文献：Ortegón M et al.Cost effectiveness of strategies to combat cardiovascular disease, diabetes, and tobacco use in sub-Saharan Africa and South East Asia: mathematical modelling study.BMJ 2012;344:e607.
Cost effectiveness of strategies to combat cardiovascular disease, diabetes, and tobacco use in sub-Saharan Africa and South East Asia: mathematical modelling study
BMJ2012;344doi: 10.1136/bmj.e607(Published 2 March 2012)
Cite this as:BMJ2012;344:e607
・Drugs: cardiovascular system
・Evidence based practice
・Health service research
・Screening (public health)
・Smoking and tobacco
1.Mónica Ortegón, researcher1,
2.Stephen Lim, associate professor of global health2,
3.Dan Chisholm, health economist3,
4.Shanthi Mendis, coordinator4
1.1School of Medicine and Health Sciences, Universidad del Rosario, Bogotá, Colombia
2.2Institute for Health Metrics and Evaluation, University of Washington, Seattle, USA
3.3Department of Health Systems Financing, World Health Organization, Geneva, Switzerland
4.4Department of Chronic Diseases and Health Promotion, World Health Organization, Geneva
Correspondence to: M Ortegón Carrera 24 # 63C-69 Bogotá, Colombia email@example.com
・Accepted 26 October 2011
Objective To determine the relative costs and health effects of interventions to combat cardiovascular disease, diabetes, and tobacco related disease in order to guide the allocation of resources in developing countries.
Design Cost effectiveness analysis of 123 single or combined prevention and treatment strategies for cardiovascular disease, diabetes, and smoking by means of a lifetime population model.
Setting Two World Health Organization sub-regions of the world: countries in sub-Saharan Africa with very high adult and high child mortality (AfrE) and countries in South East Asia with high adult and high child mortality (SearD).
Data sources Demographic and epidemiological data were taken from the WHO databases of mortality and global burden of disease. Estimates of intervention coverage, effectiveness, and resource needs were drawn from clinical trials, observational studies, and treatment guidelines. Unit costs were taken from the WHO-CHOICE (Choosing Interventions that are Cost-Effective) price database.
Main outcome measures Cost per disability adjusted life year (DALY) averted, expressed in international dollars ($Int) for the year 2005.
Results Most of the interventions studied were considered highly cost effective, meaning they generate one healthy year of life at a cost of <$Int2000 (which is the gross domestic product per capita of the two regions considered here). Interventions that offer particularly good monetary value, and which could be considered for prioritised implementation or scale up, include demand reduction strategies of the Framework Convention for Tobacco Control (<$Int950 and <$Int200 per DALY averted in AfrE and SearD respectively); combination drug therapy for people with a >25% chance of experiencing a cardiovascular event over the next decade, either alone or together with specific multidrug regimens for the secondary prevention of post-acute ischaemic heart disease and stroke (<$Int150 and <$Int230 per DALY averted in AfrE and SearD respectively); and retinopathy screening and glycaemic control for patients with diabetes (<$Int2100 and <$Int950 per DALY averted in AfrE and SearD respectively).
Conclusion This comparative economic assessment has identified a set of population-wide and individual strategies for prevention and control of cardiovascular disease that are inexpensive and cost effective in low resource settings.
There is growing concern about the escalating burden of non-communicable diseases and injuries throughout the world, from both epidemiological and economic perspectives. Lives lost to diseases such as cancer, cardiovascular disease, and diabetes—together with the often longstanding disability associated with them—have an economic impact on households and communities, both through the uptake of health services and goods that diverts expenditure away from other possible uses and through loss of income or labour productivity.1 2 Despite these adverse consequences on health and economic welfare, non-communicable diseases and injuries have been neglected in international health and development initiatives. The recent high level meeting on non-communicable diseases at a special session of the United Nations General Assembly and the subsequent political declaration3 provides a political mandate and an unprecedented opportunity to develop an international policy framework for the prevention and control of non-communicable diseases. A key action in support of this strategy is the evidence on the interventions that work best at the lowest cost in the prevention and control of non-communicable disease and injuries, in developing regions with a high disease burden.
