 581 cases (12 171 males and 11 410 females) and 23 581 controls (12 171 males and 11 410 females). A significantly increased risk of pancreatic cancer mortality was observed among males who were managers (odds ratio (OR) 2.99; 95% confidence interval (CI) 1.36 - 6.60; p=0.006) and craft and related trade workers (OR 1.89; 95% CI 1.14 - 3.14; p=0.013). Elevated risks of pancreatic cancer mortality were also found among females who were managers (OR 6.13; 95% CI 1.32 - 28.52; p=0.021), professionals (OR 2.12; 95% CI 1.24 - 3.63; p=0.006), clerical support workers (OR 3.78; 95% CI 1.79 - 7.98; p=0.001) and elementary occupation workers (OR 1.41; 95% CI 0.99 - 2.00; p=0.059). Smoking was significantly associated with pancreatic cancer mortality in females (OR 1.36; 95% CI 1.02 - 1.82; p=0.039). Working in several occupations was associated with an increased risk of pancreatic cancer mortality in males (OR 1.31; 95% CI 1.01 - 1.71; p=0.045) and females (OR 1.66; 95% CI 1.30 - 2.12; p<0.001). CONCLUSION Smoking and certain occupations increased the risk of pancreatic cancer mortality. Further research is needed to evaluate the associations between other extrinsic and intrinsic factors and pancreatic cancer mortality.
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Affiliation(s)
- M L Nhleko
- Division of Epidemiology and Biostatistics, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
| | - I Edoka
- Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
| | - E Musenge
- Division of Epidemiology and Biostatistics, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
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Nhleko ML, Edoka I, Musenge E. RETRACTED. S Afr Med J 2023; 113:33-36. [PMID: 37882118 DOI: 10.7196/samj.2023.v113i7.574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Indexed: 10/27/2023] Open
Abstract
BACKGROUND Upon the addition of the numbers corresponding to various cancer anatomical locations in the report published by Statistics South Africa (StatsSA), the absolute number and proportion of deaths due to all cancers increased from 36 726 (8.0%) in 2013 to 40 460 (8.5%) in 2015. These high figures suggest that malignant neoplasms were in fact the second-most frequent cause of death in South Africa (SA) in 2013, and moved to the first rank in 2015. OBJECTIVES To support the initiative aimed at reducing cancer mortality in SA. To this purpose, we assessed trends in cancer mortality rates among males and females in SA from 1997 to 2016 to better understand the increasing threat of cancer mortality in SA. METHODS The general mortality data for the period 1997 - 2016, as captured from death certificates in SA, was retrieved from StatsSA. Agestandardised mortality rates (ASMR) for each year were computed using the world standard population structure proposed by Segi as the reference population. The adjusted rates were reported per 100 000 population per year. The years of potential productive life lost (YPPLL) due to cancer deaths were calculated for each age group and gender. RESULTS There were 681 689 total cancer deaths from 1997 to 2016, with 51.1% males and 48.9% females. Males had higher mortality rates than females. The ASMR ranged from 105.0 to 129.2 and 67.9 to 88.3 per 100 000 population per year among males and females, respectively. In 2004, the cancer mortality rate increased significantly among males (129.2 per 100 000 population), which was 1.5 times higher than in females (88.3 per 100 000 population). Among males, cancer of the lung had the highest YPPLL (394 779.3), followed by oesophageal (253 989.4) and liver (207 911.0). The YPPLL for cancer of the cervix (647 855.5) ranked first, followed by breast (483 863.6) and lung (146 304.6) in females. CONCLUSION Cancer mortality rates have increased since 1997, regardless of gender. Overall, there was a decline in YPPLL for cancer in the young population, while it increased in the adult population. A significant reduction in cancer deaths could be achieved by broadly applying effective interventions.
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Affiliation(s)
- M L Nhleko
- Division of Epidemiology and Biostatistics, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
| | - I Edoka
- Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
| | - E Musenge
- Division of Epidemiology and Biostatistics, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
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Nhleko ML, Edoka I, Musenge E. Cancer mortality distribution in South Africa, 1997-2016. Front Epidemiol 2023; 3:1094271. [PMID: 38455894 PMCID: PMC10911026 DOI: 10.3389/fepid.2023.1094271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 05/26/2023] [Indexed: 03/09/2024]
Abstract
Introduction The mortality data in South Africa (SA) have not been widely used to estimate the patterns of deaths attributed to cancer over a spectrum of relevant subgroups. There is no research in SA providing patterns and atlases of cancer deaths in age and sex groups per district per year. This study presents age-sex-specific geographical patterns of cancer mortality at the district level in SA and their temporal evolutions from 1997 to 2016. Methods Individual mortality level data provided by Statistics South Africa were grouped by three age groups (0-14, 15-64, and 65+), sex (male and female), and aggregated at each of the 52 districts. The proportionate mortality ratios (PMRs) for cancer were calculated per 100 residents. The atlases showing the distribution of cancer mortality were plotted using ArcGIS. Spatial analyses were conducted through Moran's I test. Results There was an increase in PMRs for cancer in the age groups 15-64 and 65+ years from 2006 to 2016. Ranges were 2.83 (95% CI: 2.77-2.89) -4.16 (95% CI: 4.08-4.24) among men aged 15-64 years and 2.99 (95% CI: 2.93-3.06) -5.19 (95% CI: 5.09-5.28) among women in this age group. The PMRs in men and women aged 65+ years were 2.47 (95% CI: 2.42-2.53) -4.06 (95% CI: 3.98-4.14), and 2.33 (95% CI: 2.27-2.38) -4.19 (95% CI: 4.11-4.28). There were considerable geographical variations and similarities in the patterns of cancer mortality. For the age group 15-64 years, the ranges were 1.18 (95% CI: 0.78-1.71) -8.71 (95% CI: 7.18-10.47), p < 0.0001 in men and 1.35 (95% CI: 0.92-1.92) -10.83 (95% CI: 8.84-13.14), p < 0.0001 in women in 2016. There were higher PMRs among women in the Western Cape, Northern Cape, North West, and Gauteng compared to other areas. Similar patterns were also observed among men in these provinces, except in North West and Gauteng. Conclusion The identification of geographical and temporal distributions of cancer mortality provided evidence of periods and districts with similar and divergent patterns. This will contribute to understanding the past, present, future trends and formulating interventions at a local level.
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Affiliation(s)
- Mandlakayise Lucky Nhleko
- Division of Epidemiology and Biostatistics, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Ijeoma Edoka
- Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Eustasius Musenge
- Division of Epidemiology and Biostatistics, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
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Edoka I, Fraser H, Jamieson L, Meyer-Rath G, Mdewa W. Inpatient Care Costs of COVID-19 in South Africa's Public Healthcare System. Int J Health Policy Manag 2022; 11:1354-1361. [PMID: 33949817 PMCID: PMC9808349 DOI: 10.34172/ijhpm.2021.24] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 03/13/2021] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND Coronavirus disease 2019 (COVID-19) has had a devastating impact globally, with severe health and economic consequences. To prepare health systems to deal with the pandemic, epidemiological and cost projection models are required to inform budgets and efficient allocation of resources. This study estimates daily inpatient care costs of COVID-19 in South Africa, an important input into cost projection and economic evaluation models. METHODS We adopted a micro-costing approach, which involved the identification, measurement and valuation of resources used in the clinical management of COVID-19. We considered only direct medical costs for an episode of hospitalisation from the South African public health system perspective. Resource quantities and unit costs were obtained from various sources. Inpatient costs per patient day was estimated for consumables, capital equipment and human resources for three levels of inpatient care - general wards, high care wards and intensive care units (ICUs). RESULTS Average daily costs per patient increased with the level of care. The highest average daily cost was estimated for ICU admissions - 271 USD to 306 USD (financial costs) and ~800 USD to 830 USD (economic costs, excluding facility fee) depending on the need for invasive vs. non-invasive ventilation (NIV). Conversely, the lowest cost was estimated for general ward-based care - 62 USD to 79 USD (financial costs) and 119 USD to 278 USD (economic costs, excluding facility fees) depending on the need for supplemental oxygen. In high care wards, total cost was estimated at 156 USD, financial costs and 277 USD, economic costs (excluding facility fees). Probabilistic sensitivity analyses suggest our costs estimates are robust to uncertainty in cost inputs. CONCLUSION Our estimates of inpatient costs are useful for informing budgeting and planning processes and cost-effectiveness analysis in the South African context. However, these estimates can be adapted to inform policy decisions in other context.
