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Health Aff (Millwood). Author manuscript; available in PMC 2016 September 01. Published in final edited form as: Health Aff (Millwood). 2015 September ; 34(9): 1538–1545. doi:10.1377/hlthaff.2015.0349.
Cardiovascular Disease Screening By Community Health Workers Can Be Cost-Effective In Low-Resource Countries Thomas Gaziano, Assistant professor in the Cardiovascular Division of Brigham and Women’s Hospital, in Boston, Massachusetts
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Shafika Abrahams-Gessel, Research manager at the Center for Health Decision Science in the Harvard T. H. Chan School of Public Health, in Boston Sam Surka, Researcher in the Chronic Diseases Initiative for Africa at Old Groote Schuur Hospital, in Cape Town, South Africa Stephen Sy, Programmer at the Center for Health Decision Science in the Harvard T. H. Chan School of Public Health Ankur Pandya, Assistant professor of health policy and management at the Harvard T. H. Chan School of Public Health
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Catalina A. Denman, Professor in the Centro de Estudios en Salud y Sociedad at El Colegio de Sonora, in Hermosillo, Mexico Carlos Mendoza, Coinvestigator at the Instituto de Nutricion de Centro America y Panama, in Guatemala City, Guatemala Thandi Puoane, and Professor in the School of Public Health at the University of the Western Cape, in Bellville, South Africa
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Naomi S. Levitt Director of the Division of Diabetes and the Chronic Diseases Initiative for Africa, both at Old Groote Schuur Hospital Thomas Gaziano: [email protected]
Abstract In low-resource settings, a physician is not always available. We recently demonstrated that community health workers—instead of physicians or nurses—can efficiently screen adults for cardiovascular disease in South Africa, Mexico, and Guatemala. In this analysis we sought to determine the health and economic impacts of shifting this screening to community health workers equipped with either a paper-based or a mobile phone–based screening tool. We found that
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screening by community health workers was very cost-effective or even cost-saving in all three countries, compared to the usual clinic-based screening. The mobile application emerged as the most cost-effective strategy because it could save more lives than the paper tool at minimal extra cost. Our modeling indicated that screening by community health workers, combined with improved treatment rates, would increase the number of deaths averted from 15,000 to 110,000, compared to standard care. Policy makers should promote greater acceptance of community health workers by both national populations and health professionals and should increase their commitment to treating cardiovascular disease and making medications available.
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Noncommunicable diseases cause the majority of death worldwide, with nearly 80 percent of these deaths occurring in low- and middle-income countries.1–3 Among noncommunicable diseases, cardiovascular disease is the leading cause of morbidity and mortality. The burden of cardiovascular disease is high in both high-income and low- and middle-income countries, but the future of that burden differs in the two groups of countries.1,4 In low- and middle-income countries, rates of cardiovascular disease are increasing, and it is the leading cause of death—especially of premature deaths, of which 82 percent are the result of cardiovascular disease.5 For example, South Africa has one of the most quickly increasing cardiovascular disease death rates in the world, and the rate of premature death in South African adults as a result of cardiovascular disease is projected to increase by 41 percent between 2000 and 2030.6 Although preventive treatment is available at low cost in many low- and middle-income countries, as few as 10 percent of the people in those countries receive recommended care. Significant gaps occur between developing countries in disease awareness, treatment, control, and continuity of treatment.7
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In contrast, in high-income countries such as the United States, age-adjusted mortality rates per 100,000 population from ischemic heart disease declined from 419 in 1983 to 103 in 2013. Half of this reduction can be attributed to improved primary prevention actions (actions to prevent disease before it occurs), including effective population screening and treatment programs.8–10 Reductions in mortality rates for chronic conditions require awareness of the condition, initiation of treatment when the condition is identified, and control of the condition through appropriate follow-up.