In this series of articles we examine the relative cost effectiveness of a comprehensive set of interventions and strategies for combating major non-communicable diseases and injury in economically developing regions of the world: this paper covers cardiovascular disease and some of its key risk factors (including raised blood pressure, raised blood cholesterol, and tobacco use), and the others assess respiratory disease (asthma and chronic obstructive pulmonary disease), cancer (of the breast, cervix, and colon or rectum), neuropsychiatric disorders (schizophrenia, bipolar affective disorder, depression, harmful alcohol use, and epilepsy), sense organ diseases (including cataract, trachoma, refractive error, and hearing loss), and road traffic injury.4 5 6 7 8 Although this list leaves some gaps in the diseases covered—musculoskeletal diseases and blood disorders, for example—these analyses provide the largest available database of comparable cost effectiveness estimates, which a final paper uses to identify key priorities for the prevention and control of non-communicable diseases and injuries.9 We also provide a companion paper that shows the use of these methods at the country level (Mexico), as opposed to the level of epidemiologically defined World Health Organization sub-regions.10
Cardiovascular disease is the single largest cause of mortality worldwide, accounting for 17 million deaths, equivalent to 29% of all deaths annually. We cover primary prevention efforts at both the population level (such as tobacco control measures, reduced dietary salt intake) and at the individual level (such as control of hypertension or blood cholesterol with drugs and combination drug therapy for individuals at high risk of a cardiovascular event) as well as secondary and tertiary prevention or management of ischaemic heart disease and stroke. We also include the management (but not prevention) of another major cardiovascular risk factor, namely diabetes and its associated complications (which account for more than another million deaths worldwide each year). Intervention cost effectiveness results for two further cardiovascular risk factors—unhealthy diet and physical inactivity—have recently been reported elsewhere for a set of (mainly middle income) countries,11 but are not integrated into our analysis because of differences in the modelling environment adopted.
This analysis follows the standardised methodology on cost effectiveness analysis set forth by the WHO-CHOICE project12 13 14 and builds on previous analyses of public health interventions to lower systolic blood pressure and cholesterol15 and of tobacco use.16 We provide an overview of the methods and data used to carry out and update these earlier analyses and a more detailed description of modelling assumptions and data sources adopted for previously unpublished analyses (management of cardiovascular disease and diabetes).
In common with other papers in this and a previous WHO-CHOICE series,17 cost effectiveness modelling was carried out for two WHO reporting sub-regions, one in Africa (countries with high child and very high adult mortality, henceforth denoted “AfrE”) and the other in South East Asia (countries with high child and adult mortality, henceforth denoted “SearD”). Information on the countries pertaining to these two WHO epidemiological sub regions can be found in appendix 1 on bmj.com. Results for other WHO reporting regions can be viewed at the WHO-CHOICE website (www.who.int/choice); the models used have been designed for subsequent contextualisation by individual member states.
A range of strategies for prevention and control were considered; where it was clinically meaningful to do so, we also assessed combination strategies. Table 1⇓ lists all single interventions included in this analysis. Interventions were selected according to the strength of evidence supporting their effectiveness as well as recommendations from published guidelines (see appendices 2–4 on bmj.com). Effectiveness of interventions was sought using the best available evidence reported in international literature. Source data for intervention effectiveness included meta-analyses, systematic reviews, clinical trials, and observational studies (appendices 2–4).
View this table:
List of single interventions considered in cost effectiveness analysis of strategies to combat cardiovascular disease, diabetes, and tobacco related disease in WHO sub-Saharan African sub-region AfrE and South East Asian sub-region SearD
Tobacco control strategies—Prevention of cardiovascular disease—as well as lung cancer and chronic obstructive pulmonary disease—via enhanced tobacco control efforts included key strategies of the WHO Framework Convention for Tobacco Control to reduce demand (current and increased taxation, legislated restrictions on smoking in public places, comprehensive bans on advertising of tobacco products, information dissemination through health warning labels, counter advertising, and various consumer information packages). Personal health interventions include nicotine replacement therapy and physician advice. Appendix 2 on bmj.com documents the efficacy, non-compliance, and target coverage levels of these measures.