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Affiliation(s)
- Ijeoma Edoka
- SAMRC Centre for Health Economics and Decision Science-PRICELESS SA, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Heather Fraser
- SAMRC Centre for Health Economics and Decision Science-PRICELESS SA, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Lise Jamieson
- Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Gesine Meyer-Rath
- Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Department of Global Health, School of Public Health, Boston University, Boston, MA, USA
| | - Winfrida Mdewa
- SAMRC Centre for Health Economics and Decision Science-PRICELESS SA, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
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Edoka I, Stacey N. Response to a Commentary by Barr (2022) on Edoka and Stacey (2020) Estimating a Cost-Effectiveness Threshold for Health Care Decision-Making in South Africa. Health Policy Plan 2022; 37:1070-1073. [PMID: 35762464 DOI: 10.1093/heapol/czac049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 06/27/2022] [Indexed: 11/12/2022] Open
Affiliation(s)
- Ijeoma Edoka
- Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, South Africa
| | - Nicholas Stacey
- Department of Health Policy, London School of Economics and Political Science, United Kingdom
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Vallejo-Torres L, García-Lorenzo B, Edney LC, Stadhouders N, Edoka I, Castilla-Rodríguez I, García-Pérez L, Linertová R, Valcárcel-Nazco C, Karnon J. Are Estimates of the Health Opportunity Cost Being Used to Draw Conclusions in Published Cost-Effectiveness Analyses? A Scoping Review in Four Countries. Appl Health Econ Health Policy 2022; 20:337-349. [PMID: 34964092 PMCID: PMC9021093 DOI: 10.1007/s40258-021-00707-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 11/23/2021] [Indexed: 05/19/2023]
Abstract
BACKGROUND When healthcare budgets are exogenous, cost-effectiveness thresholds (CETs) used to inform funding decisions should represent the health opportunity cost (HOC) of such funding decisions, but HOC-based CET estimates have not been available until recently. In recent years, empirical HOC-based CETs for multiple countries have been published, but the use of these CETs in the cost-effectiveness analysis (CEA) literature has not been investigated. Analysis of the use of HOC-based CETs by researchers undertaking CEAs in countries with different decision-making contexts will provide valuable insights to further understand barriers and facilitators to the acceptance and use of HOC-based CETs. OBJECTIVES We aimed to identify the CET values used to interpret the results of CEAs published in the scientific literature before and after the publication of jurisdiction-specific empirical HOC-based CETs in four countries. METHODS We undertook a scoping review of CEAs published in Spain, Australia, the Netherlands and South Africa between 2016 (2014 in Spain) and 2020. CETs used before and after publication of HOC estimates were recorded. We conducted logit regressions exploring factors explaining the use of HOC values in identified studies and linear models exploring the association of the reported CET value with study characteristics and results. RESULTS 1171 studies were included in this review (870 CEAs and 301 study protocols). HOC values were cited in 28% of CEAs in Spain and in 11% of studies conducted in Australia, but they were not referred to in CEAs undertaken in the Netherlands and South Africa. Regression analyses on Spanish and Australian studies indicate that more recent studies, studies without a conflict of interest and studies estimating an incremental cost-effectiveness ratio (ICER) below the HOC value were more likely to use the HOC as a threshold reference. In addition, we found a small but significant impact indicating that for every dollar increase in the estimated ICER, the reported CET increased by US$0.015. Based on the findings of our review, we discuss the potential factors that might explain the lack of adoption of HOC-based CETs in the empirical CEA literature. CONCLUSIONS The adoption of HOC-based CETs by identified published CEAs has been uneven across the four analysed countries, most likely due to underlying differences in their decision-making processes. Our results also reinforce a previous finding indicating that CETs might be endogenously selected to fit authors' conclusions.
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Affiliation(s)
- Laura Vallejo-Torres
- Departamento de Métodos Cuantitativos en Economía y Gestión, Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain.
| | - Borja García-Lorenzo
- Kronikgune Institute for Health Services Research, Barakaldo, Basque Country, Spain
- Assessment of Innovations and New Technologies Unit, Hospital Clínic Barcelona, University of Barcelona, Barcelona, Catalonia, Spain
| | - Laura Catherine Edney
- Flinders Health and Medical Research Institute, Flinders University, Bedford Park, SA, Australia
| | - Niek Stadhouders
- IQ Healthcare, Radboud University and Medical Center, Nijmegen, The Netherlands
| | - Ijeoma Edoka
- Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Iván Castilla-Rodríguez
- Departamento de Ingeniería Informática y de Sistemas, Universidad de La Laguna, La Laguna, Spain
| | - Lidia García-Pérez
- Canary Islands Health Research Institute Foundation (FIISC), Santa Cruz de Tenerife, Spain
- Evaluation Unit (SESCS), Canary Islands Health Service (SCS), Santa Cruz de Tenerife, Spain
- Research Network on Health Services in Chronic Diseases (REDISSEC), Madrid, Spain
- Red Española de Agencias de Evaluación de Tecnologías Sanitarias y Prestaciones del Sistema Nacional de Salud (RedETS), Madrid, Spain
| | - Renata Linertová
- Canary Islands Health Research Institute Foundation (FIISC), Santa Cruz de Tenerife, Spain
- Evaluation Unit (SESCS), Canary Islands Health Service (SCS), Santa Cruz de Tenerife, Spain
- Research Network on Health Services in Chronic Diseases (REDISSEC), Madrid, Spain
- Red Española de Agencias de Evaluación de Tecnologías Sanitarias y Prestaciones del Sistema Nacional de Salud (RedETS), Madrid, Spain
| | - Cristina Valcárcel-Nazco
- Canary Islands Health Research Institute Foundation (FIISC), Santa Cruz de Tenerife, Spain
- Evaluation Unit (SESCS), Canary Islands Health Service (SCS), Santa Cruz de Tenerife, Spain
- Research Network on Health Services in Chronic Diseases (REDISSEC), Madrid, Spain
- Red Española de Agencias de Evaluación de Tecnologías Sanitarias y Prestaciones del Sistema Nacional de Salud (RedETS), Madrid, Spain
| | - Jonathan Karnon
- Flinders Health and Medical Research Institute, Flinders University, Bedford Park, SA, Australia
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Fraser H, Tombe-Mdewa W, Kohli-Lynch C, Hofman K, Tempia S, McMorrow M, Lambach P, Ramkrishna W, Cohen C, Hutubessy R, Edoka I. Costs of seasonal influenza vaccination in South Africa. Influenza Other Respir Viruses 2022; 16:873-880. [PMID: 35355414 PMCID: PMC9343325 DOI: 10.1111/irv.12987] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 03/13/2022] [Indexed: 11/30/2022] Open
Abstract
Background Influenza accounts for a substantial number of deaths and hospitalisations annually in South Africa. To address this disease burden, the South African National Department of Health introduced a trivalent inactivated influenza vaccination programme in 2010. Methods We adapted and populated the WHO Seasonal Influenza Immunization Costing Tool (WHO SIICT) with country‐specific data to estimate the cost of the influenza vaccination programme in South Africa. Data were obtained through key‐informant interviews at different levels of the health system and through a review of existing secondary data sources. Costs were estimated from a public provider perspective and expressed in 2018 prices. We conducted scenario analyses to assess the impact of different levels of programme expansion and the use of quadrivalent vaccines on total programme costs. Results Total financial and economic costs were estimated at approximately USD 2.93 million and USD 7.91 million, respectively, while financial and economic cost per person immunised was estimated at USD 3.29 and USD 8.88, respectively. Expanding the programme by 5% and 10% increased economic cost per person immunised to USD 9.36 and USD 9.52 in the two scenarios, respectively. Finally, replacing trivalent inactivated influenza vaccine (TIV) with quadrivalent vaccine increased financial and economic costs to USD 4.89 and USD 10.48 per person immunised, respectively. Conclusion We adapted the WHO SIICT and provide estimates of the total costs of the seasonal influenza vaccination programme in South Africa. These estimates provide a basis for planning future programme expansion and may serve as inputs for cost‐effectiveness analyses of seasonal influenza vaccination programmes.