Cardiovascular disease interventions—Primary prevention strategies cover both population-wide and individual level interventions aimed at reducing the risk of coronary heart disease and cerebrovascular disease through the voluntary or regulated reduction in dietary salt intake, control of blood pressure and cholesterol with drugs, and combination drug therapy for people at an absolute (as opposed to relative) risk of experiencing a cardiovascular disease event over the next 10 years >25%.15 The multidrug regimen consisted of four generic drugs—a β blocker, a diuretic, a statin, and aspirin (because of the risk of gastrointestinal bleeding in a group of patients, debate continues about the overall risk:benefit ratio of aspirin in primary prevention of cardiovascular disease). Management strategies focus on acute care of myocardial infarction and stroke in the inpatient setting, covering both surgical and drug interventions. Secondary and tertiary prevention interventions concern the long term treatment of patients with a previous myocardial infarction or stroke with the aim of reducing the risk of a subsequent event and the occurrence of more severe stages of the disease. Interventions for the management of symptomatic left ventricular systolic dysfunction in patients with a previous myocardial infarction are also included since this condition is common in patients with a previous myocardial infarction. Heart failure interventions are intended for patients in stage C of the disease according to the American College of Cardiology and American Heart Association classification of chronic heart failure progression.18 Appendix 3 on bmj.com provides a list of the cardiovascular disease intervention strategies assessed, together with estimates of their effect on reducing the risk, incidence or fatality of disease. All interventions were assessed at a treatment coverage level of 80%.
Diabetes interventions—For managing type 1 and type 2 diabetes, we focused on diabetes cases and the sequelae covered by the Global Burden of Disease study (blindness due to retinopathy, neuropathy, and diabetic foot and amputation).19 Key interventions assessed were standard and intensive approaches to glycaemic control, screening for retinopathy and subsequent treatment as needed, and screening for neuropathy plus associated preventive foot care (appendix 4 on bmj.com provides a more detailed description of these interventions and how they were modelled). A uniform 80% treatment coverage was also used in order to facilitate comparison with cardiovascular disease results.
The large majority of interventions analysed are drug based. Current availability of drugs to treat chronic diseases ranges from 36% to 55% in low and middle income countries in the public and private sector, respectively.20 In Bangladesh, Malawi, and Nepal—specific countries in the regions studied—the availability of chronic disease drugs ranges from 5% to 37.5%.21 Cardiac units to perform angioplasty are available in hospitals in the following countries in AfrE: Kenya, Tanzania, Mozambique, South Africa, and Ivory Coast.22 Taking India as a country example for SearD, there are 220 hospitals capable of performing percutaneous angioplasty, located in the main cities.23
We have not been able to include all possible interventions in this analysis because of lack of information on either the impact of the treatment or the underlying epidemiological data required for determining treatment effectiveness. Renal disease and cardiovascular disease, for example, were not specified as sequelae for diabetes in the Global Burden of Disease study of 2004, so we have not assessed key interventions relating to them (including the prevention of diabetes through reduction of risk of cardiovascular disease, management of cardiovascular complications among diabetic patients, and treatment of diabetic nephropathy with angiotensin converting enzyme (ACE) inhibitors). Other excluded interventions that may have a positive health impact include those for preventing rheumatic heart disease or angina pectoris and treatment of refractory end stage heart failure, early diastolic and systolic dysfunction, and concomitant diseases such as arrhythmia and cardiac valve disorders. The treatment of complications of acute events (hypotension, pulmonary congestion, cardiogenic shock, etc) and diagnostic or prognostic interventions performed during management of an acute event were beyond the scope of this analysis.
WHO-CHOICE employs an epidemiological, population based approach to the assessment of health outcomes (see general appendix on bmj.com). Along with background birth, population, and mortality rates, observed rates of disease incidence, prevalence, and mortality—drawn from the Global Burden of Disease database19 and shown in table 2⇓—are entered into a state transition model in order to establish the total number of years of healthy life experienced over the (100 year) lifetime of a defined population.24 The model is successively run in order to calculate the additional number of healthy years lived by the population—equivalent to the number of disability adjusted life years (DALYs) averted—after the implementation of a single or combined health intervention, compared with a baseline or null scenario of no interventions for the disease in question. This null scenario was determined by back calculating incidence and case fatality rates using intervention effect sizes and current coverage rates (that is, epidemiological rates are adjusted upwards to reflect the absence of any effective intervention). Interventions are taken to be implemented for a period of 10 years, after which epidemiological rates go back to their counterfactual level of no intervention. Consistent with the WHO Global Burden of Disease study, DALYs are discounted (at 3% per year) and age weighted.
View this table:
Main epidemiological parameters used in analysis of cardiovascular disease, diabetes, and tobacco related disease rates in WHO sub-Saharan African sub-region AfrE and South East Asian sub-region SearD*
The specific benefits of tobacco control measures on population health were estimated through the impact of reduced smoking on the tobacco attributable incidence of cardiovascular disease, respiratory disease, and mortality from various forms of cancer. We modelled the increase in taxation that would reduce smoking prevalence by 10% on the basis of data on tobacco taxation from previous WHO and World Bank studies.25 The effect of price changes on consumption was estimated from information about price elasticities of demand for tobacco products (the percentage change in consumption resulting from a 1% increase in price). For a 10% rise in price due to tobacco taxes, consumption generally falls by 8–10% in low and middle income countries.26 27 We calculated that the prevalence elasticity (the percentage change in smoking prevalence resulting from a 1% increase in price) was half the total price elasticity of demand, because at least half of the estimated effect on the demand for tobacco products results from a reduction in smoking prevalence.28 Given that current smoking prevalence is a poor proxy for the accumulated health risks of tobacco use, we used the smoking impact ratio as a marker for cumulative smoking risk.29 The smoking impact ratio captures the accumulated hazards of smoking by converting the smokers in the population analysed into equivalents of smokers in a reference population, where hazards for other diseases have been measured. The reference population used in our case was the CPS II cohort.30 We used relative risks in estimating tobacco attributable morbidity and mortality. Intervention effectiveness was assessed through changes in smoking impact ratio and relative risks of mortality and morbidity from tobacco related diseases per unit of smoking impact ratio (see table 3⇓ for relative risk values used in the analysis).
View this table:
Relative risks for disease (per unit increase in risk factor) used in analysis of cardiovascular disease, diabetes, and tobacco related disease rates in WHO sub-Saharan African sub-region AfrE and South East Asian sub-region SearD*
For the primary prevention of cardiovascular disease, health effects were modelled by stochastically simulating populations specific for age and sex with the observed baseline values of ischaemic heart disease and stroke incidence and the observed distribution of risk factors (systolic blood pressure, serum cholesterol, body mass index, and prevalence of long term smokers15) (see table 2⇑). Incidence risk is apportioned between individuals using estimates of the relative risk of modelled risk factors on cardiovascular events (table 3⇑). Population level incidence of ischaemic heart disease and stroke is recalculated after applying the impact of the intervention on the individual risk factor values for those receiving the intervention.
For acute myocardial infarction and stroke, health effects were modelled through their impact on case fatality in hospital and after discharge up to 28 days after the event (out of hospital case fatality rates were assumed to remain unchanged). Secondary and tertiary prevention interventions were modelled through their impact on post-28 day case fatality rates for each condition and the rate of complications attributable to ischaemic heart disease (angina, congestive heart failure). The interaction in risk between ischaemic heart disease and stroke was modelled using estimates of relative risk of stroke for those with previous ischaemic heart disease and vice versa from published epidemiological studies (see appendix 3 on bmj.com).