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Affiliation(s)
- Heather Fraser
- SAMRC Centre for Health Economics and Decision Science-PRICELESS SA, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,Health Economics and Health Technology Assessment, Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Winfrida Tombe-Mdewa
- SAMRC Centre for Health Economics and Decision Science-PRICELESS SA, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Ciaran Kohli-Lynch
- SAMRC Centre for Health Economics and Decision Science-PRICELESS SA, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Karen Hofman
- SAMRC Centre for Health Economics and Decision Science-PRICELESS SA, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Stefano Tempia
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.,Influenza Program, Centers for Disease Control and Prevention, Pretoria, South Africa.,MassGenics, Duluth, Georgia, USA.,School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Meredith McMorrow
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.,Influenza Program, Centers for Disease Control and Prevention, Pretoria, South Africa.,US Public Health Service, Rockville, Maryland, USA
| | - Philipp Lambach
- Department of Immunization, Vaccines and Biologicals, World Health Organization, Geneva, Switzerland
| | - Wayne Ramkrishna
- Communicable Disease Cluster, National Department of Health, Pretoria, South Africa
| | - Cheryl Cohen
- School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
| | - Raymond Hutubessy
- Department of Immunization, Vaccines and Biologicals, World Health Organization, Geneva, Switzerland
| | - Ijeoma Edoka
- SAMRC Centre for Health Economics and Decision Science-PRICELESS SA, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
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Stacey N, Mirelman A, Kreif N, Suhrcke M, Hofman K, Edoka I. Facility standards and the quality of public sector primary care: Evidence from South Africa's "Ideal Clinics" program. Health Econ 2021; 30:1543-1558. [PMID: 33728741 DOI: 10.1002/hec.4228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 12/31/2020] [Accepted: 01/04/2021] [Indexed: 06/12/2023]
Abstract
Primary healthcare systems are central to achieving universal healthcare coverage. However, in many low- and middle-income country settings, primary care quality is challenged by inadequate facility infrastructure and equipment, limited human resources, and poor provider process. We study the effects of a recent large-scale quality improvement policy in South Africa, the Ideal Clinics Realization and Maintenance Program (ICRMP). The ICRMP introduced a set of standards for facilities and a quality improvement process involving manuals, district-based support, and external assessment. Exploiting differential prioritization of facilities for the ICRMP's quality improvement process, we apply differences-in-differences methods to identify the effects of the program's efforts on standards scores and primary care quality indicators over the first 12 months of implementation. We find large and statistically significant increases in standards scores, but mixed effects on care outcomes-a small magnitude improvement in early antenatal care usage, null effects on childhood immunization and cervical cancer screening, and small negative effect of human immunodeficiency virus (HIV) care. While the ICRMP process has led to significant improvements in facilities' satisfaction of the program's standards, we were unable to detect meaningful change in care quality indicators.
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Affiliation(s)
- Nicholas Stacey
- Department of Health Policy, London School of Economics and Political Science, London, UK
- SAMRC/Wits Centre for Health Economics and Decision Science-PRICELESS SA, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | | | - Noemi Kreif
- Centre for Health Economics, University of York, York, UK
| | - Marc Suhrcke
- Centre for Health Economics, University of York, York, UK
- Luxembourg Institute of Socio-economic Research, Luxembourg
| | - Karen Hofman
- SAMRC/Wits Centre for Health Economics and Decision Science-PRICELESS SA, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Ijeoma Edoka
- SAMRC/Wits Centre for Health Economics and Decision Science-PRICELESS SA, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
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Stacey N, Edoka I, Hofman K, Swart EC, Popkin B, Ng SW. Changes in beverage purchases following the announcement and implementation of South Africa's Health Promotion Levy: an observational study. Lancet Planet Health 2021; 5:e200-e208. [PMID: 33838735 PMCID: PMC8071067 DOI: 10.1016/s2542-5196(20)30304-1] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 12/11/2020] [Accepted: 12/14/2020] [Indexed: 05/10/2023]
Abstract
BACKGROUND In 2016, South Africa announced an intention to levy a tax on sugar-sweetened beverages (SSBs). In 2018, the country implemented an SSB tax of approximately 10%, known as the Health Promotion Levy (HPL). We aimed to assess changes in the purchases of beverages before and after the HPL announcement and implementation. METHODS We used Kantar Europanel data on monthly household purchases between January, 2014, and March, 2019, among a sample of South African households (n=113 653 household-month observations) from all nine provinces to obtain per-capita sugar, calories, and volume from taxable and non-taxable beverages purchased before and after the HPL announcement and implementation. We describe survey-weighted means for each period, and regression-controlled predictions of outcomes and counterfactuals based on pre-HPL announcement trends, with bootstrapped 95% CIs, and stratify results by socioeconomic status. FINDINGS Mean sugar from taxable beverage purchases fell from 16·25 g/capita per day (95% CI 15·80-16·70) to 14·26 (13·85-14·67) from the pre-HPL announcement to post-announcement period, and then to 10·63 g/capita per day (10·22-11·04) in the year after implementation. Mean volumes of taxable beverage purchases fell from 518·99 mL/capita per day (506·90-531·08) to 492·16 (481·28-503·04) from pre-announcement to post announcement, and then to 443·39 mL/capita per day (430·10-456·56) after implementation. Across these time periods, there was a small increase in the purchases of non-taxable beverages, from 283·45 mL/capita per day (273·34-293·56) pre-announcement to 312·94 (296·29-329·29) post implementation. When compared with pre-announcement counterfactual trends, reductions in taxable beverage purchase outcomes were significantly larger than the unadjusted survey-weighted observed reductions. Households with lower socioeconomic status purchased larger amounts of taxable beverages in the pre-announcement period than did households with higher socioeconomic status, but demonstrated bigger reductions after the tax was implemented. INTERPRETATION The announcement and introduction of South Africa's HPL were followed by reductions in the sugar, calories, and volume of beverage purchases. FUNDING Bloomberg Philanthropies, International Development Research Centre, South African Medical Research Council, and the US National Institutes of Health.
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Affiliation(s)
- Nicholas Stacey
- SAMRC/Wits Centre for Health Economics and Decision Science - PRICELESS SA, Wits School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; Department of Health Policy, London School of Economics and Political Science, London, UK
| | - Ijeoma Edoka
- SAMRC/Wits Centre for Health Economics and Decision Science - PRICELESS SA, Wits School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Karen Hofman
- SAMRC/Wits Centre for Health Economics and Decision Science - PRICELESS SA, Wits School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Elizabeth C Swart
- Department of Dietetics and Nutrition, University of the Western Cape, Cape Town, South Africa; DST/NRF Center of Excellence in Food Security, University of the Western Cape, Cape Town, South Africa
| | - Barry Popkin
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA; Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA
| | - Shu Wen Ng
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA; Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA.
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10
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Jo Y, Jamieson L, Edoka I, Long L, Silal S, Pulliam JRC, Moultrie H, Sanne I, Meyer-Rath G, Nichols BE. Cost-effectiveness of Remdesivir and Dexamethasone for COVID-19 Treatment in South Africa. Open Forum Infect Dis 2021; 8:ofab040. [PMID: 33732750 PMCID: PMC7928624 DOI: 10.1093/ofid/ofab040] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Accepted: 01/24/2021] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Dexamethasone and remdesivir have the potential to reduce coronavirus disease 2019 (COVID)-related mortality or recovery time, but their cost-effectiveness in countries with limited intensive care resources is unknown. METHODS We projected intensive care unit (ICU) needs and capacity from August 2020 to January 2021 using the South African National COVID-19 Epi Model. We assessed the cost-effectiveness of (1) administration of dexamethasone to ventilated patients and remdesivir to nonventilated patients, (2) dexamethasone alone to both nonventilated and ventilated patients, (3) remdesivir to nonventilated patients only, and (4) dexamethasone to ventilated patients only, all relative to a scenario of standard care. We estimated costs from the health care system perspective in 2020 US dollars, deaths averted, and the incremental cost-effectiveness ratios of each scenario. RESULTS Remdesivir for nonventilated patients and dexamethasone for ventilated patients was estimated to result in 408 (uncertainty range, 229-1891) deaths averted (assuming no efficacy [uncertainty range, 0%-70%] of remdesivir) compared with standard care and to save $15 million. This result was driven by the efficacy of dexamethasone and the reduction of ICU-time required for patients treated with remdesivir. The scenario of dexamethasone alone for nonventilated and ventilated patients requires an additional $159 000 and averts 689 [uncertainty range, 330-1118] deaths, resulting in $231 per death averted, relative to standard care. CONCLUSIONS The use of remdesivir for nonventilated patients and dexamethasone for ventilated patients is likely to be cost-saving compared with standard care by reducing ICU days. Further efforts to improve recovery time with remdesivir and dexamethasone in ICUs could save lives and costs in South Africa.