Finally, for managing diabetes and its complications, intervention health effects were expressed in terms of composite disability weights that reflect varying distributions of different health states (diabetes without complications, neuropathy, lower extremity amputation, background retinopathy, proliferative diabetic retinopathy plus macular oedema, and blindness due to retinopathy). These six disease states reflect the progression of diabetes along the long term consequences of eye and foot disease. To derive a composite disability weight for each intervention, we simulated the evolution of a closed population cohort of people aged >15 years over 100 years via a health state model (MiniMod, see appendix 4 on bmj.com for further details).
We pursued an ingredients approach to costing, meaning that information on the quantities of all services and goods required for the delivery of an intervention as well as data on their unit costs were sought. The total cost of an intervention is the product of these quantities and their respective unit costs. Particular attention was given to maintaining consistency of the information on resource use with that described in the articles selected as source of effectiveness for the interventions. Costs were calculated for a 10 year period of implementation (subsequently discounted annually by 3%) and expressed in international dollars for 2005. An international dollar is a hypothetical currency that is used as a means of comparing costs taking into account differences in purchasing power. One international dollar ($Int1) buys the same quantity of healthcare resources in Kenya or India as it does in the United States. As reference, $Int1 is worth US$0.44 and US$0.32 in sub-Saharan Africa and South East Asia regions, respectively. We considered both patient and programme costs. Patient costs included drugs, laboratory tests, and inpatient and outpatient visits. A detailed description of resource quantities used at the patient level is given for each diabetes intervention in appendix 4 and for each cardiovascular disease intervention in appendix 5 on bmj.com. Programme costs included all resources required for the implementation and maintenance of interventions, such as administration and planning, media and communications, law enforcement activities, training, evaluation, and monitoring. Population-wide measures for reducing salt intake or tobacco use involve costs exclusively at the programme level and are documented elsewhere.25 Costing of these interventions was performed using WHO-CHOICE programme costing templates and world regional pricing databases (www.who.int/choice).
Handling of cost effectiveness data and uncertainty
Dividing the total implementation costs of each intervention by its effects generates a simple cost effectiveness ratio, relative to a comparator situation of no intervention. In addition to average cost effectiveness ratios, incremental cost effectiveness ratios are reported for the successive set of interventions that would be selected at expanding levels of resource availability, starting with the intervention with the lowest cost per DALY averted, then moving to the next most cost effective combination intervention out of the remaining available set of interventions. An intervention that is more costly or less effective than other more efficient interventions is denoted as dominated.
All interventions are imbued with a certain degree of uncertainty. To handle this aspect of reporting for such a wide range of interventions, we first placed intervention results on a logarithmic scale, with a view to ascertaining order of magnitude differences in cost effectiveness (such as $Int10–100 versus $Int100–1000 per DALY averted). Secondly, we categorised results according to a defined set of cost effectiveness thresholds: WHO-CHOICE denotes an intervention as “cost effective” if it produces a healthy year of life for less than three times the gross domestic product (GDP) per capita, and as “very cost effective” if it produces a healthy year of life for less than the GDP per capita. Finally, for the subset of intervention strategies that were not dominated by others and therefore fall on the cost effectiveness frontier, we undertook a probabilistic uncertainty analysis using the MCLeague software program.32 We also assessed the impact of removing age weights or discounting on baseline results via one way sensitivity analysis.
A total of 123 single and combined intervention strategies were assessed (36 for tobacco control, 77 for cardiovascular disease, and 10 for diabetes). The annual cost, effect, and cost effectiveness for all interventions are provided in appendix 6 on bmj.com, and are shown graphically in figures 1⇓ and 2⇓. Costs ($Int) and effects (DALYs averted) have been calculated for a standardised population of one million people to allow for easier comparison between different geographical regions