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Affiliation(s)
- Youngji Jo
- Section of Infectious Disease, Department of Medicine, Boston Medical Center, Boston, Massachusetts, USA
| | - Lise Jamieson
- Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Ijeoma Edoka
- SAMRC Centre for Health Economics and Decision Science-PRICELESS SA, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Lawrence Long
- Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Department of Global Health, School of Public Health, Boston University, Boston, Massachusetts, USA
| | - Sheetal Silal
- Modelling and Simulation Hub, Africa, Department of Statistical Sciences, University of Cape Town, Cape Town, South Africa
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Juliet R C Pulliam
- South African DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, South Africa
| | - Harry Moultrie
- Division of the National Health Laboratory Service, National Institute for Communicable Diseases (NICD), Johannesburg, South Africa
| | - Ian Sanne
- Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Gesine Meyer-Rath
- Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Department of Global Health, School of Public Health, Boston University, Boston, Massachusetts, USA
| | - Brooke E Nichols
- Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Department of Global Health, School of Public Health, Boston University, Boston, Massachusetts, USA
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11
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Edoka I, Kohli-Lynch C, Fraser H, Hofman K, Tempia S, McMorrow M, Ramkrishna W, Lambach P, Hutubessy R, Cohen C. A cost-effectiveness analysis of South Africa's seasonal influenza vaccination programme. Vaccine 2020; 39:412-422. [PMID: 33272702 DOI: 10.1016/j.vaccine.2020.11.028] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Revised: 10/02/2020] [Accepted: 11/09/2020] [Indexed: 12/16/2022]
Abstract
BACKGROUND Seasonal influenza imposes a significant health and economic burden in South Africa, particularly in populations vulnerable to severe consequences of influenza. This study assesses the cost-effectiveness of South Africa's seasonal influenza vaccination strategy, which involves vaccinating vulnerable populations with trivalent inactivated influenza vaccine (TIV) during routine facility visits. Vulnerable populations included in our analysis are persons aged ≥ 65 years; pregnant women; persons living with HIV/AIDS (PLWHA), persons of any age with underlying medical conditions (UMC) and children aged 6-59 months. METHOD We employed the World Health Organisation's (WHO) Cost Effectiveness Tool for Seasonal Influenza Vaccination (CETSIV), a decision tree model, to evaluate the 2018 seasonal influenza vaccination campaign from a public healthcare provider and societal perspective. CETSIV was populated with existing country-specific demographic, epidemiologic and coverage data to estimate incremental cost-effectiveness ratios (ICERs) by comparing costs and benefits of the influenza vaccination programme to no vaccination. RESULTS The highest number of clinical events (influenza cases, outpatient visits, hospitalisation and deaths) were averted in PLWHA and persons with other UMCs. Using a cost-effectiveness threshold of US$ 3400 per quality-adjusted life year (QALY), our findings suggest that the vaccination programme is cost-effective for all vulnerable populations except for children aged 6-59 months. ICERs ranged from ~US$ 1 750 /QALY in PLWHA to ~US$ 7500/QALY in children. In probabilistic sensitivity analyses, the vaccination programme was cost-effective in pregnant women, PLWHA, persons with UMCs and persons aged ≥65 years in >80% of simulations. These findings were robust to changes in many model inputs but were most sensitive to uncertainty in estimates of influenza-associated illness burden. CONCLUSION South Africa's seasonal influenza vaccination strategy of opportunistically targeting vulnerable populations during routine visits is cost-effective. A budget impact analysis will be useful for supporting future expansions of the programme.
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Affiliation(s)
- Ijeoma Edoka
- SAMRC Centre for Health Economics and Decision Science - PRICELESS SA, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
| | - Ciaran Kohli-Lynch
- SAMRC Centre for Health Economics and Decision Science - PRICELESS SA, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Heather Fraser
- SAMRC Centre for Health Economics and Decision Science - PRICELESS SA, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Karen Hofman
- SAMRC Centre for Health Economics and Decision Science - PRICELESS SA, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Stefano Tempia
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA; Influenza Program, Centers for Disease Control and Prevention, Pretoria, South Africa; Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; MassGenics, Duluth, GA, USA; School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Meredith McMorrow
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA; Influenza Program, Centers for Disease Control and Prevention, Pretoria, South Africa; US Public Health Service, Rockville, MD, USA
| | - Wayne Ramkrishna
- Communicable Disease Cluster, National Department of Health, South Africa
| | - Philipp Lambach
- Department of Immunization, Vaccines and Biologicals, Initiative for Vaccine Research, World Health Organization, Geneva, Switzerland
| | - Raymond Hutubessy
- Department of Immunization, Vaccines and Biologicals, Initiative for Vaccine Research, World Health Organization, Geneva, Switzerland
| | - Cheryl Cohen
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
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12
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Chi YL, Blecher M, Chalkidou K, Culyer A, Claxton K, Edoka I, Glassman A, Kreif N, Jones I, Mirelman AJ, Nadjib M, Morton A, Norheim OF, Ochalek J, Prinja S, Ruiz F, Teerawattananon Y, Vassall A, Winch A. What next after GDP-based cost-effectiveness thresholds? Gates Open Res 2020; 4:176. [PMID: 33575544 PMCID: PMC7851575 DOI: 10.12688/gatesopenres.13201.1] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/20/2020] [Indexed: 11/30/2022] Open
Abstract
Public payers around the world are increasingly using cost-effectiveness thresholds (CETs) to assess the value-for-money of an intervention and make coverage decisions. However, there is still much confusion about the meaning and uses of the CET, how it should be calculated, and what constitutes an adequate evidence base for its formulation. One widely referenced and used threshold in the last decade has been the 1-3 GDP per capita, which is often attributed to the Commission on Macroeconomics and WHO guidelines on Choosing Interventions that are Cost Effective (WHO-CHOICE). For many reasons, however, this threshold has been widely criticised; which has led experts across the world, including the WHO, to discourage its use. This has left a vacuum for policy-makers and technical staff at a time when countries are wanting to move towards Universal Health Coverage
. This article seeks to address this gap by offering five practical options for decision-makers in low- and middle-income countries that can be used instead of the 1-3 GDP rule, to combine existing evidence with fair decision-rules or develop locally relevant CETs. It builds on existing literature as well as an engagement with a group of experts and decision-makers working in low, middle and high income countries.
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Affiliation(s)
- Y-Ling Chi
- Center for Global Development, London, SW1P 3SE, UK
| | | | - Kalipso Chalkidou
- Center for Global Development, London, SW1P 3SE, UK.,Department of Infectious Disease Epidemiology, Imperial College London, London, SW7 2AZ, UK
| | - Anthony Culyer
- Centre for Health Economics, Department of Economics and Related Studies, University of York, York, YO10 5DD, UK
| | - Karl Claxton
- Centre for Health Economics, Department of Economics and Related Studies, University of York, York, YO10 5DD, UK
| | - Ijeoma Edoka
- School of Public Health, Wits University, Parktown, 2193, South Africa
| | | | - Noemi Kreif
- Centre for Health Economics, Department of Economics and Related Studies, University of York, York, YO10 5DD, UK
| | - Iain Jones
- Sightsavers, Haywards Health, RH16 3BW, UK
| | - Andrew J Mirelman
- Centre for Health Economics, Department of Economics and Related Studies, University of York, York, YO10 5DD, UK
| | - Mardiati Nadjib
- Faculty of Public Health, Department of Health Policy and Administration, Universitas Indonesia, Depok, Indonesia
| | | | - Ole Frithjof Norheim
- BCEPS, Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
| | - Jessica Ochalek
- Centre for Health Economics, Department of Economics and Related Studies, University of York, York, YO10 5DD, UK
| | - Shankar Prinja
- Department of Community Medicine & School of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh, 160 012, India
| | - Francis Ruiz
- Center for Global Development, London, SW1P 3SE, UK.,Department of Infectious Disease Epidemiology, Imperial College London, London, SW7 2AZ, UK
| | - Yot Teerawattananon
- Health Intervention and Technology Assessment Program, Ministry of Public Health, Thailand, Nonthaburi, 11000, Thailand
| | - Anna Vassall
- Department of Global Health and Development, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, WC1H 9SH, UK
| | - Alexander Winch
- Department of Infectious Disease Epidemiology, Imperial College London, London, SW7 2AZ, UK
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13
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Jo Y, Jamieson L, Edoka I, Long L, Silal S, Pulliam JRC, Moultrie H, Sanne I, Meyer-Rath G, Nichols BE. Cost-effectiveness of remdesivir and dexamethasone for COVID-19 treatment in South Africa. medRxiv 2020. [PMID: 32995824 DOI: 10.1101/2020.09.24.20200196] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Background South Africa recently experienced a first peak in COVID-19 cases and mortality. Dexamethasone and remdesivir both have the potential to reduce COVID-related mortality, but their cost-effectiveness in a resource-limited setting with scant intensive care resources is unknown. Methods We projected intensive care unit (ICU) needs and capacity from August 2020 to January 2021 using the South African National COVID-19 Epi Model. We assessed cost-effectiveness of 1) administration of dexamethasone to ventilated patients and remdesivir to non-ventilated patients, 2) dexamethasone alone to both non-ventilated and ventilated patients, 3) remdesivir to non-ventilated patients only, and 4) dexamethasone to ventilated patients only; all relative to a scenario of standard care. We estimated costs from the healthcare system perspective in 2020 USD, deaths averted, and the incremental cost effectiveness ratios of each scenario. Results Remdesivir for non-ventilated patients and dexamethasone for ventilated patients was estimated to result in 1,111 deaths averted (assuming a 0-30% efficacy of remdesivir) compared to standard care, and save $11.5 million. The result was driven by the efficacy of the drugs, and the reduction of ICU-time required for patients treated with remdesivir. The scenario of dexamethasone alone to ventilated and non-ventilated patients requires additional $159,000 and averts 1,146 deaths, resulting in $139 per death averted, relative to standard care. Conclusions The use of dexamethasone for ventilated and remdesivir for non-ventilated patients is likely to be cost-saving compared to standard care. Given the economic and health benefits of both drugs, efforts to ensure access to these medications is paramount.
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14
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Tempia S, Moyes J, Cohen AL, Walaza S, McMorrow ML, Edoka I, Fraser H, Treurnicht FK, Hellferscee O, Wolter N, von Gottberg A, McAnerney JM, Dawood H, Variava E, Cohen C. Influenza economic burden among potential target risk groups for immunization in South Africa, 2013-2015. Vaccine 2020; 38:7007-7014. [PMID: 32980198 DOI: 10.1016/j.vaccine.2020.09.033] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 09/10/2020] [Accepted: 09/11/2020] [Indexed: 11/18/2022]
Abstract
BACKGROUND Data on influenza economic burden in risk groups for severe influenza are important to guide targeted influenza immunization, especially in resource-limited settings. However, this information is limited in low- and middle-income countries. METHODS We estimated the cost (from a health system and societal perspective) and years of life lost (YLL) for influenza-associated illness in South Africa during 2013-2015 among (i) children aged 6-59 months, (ii) individuals aged 5-64 years with HIV, pulmonary tuberculosis (PTB) and selected underlying medical conditions (UMC), separately, (iii) pregnant women and (iv) individuals aged ≥65 years, using publicly available data and data collected through laboratory-confirmed influenza surveillance and costing studies. All costs were expressed in 2015 prices using the South Africa all-items Consumer Price Index. RESULTS During 2013-2015, the mean annual cost of influenza-associated illness among the selected risk groups accounted for 52.1% ($140.9/$270.5 million) of the total influenza-associated illness cost (for the entire population of South Africa), 45.2% ($52.2/$115.5 million) of non-medically attended illness costs, 43.3% ($46.7/$107.9 million) of medically-attended mild illness costs and 89.3% ($42.0/$47.1 million) of medically-attended severe illness costs. The YLL among the selected risk groups accounted for 86.0% (262,069 /304,867 years) of the total YLL due to influenza-associated death. CONCLUSION In South Africa, individuals in risk groups for severe influenza accounted for approximately half of the total influenza-associated illness cost but most of the cost of influenza-associated medically attended severe illness and YLL. This study provides the foundation for future studies on the cost-effectiveness of influenza immunization among risk groups.
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Affiliation(s)
- Stefano Tempia
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, United States; Influenza Program, Centers for Disease Control and Prevention, Pretoria, South Africa; Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; MassGenics, Duluth, Georgia, Unites States of America; School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
| | - Jocelyn Moyes
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Adam L Cohen
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, United States; Department of Immunization, Vaccines and Biological, World Health Organization, Geneva, Switzerland
| | - Sibongile Walaza
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Meredith L McMorrow
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, United States; Influenza Program, Centers for Disease Control and Prevention, Pretoria, South Africa
| | - Ijeoma Edoka
- South Africa Medical Research Council/Wits Centre for Health Economic and Decision Science - PRICELESS SA, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Heather Fraser
- South Africa Medical Research Council/Wits Centre for Health Economic and Decision Science - PRICELESS SA, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Florette K Treurnicht
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
| | - Orienka Hellferscee
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Nicole Wolter
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Anne von Gottberg
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Johanna M McAnerney
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
| | - Halima Dawood
- Department of Medicine, Greys Hospital, Pietermaritzburg, South Africa; Caprisa, University of KwaZulu-Natal, Pietermaritzburg, South Africa
| | - Ebrahim Variava
- Department of Medicine, Klerksdorp-Tshepong Hospital Complex, Klerksdorp, South Africa; Department of Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; Perinatal HIV Research Unit, University of the Witwatersrand, Johannesburg, South Africa
| | - Cheryl Cohen
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
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15
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Tempia S, Walaza S, Moyes J, McMorrow ML, Cohen AL, Edoka I, Fraser H, Treurnicht FK, Hellferscee O, Wolter N, von Gottberg A, McAnerney JM, Dawood H, Variava E, Cohen C. Influenza disease burden among potential target risk groups for immunization in South Africa, 2013-2015. Vaccine 2020; 38:4288-4297. [PMID: 32389494 DOI: 10.1016/j.vaccine.2020.04.045] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2019] [Revised: 04/17/2020] [Accepted: 04/18/2020] [Indexed: 01/18/2023]
Abstract
BACKGROUND Data on influenza burden in risk groups for severe influenza are important to guide targeted influenza immunization, especially in resource limited settings. However, this information is limited overall and in particular in low- and middle-income countries. We sought to assess the mean annual national burden of medically and non-medically attended influenza-associated mild, severe-non-fatal and fatal illness among potential target groups for influenza immunization in South Africa during 2013-2015. METHODS We used published mean national annual estimates of mild, severe-non-fatal, and fatal influenza-associated illness in South Africa during 2013-2015 and estimated the number of such illnesses occurring among the following risk groups: (i) children aged 6-59 months; (ii) individuals aged 5-64 years with HIV, and/or pulmonary tuberculosis (PTB), and/or selected underlying medical conditions (UMC); (iii) pregnant women; and (iv) individuals aged ≥65 years. We also estimated the number of individuals among the same risk groups in the population. RESULTS During 2013-2015, individuals in the selected risk groups accounted for 45.3% (24,569,328/54,086,144) of the population and 43.5% (4,614,763/10,598,138), 86.8% (111,245/128,173) and 94.5% (10,903/11,536) of the mean annual estimated number of influenza-associated mild, severe-non-fatal and fatal illness episodes, respectively. The rates of influenza-associated illness were highest in children aged 6-59 months (23,983 per 100,000 population) for mild illness, in pregnant women (930 per 100,000 population) for severe-non-fatal illness and in individuals aged ≥65 years (138 per 100,000 population) for fatal illness. CONCLUSION Influenza immunization of the selected risk groups has the potential to prevent a substantial number of influenza-associated severe illness. Nonetheless, because of the high number of individuals at risk, South Africa, due to financial resources constrains, may need to further prioritize interventions among risk populations. Cost-burden and cost-effectiveness estimates may assist with further prioritization.
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Affiliation(s)
- Stefano Tempia
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, United States; Influenza Program, Centers for Disease Control and Prevention, Pretoria, South Africa; Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; MassGenics, Duluth, GA, United States.
| | - Sibongile Walaza
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Jocelyn Moyes
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Meredith L McMorrow
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, United States; Influenza Program, Centers for Disease Control and Prevention, Pretoria, South Africa
| | - Adam L Cohen
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, United States; Department of Immunization, Vaccines and Biological, World Health Organization, Geneva, Switzerland
| | - Ijeoma Edoka
- South Africa Medical Research Council/Wits Centre for Health Economics and Decision Science, PRICELESS SA, University of Witwatersrand School of Public Health, Faculty of Health Sciences, Johannesburga South Africa
| | - Heather Fraser
- South Africa Medical Research Council/Wits Centre for Health Economics and Decision Science, PRICELESS SA, University of Witwatersrand School of Public Health, Faculty of Health Sciences, Johannesburga South Africa
| | - Florette K Treurnicht
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
| | - Orienka Hellferscee
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Nicole Wolter
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Anne von Gottberg
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Johanna M McAnerney
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
| | - Halima Dawood
- Department of Medicine, Pietermaritzburg Metropolitan Hospital, Pietermaritzburg, South Africa; Department of Medicine, University of KwaZulu-Natal, Pietermaritzburg, South Africa
| | - Ebrahim Variava
- Department of Medicine, Klerksdorp-Tshepong Hospital Complex, Klerksdorp, South Africa; Department of Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; Perinatal HIV Research Unit, University of the Witwatersrand, Johannesburg, South Africa
| | - Cheryl Cohen
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
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16
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Tempia S, Moyes J, Cohen AL, Walaza S, Edoka I, McMorrow ML, Treurnicht FK, Hellferscee O, Wolter N, von Gottberg A, Nguweneza A, McAnerney JM, Dawood H, Variava E, Cohen C. Health and economic burden of influenza-associated illness in South Africa, 2013-2015. Influenza Other Respir Viruses 2019; 13:484-495. [PMID: 31187609 PMCID: PMC6692552 DOI: 10.1111/irv.12650] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Revised: 05/10/2019] [Accepted: 05/10/2019] [Indexed: 01/01/2023] Open
Abstract
Background Economic burden estimates are essential to guide policy‐making for influenza vaccination, especially in resource‐limited settings. Methods We estimated the cost, absenteeism, and years of life lost (YLL) of medically and non‐medically attended influenza‐associated mild and severe respiratory, circulatory and non‐respiratory/non‐circulatory illness in South Africa during 2013‐2015 using a modified version of the World Health Organization (WHO) worksheet based tool for estimating the economic burden of seasonal influenza. Additionally, we restricted the analysis to influenza‐associated severe acute respiratory illness (SARI) and influenza‐like illness (ILI; subsets of all‐respiratory illnesses) as suggested in the WHO manual. Results The estimated mean annual cost of influenza‐associated illness was $270.5 million, of which $111.3 million (41%) were government‐incurred costs, 40.7 million (15%) were out‐of‐pocket expenses, and $118.4 million (44%) were indirect costs. The cost of influenza‐associated medically attended mild illness ($107.9 million) was 2.3 times higher than that of severe illness ($47.1 million). Influenza‐associated respiratory illness costs ($251.4 million) accounted for 93% of the total cost. Estimated absenteeism and YLL were 13.2 million days and 304 867 years, respectively. Among patients with influenza‐associated WHO‐defined ILI or SARI, the costs ($95.3 million), absenteeism (4.5 million days), and YLL (65 697) were 35%, 34%, and 21% of the total economic and health burden of influenza. Conclusion The economic burden of influenza‐associated illness was substantial from both a government and a societal perspective. Models that limit estimates to those obtained from patients with WHO‐defined ILI or SARI substantially underestimated the total economic and health burden of influenza‐associated illness.
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Affiliation(s)
- Stefano Tempia
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia.,Influenza Program, Centers for Disease Control and Prevention, Pretoria, South Africa.,Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.,MassGenics, Duluth, Georgia
| | - Jocelyn Moyes
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.,Faculty of Health Sciences, School of Public Health, University of the Witwatersrand, Johannesburg, South Africa
| | - Adam L Cohen
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia.,Influenza Program, Centers for Disease Control and Prevention, Pretoria, South Africa.,Expanded Programme on Immunization, Department of Immunization, Vaccines and Biological, World Health Organization, Geneva, Switzerland
| | - Sibongile Walaza
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.,Faculty of Health Sciences, School of Public Health, University of the Witwatersrand, Johannesburg, South Africa
| | - Ijeoma Edoka
- Priority Cost Effectiveness Lessons for System Strengthening South Africa, South Africa Medical Research Council, Wits Center for Health Economic and Decision Science, School of Public Health, University of the Witwatersrand, Johannesburg, South Africa
| | - Meredith L McMorrow
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia.,Influenza Program, Centers for Disease Control and Prevention, Pretoria, South Africa
| | - Florette K Treurnicht
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
| | - Orienka Hellferscee
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.,Faculty of Health Sciences, School of Pathology, University of the Witwatersrand, Johannesburg, South Africa
| | - Nicole Wolter
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.,Faculty of Health Sciences, School of Pathology, University of the Witwatersrand, Johannesburg, South Africa
| | - Anne von Gottberg
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.,Faculty of Health Sciences, School of Pathology, University of the Witwatersrand, Johannesburg, South Africa
| | - Athermon Nguweneza
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
| | - Johanna M McAnerney
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
| | - Halima Dawood
- Department of Medicine, Greys Hospital, Pietermaritzburg, South Africa.,Caprisa, University of KwaZulu-Natal, Pietermaritzburg, South Africa
| | - Ebrahim Variava
- Department of Medicine, Klerksdorp-Tshepong Hospital Complex, Klerksdorp, South Africa.,Faculty of Health Sciences, Department of Medicine, University of the Witwatersrand, Johannesburg, South Africa.,Perinatal HIV Research Unit, University of the Witwatersrand, Johannesburg, South Africa
| | - Cheryl Cohen
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.,Faculty of Health Sciences, School of Public Health, University of the Witwatersrand, Johannesburg, South Africa
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17
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Alshreef A, MacQuilkan K, Dawkins B, Riddin J, Ward S, Meads D, Taylor M, Dixon S, Culyer AJ, Ruiz F, Chalkidou K, Edoka I. Cost-Effectiveness of Docetaxel and Paclitaxel for Adjuvant Treatment of Early Breast Cancer: Adaptation of a Model-Based Economic Evaluation From the United Kingdom to South Africa. Value Health Reg Issues 2019; 19:65-74. [PMID: 31096179 DOI: 10.1016/j.vhri.2019.03.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2018] [Revised: 02/02/2019] [Accepted: 03/08/2019] [Indexed: 12/24/2022]
Abstract
OBJECTIVES Transferability of economic evaluations to low- and middle-income countries through adaptation of models is important; however, several methodological and practical challenges remain. Given its significant costs and the quality-of-life burden to patients, adjuvant treatment of early breast cancer was identified as a priority intervention by the South African National Department of Health. This study assessed the cost-effectiveness of docetaxel and paclitaxel-containing chemotherapy regimens (taxanes) compared with standard (non-taxane) treatments. METHODS A cost-utility analysis was undertaken based on a UK 6-health-state Markov model adapted for South Africa using the Mullins checklist. The analysis assumed a 35-year time horizon. The model was populated with clinical effectiveness data (hazard ratios, recurrence rates, and adverse events) using direct comparisons from clinical trials. Resource use patterns and unit costs for estimating cost parameters (drugs, diagnostics, consumables, personnel) were obtained from South Africa. Uncertainty was assessed using probabilistic and deterministic sensitivity analyses. RESULTS The incremental cost per patient for the docetaxel regimen compared with standard treatment was R6774. The incremental quality-adjusted life years (QALYs) were 0.24, generating an incremental cost-effectiveness ratio of R28430 per QALY. The cost of the paclitaxel regimen compared with standard treatment was estimated as -R578 and -R1512, producing an additional 0.03 and 0.025 QALYs, based on 2 trials. Paclitaxel, therefore, appears to be a dominant intervention. The base case results were robust to all sensitivity analyses. CONCLUSIONS Based on the adapted model, docetaxel and paclitaxel are predicted to be cost-effective as adjuvant treatment for early breast cancer in South Africa.
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Affiliation(s)
- Abualbishr Alshreef
- Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, England, UK.
| | - Kim MacQuilkan
- SAMRC/Wits Centre for Health Economics and Priority Setting, PRICELESS SA, School of Public Health, Faculty of Health Sciencess, University of the Witwatersrand, Johannesburg, South Africa
| | - Bryony Dawkins
- Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds, Leeds, England, UK
| | - Jane Riddin
- Essential Drugs Programme, National Department of Health, Pretoria, South Africa
| | - Sue Ward
- Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, England, UK
| | - David Meads
- Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds, Leeds, England, UK
| | - Matthew Taylor
- York Health Economics Consortium, University of York, York, England, UK
| | - Simon Dixon
- Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, England, UK
| | - Anthony J Culyer
- Department of Economics and Related Studies, University of York, York, England, UK
| | - Francis Ruiz
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, England, UK
| | - Kalipso Chalkidou
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, England, UK; Centre for Global Development Europe, London, England, UK
| | - Ijeoma Edoka
- SAMRC/Wits Centre for Health Economics and Priority Setting, PRICELESS SA, School of Public Health, Faculty of Health Sciencess, University of the Witwatersrand, Johannesburg, South Africa
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18
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Edoka I, McPake B, Ensor T, Amara R, Edem-Hotah J. Changes in catastrophic health expenditure in post-conflict Sierra Leone: an Oaxaca-blinder decomposition analysis. Int J Equity Health 2017; 16:166. [PMID: 28870228 PMCID: PMC5583765 DOI: 10.1186/s12939-017-0661-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2016] [Accepted: 08/24/2017] [Indexed: 11/10/2022] Open
Abstract
Background At the end of the eleven-year conflict in Sierra Leone, a wide range of policies were implemented to address both demand- and supply-side constraints within the healthcare system, which had collapsed during the conflict. This study examines the extent to which households’ exposure to financial risks associated with seeking healthcare evolved in post-conflict Sierra Leone. Method This study uses the 2003 and 2011 cross-sections of the Sierra Leone Integrated Household Survey to examine changes in catastrophic health expenditure between 2003 and 2011. An Oaxaca-Blinder decomposition approach is used to quantify the extent to which changes in catastrophic health expenditure are attributable to changes in the distribution of determinants (distributional effect) and to changes in the impact of these determinants on the probability of incurring catastrophic health expenditure (coefficient effect). Results The incidence of catastrophic health expenditure decreased significantly by 18% from approximately 50% in 2003 t0 32% in 2011. The decomposition analysis shows that this decrease represents net effects attributable to the distributional and coefficient effects of three determinants of catastrophic health expenditure – ill-health, the region in which households reside and the type of health facility used. A decrease in the incidence of ill-health and changes in the regional location of households contributed to a decrease in catastrophic health expenditure. The distributional effect of health facility types observed as an increase in the use of public health facilities, and a decrease in the use of services in facilities owned by non-governmental organizations (NGOs) also contributed to a decrease in the incidence of catastrophic health expenditure. However, the coefficient effect of public health facilities and NGO-owned facilities suggests that substantial exposure to financial risk remained for households utilizing both types of health facilities in 2011. Conclusion The findings support the need to continue expanding current demand-side policies in Sierra Leone to reduce the financial risk of exposure to ill health.
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Affiliation(s)
- Ijeoma Edoka
- PRICELESS SA, Wits School of Public Health, University of the Witwatersrand, Johannesburg, South Africa.
| | - Barbara McPake
- Nossal Institute for Global Health, University of Melbourne, Australia and Institute for Global Health and Development, Queen Margaret University Edinburgh, Edinburgh, UK
| | - Tim Ensor
- Institute of Health Sciences, University of Leeds, Leeds, UK
| | - Rogers Amara
- ReBUILD Consortium, College of Medicine and Allied Health Sciences, University of Sierra Leone, Freetown, Sierra Leone
| | - Joseph Edem-Hotah
- ReBUILD Consortium, College of Medicine and Allied Health Sciences, University of Sierra Leone, Freetown, Sierra Leone
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19
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Ensor T, Chhun C, Kimsun T, McPake B, Edoka I. Impact of health financing policies in Cambodia: A 20 year experience. Soc Sci Med 2017; 177:118-126. [PMID: 28161669 DOI: 10.1016/j.socscimed.2017.01.034] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2016] [Revised: 12/12/2016] [Accepted: 01/22/2017] [Indexed: 11/28/2022]
Abstract
Improving financial access to services is an essential part of extending universal health coverage in low resource settings. In Cambodia, high out of pocket spending and low levels of utilisation have impeded the expansion of coverage and improvement in health outcomes. For twenty years a series of health financing policies have focused on mitigating costs to increase access particularly by vulnerable groups. Demand side financing policies including health equity funds, vouchers and community health insurance have been complemented by supply side measures to improve service delivery incentives through contracting. Multiple rounds of the Cambodia Socio-Economic Survey are used to investigate the impact of financing policies on health service utilisation and out of pocket payments both over time using commune panel data from 1997 to 2011 and across groups using individual data from 2004 and 2009. Policy combinations including areas with multiple interventions were examined against controls using difference-in-difference and panel estimation. Widespread roll-out of financing policies combined with user charge formalisation has led to a general reduction in health spending by the poor. Equity funds are associated with a reduction in out of pocket payments although the effect of donor schemes is larger than those financed by government. Vouchers, which are aimed only at reproductive health services, has a more modest impact that is enhanced when combined with other schemes. At the aggregate level changes are less pronounced although there is evidence that policies take a number of years to have substantial effect. Health financing policies and the supportive systems that they require provide a foundation for more radical extension of coverage already envisaged by a proposed social insurance system. A policy challenge is how disparate mechanisms can be integrated to ensure that vulnerable groups remain protected.
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Affiliation(s)
- Tim Ensor
- University of Leeds, United Kingdom.
| | - Chhim Chhun
- Cambodia Development Resource Institute, Cambodia.
| | - Ton Kimsun
- Cambodia Development Resource Institute, Cambodia.
| | | | - Ijeoma Edoka
- PRICELESS, School of Public Health University of the Witwatersrand, South Africa.
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20
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Doherty JE, Wilkinson T, Edoka I, Hofman K. Strengthening expertise for health technology assessment and priority-setting in Africa. Glob Health Action 2017; 10:1370194. [PMID: 29035166 PMCID: PMC5700536 DOI: 10.1080/16549716.2017.1370194] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2017] [Accepted: 08/17/2017] [Indexed: 11/07/2022] Open
Abstract
BACKGROUND Achieving sustainable universal health coverage depends partly on fair priority-setting processes that ensure countries spend scarce resources wisely. While general health economics capacity-strengthening initiatives exist in Africa, less attention has been paid to developing the capacity of individuals, institutions and networks to apply economic evaluation in support of health technology assessment and effective priority-setting. OBJECTIVE On the basis of international lessons, to identify how research organisations and partnerships could contribute to capacity strengthening for health technology assessment and priority-setting in Africa. METHODS A rapid scan was conducted of international formal and grey literature and lessons extracted from the deliberations of two international and regional workshops relating to capacity-building for health technology assessment. 'Capacity' was defined in broad terms, including a conducive political environment, strong public institutional capacity to drive priority-setting, effective networking between experts, strong research organisations and skilled researchers. RESULTS Effective priority-setting requires more than high quality economic research. Researchers have to engage with an array of stakeholders, network closely other research organisations, build partnerships with different levels of government and train the future generation of researchers and policy-makers. In low- and middle-income countries where there are seldom government units or agencies dedicated to health technology assessment, they also have to support the development of an effective priority-setting process that is sensitive to societal and government needs and priorities. CONCLUSIONS Research organisations have an important role to play in contributing to the development of health technology assessment and priority-setting capacity. In Africa, where there are resource and capacity challenges, effective partnerships between local and international researchers, and with key government stakeholders, can leverage existing skills and knowledge to generate a critical mass of individuals and institutions. These would help to meet the priority-setting needs of African countries and contribute to sustainable universal health coverage.
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Affiliation(s)
- Jane E Doherty
- School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Parktown, Johannesburg, South Africa
| | - Thomas Wilkinson
- PRICELESS SA (Priority Cost-Effective Lessons for Systems Strengthening South Africa), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Parktown, Johannesburg, South Africa
| | - Ijeoma Edoka
- PRICELESS SA (Priority Cost-Effective Lessons for Systems Strengthening South Africa), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Parktown, Johannesburg, South Africa
| | - Karen Hofman
- PRICELESS SA (Priority Cost-Effective Lessons for Systems Strengthening South Africa), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Parktown, Johannesburg, South Africa
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21
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Edoka I, Ensor T, McPake B, Amara R, Tseng FM, Edem-Hotah J. Free health care for under-fives, expectant and recent mothers? Evaluating the impact of Sierra Leone's free health care initiative. Health Econ Rev 2016; 6:19. [PMID: 27215909 PMCID: PMC4877339 DOI: 10.1186/s13561-016-0096-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/07/2016] [Accepted: 05/13/2016] [Indexed: 06/05/2023]
Abstract
This study evaluates the impact of Sierra Leone's 2010 Free Health Care Initiative (FHCI). It uses two nationally representative surveys to identify the impact of the policy on utilisation of maternal care services by pregnant women and recent mothers as well as the impact on curative health care services and out-of-pocket payments for consultation and prescription in children under the age of 5 years. A Regression Discontinuity Design (RDD) is applied in the case of young children and a before-after estimation approach, adjusted for time trends in the case of expectant and recent mothers. Our results suggest that children affected by the FHCI have a lower probability of incurring any health expenditure in public, non-governmental and missionary health facilities. However, a proportion of eligible children are observed to incur some health expenditure in participating facilities with no impact of the policy on the level of out-of-pocket health expenditure. Similarly, no impact is observed with the utilisation of services in these facilities. Utilisation of informal care is observed to be higher among non-eligible children while in expectant and recent mothers, we find substantial but possibly transient increases in the use of key maternal health care services in public facilities following the implementation of the FHCI. The diminishing impact on utilisation mirrors experience in other countries that have implemented free health care initiatives and demonstrates the need for greater domestic and international efforts to ensure that resources are sufficient to meet increasing demand and monitor the long run impact of these policies.
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Affiliation(s)
- Ijeoma Edoka
- PRICELESS, Wits School of Public Health, Johannesburg, South Africa.
| | - Tim Ensor
- Institute of Health Sciences, University of Leeds, Leeds, UK
| | - Barbara McPake
- Institute for Global Health and Development, Queen Margaret University Edinburgh, Edinburgh, UK
- Nossal Institute for Global Health, University of Melbourne, Melbourne, Australia
| | - Rogers Amara
- Rebuild Consortium, College of Medicine and Allied Health Sciences, University of Sierra Leone, Freetown, Sierra Leone
| | - Fu-Min Tseng
- Department of Surgery and Cancer, Imperial College London, London, UK
| | - Joseph Edem-Hotah
- Rebuild Consortium, College of Medicine and Allied Health Sciences, University of Sierra Leone, Freetown, Sierra Leone
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22
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McPake B, Edoka I, Witter S, Kielmann K, Taegtmeyer M, Dieleman M, Vaughan K, Gama E, Kok M, Datiko D, Otiso L, Ahmed R, Squires N, Suraratdecha C, Cometto G. Cost-effectiveness of community-based practitioner programmes in Ethiopia, Indonesia and Kenya. Bull World Health Organ 2015; 93:631-639A. [PMID: 26478627 PMCID: PMC4581637 DOI: 10.2471/blt.14.144899] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2014] [Revised: 03/05/2015] [Accepted: 06/19/2015] [Indexed: 11/27/2022] Open
Abstract
OBJECTIVE To assess the cost-effectiveness of community-based practitioner programmes in Ethiopia, Indonesia and Kenya. METHODS Incremental cost-effectiveness ratios for the three programmes were estimated from a government perspective. Cost data were collected for 2012. Life years gained were estimated based on coverage of reproductive, maternal, neonatal and child health services. For Ethiopia and Kenya, estimates of coverage before and after the implementation of the programme were obtained from empirical studies. For Indonesia, coverage of health service interventions was estimated from routine data. We used the Lives Saved Tool to estimate the number of lives saved from changes in reproductive, maternal, neonatal and child health-service coverage. Gross domestic product per capita was used as the reference willingness-to-pay threshold value. FINDINGS The estimated incremental cost per life year gained was 82 international dollars ($)in Kenya, $999 in Ethiopia and $3396 in Indonesia. The results were most sensitive to uncertainty in the estimates of life-years gained. Based on the results of probabilistic sensitivity analysis, there was greater than 80% certainty that each programme was cost-effective. CONCLUSION Community-based approaches are likely to be cost-effective for delivery of some essential health interventions where community-based practitioners operate within an integrated team supported by the health system. Community-based practitioners may be most appropriate in rural poor communities that have limited access to more qualified health professionals. Further research is required to understand which programmatic design features are critical to effectiveness.
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Affiliation(s)
- Barbara McPake
- Nossal Institute for Global Health, University of Melbourne, Melbourne, Australia
| | - Ijeoma Edoka
- Institute for International Health & Development, Queen Margaret University, Queen Margaret Drive Musselburgh, Edinburgh EH21 6UU, Scotland
| | - Sophie Witter
- Institute for International Health & Development, Queen Margaret University, Queen Margaret Drive Musselburgh, Edinburgh EH21 6UU, Scotland
| | - Karina Kielmann
- Institute for International Health & Development, Queen Margaret University, Queen Margaret Drive Musselburgh, Edinburgh EH21 6UU, Scotland
| | - Miriam Taegtmeyer
- Department of International Public Health, Liverpool School of Tropical Medicine, Liverpool, England
| | | | | | - Elvis Gama
- Department of International Public Health, Liverpool School of Tropical Medicine, Liverpool, England
| | - Maryse Kok
- Royal Tropical Institute, Amsterdam, Netherlands
| | - Daniel Datiko
- REACHOUT, Hidase Hulentenawi Agelglot Yebego Adragot Mahber, Awassa, Ethiopia
| | | | - Rukhsana Ahmed
- Department of International Public Health, Liverpool School of Tropical Medicine, Liverpool, England
| | - Neil Squires
- Public Health England, North of England Region, England
| | - Chutima Suraratdecha
- United States Agency for International Development, Washington, DC, United States of America
| | - Giorgio Cometto
- Global Health Workforce Alliance, World Health Organization, Geneva, Switzerland
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23
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McPake B, Edoka I. Universal health coverage reforms: implications for the distribution of the health workforce in low-and middle-income countriess. WHO South East Asia J Public Health 2014; 3:213-218. [PMID: 28612805 DOI: 10.4103/2224-3151.206743] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
To achieve universal health coverage (UHC), a range of health-financing reforms, including removal of user fees and the expansion of social health insurance, have been implemented in many countries. While the focus of much research and discussion on UHC has been on the impact of health-financing reforms on population coverage, health-service utilization and out-of-pocket payments, the implications of such reforms for the distribution and performance of the health workforce have often been overlooked. Shortages and geographical imbalances in the distribution of skilled health workers persist in many low- and middle-income countries, posing a threat to achieving UHC. This paper suggests that there are risks associated with health-financing reforms, for the geographical distribution and performance of the health workforce. These risks require greater attention if poor and rural populations are to benefit from expanded financial protection.
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Affiliation(s)
- Barbara McPake
- Nossal Institute for Global Health, Melbourne School of Population and Global Health, University of Melbourne, Australia; Institute for International Health and Development, Queen Margaret University, Edinburgh, United Kingdom of Great Britain and Northern Ireland
| | - Ijeoma Edoka
- Institute for International Health and Development, Queen Margaret University, Edinburgh, United Kingdom of Great Britain and Northern Ireland
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