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Barriers to improving control rates for those at high risk for cardiovascular disease include health worker shortages, crowded primary health centers, and high costs associated with traditional screening programs. Shifting some of the responsibilities for hypertension and diabetes screening from doctors to nurses has been shown to improve quality of care and reduce costs.11 Even more shifting, from nurses to community health workers, is needed. Community health workers in low- and middle-income countries are typically lay people with no formal professional training in health service delivery who are selected to serve members of the communities in which they reside. The evidence for the cost-effectiveness of shifting the task of primary screening for cardiovascular disease to community health workers in low- and middle-income countries is very limited.12,13
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We recently demonstrated that community health workers in South Africa, Mexico, and Guatemala can screen for cardiovascular disease risk as effectively as physicians or nurses can, by using a previously validated inexpensive nonlaboratory paper-based screening tool.14,15 The paper tool was subsequently converted into a mobile phone–based application. Compared to community health workers who used the paper tool, those who used the mobile application were trained in less time, took fifteen minutes less on average to conduct a screening, and had a lower error rate in cardiovascular disease risk assessment measurements.16 Approximately30–70percent of individuals identified as high risk sought care at primary health centers, where a high percentage were started on appropriate treatment for their cardiovascular disease risk factors.17
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Mexico and other countries have invested in community health workers, so they can take on some parts of the management of noncommunicable diseases.18 The government of South Africa is restructuring its primary health care program, in part by training and deploying 700,000 community health workers by 2030, with the goal of better integrating them into the overall health system.19,20 Two issues have not yet been evaluated: Which roles would be most appropriate for newly trained community health workers, and how can they best be integrated into the overall health system? We evaluated the potential cost-effectiveness of using community health workers to screen for cardiovascular disease in community settings using a paper-based tool or a mobile app and to refer people at high risk to primary health centers for further evaluation and treatment in Guatemala, Mexico, and South Africa.
Study Data And Methods Author Manuscript
To assess the benefits, risks, and costs of two interventions to increase screening for cardiovascular disease by community health workers, we used an established microsimulation cardiovascular disease policy model developed with age-varying probabilities of cardiovascular disease events. The first intervention trained community health workers to use a simple nonlaboratory, paper-based cardiovascular disease risk chart in community settings. The second intervention trained the workers to use the same risk chart embedded in a mobile application. In both interventions, community health workers referred people with a five-year cardiovascular disease risk score of greater than 20 percent to the local primary health center for further evaluation and management. Both interventions were compared to the usual care of opportunistic screening at the primary health center.
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MODEL DESCRIPTION We used the cardiovascular disease policy model to project the lifetime health outcomes and costs related to cardiovascular disease of 1,000,000 hypothetical adults ages 35–74 with no prior history of stroke or ischemic heart disease in Guatemala, Mexico, and South Africa. This decision analytic model was based on a previously published cardiovascular disease model21–23 and is described in greater detail in the online Appendix.24
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The model was populated by a weighted sample of individuals from a previous community health worker study conducted in these three countries.14 Mean values for the risk factor distributions for the cohort for each country from the community health worker trial are listed in Appendix Exhibit A1.24 All other model parameters were estimated from published sources. Complete model inputs for the basic model structure, risk equations, and inputs unique to the interventions in each country, along with references for the published sources, are listed in the Appendix (Exhibits A2–8).24 KEY INTERVENTION ASSUMPTIONS AND PARAMETERS
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Given the average household size of 4 people (of whom 1.15 were estimated to be ages 35– 74),25 we assumed that each community health worker would be responsible for about 2,300 adults in that age range. Based on data from our previous studies,14,16 the model assumed that each worker would be able to screen seven adult community members per day with the paper-based intervention. Using the same data, the model assumed that each worker would be able to screen ten community members per day with the mobile application. Assuming that the workers devoted, on average, 20 percent of their time to prevention and screening, they would be able to screen either 336 or 480 new adults for cardiovascular disease per year using the paper tool or mobile application, respectively. That is, roughly 15 percent (paper) or 21 percent (mobile) of the local population would be screened over the course of a year. With a screening frequency of once every five years per adult, the workers would be able to screen the majority, if not all, of the community every five years.
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Screened people with a five-year cardiovascular disease risk score of greater than 20 percent would be referred to the primary health center for treatment with statins or hypertension medications as indicated. Our previous work established that of those referred to treatment, approximately 37 percent overall and 69 percent of those at highest risk actually visited a local clinic within the recommended two weeks of screening.17 However, each country has different rates of initiation for treatment with essential blood pressure medications or statins. We therefore used current treatment rate information for hypertension from published surveys for each country studied25–27 (Appendix Exhibit A7).24 Statin initiation data exist for secondary prevention (which attempts to reduce the impact of a disease on health), but data for primary prevention are sparse. We assumed that the initiation rate among people eligible to take statins would be half of that for blood pressure medications because simvastatin (a common and effective statin) has been on the essential drug list of the World Health Organization (WHO) only since 2009, and adoption in each country lags.
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We then conducted sensitivity analyses for rates of initiation both higher and lower than these values. Relative risk reductions for stroke and ischemic heart disease for those who are ultimately on either type of medication are listed in the Appendix (Exhibit A5).24 COSTS AND UTILITIES Estimated costs were the costs of care after acute myocardial infarction or stroke, the chronic care costs associated with surviving such acute events, treatment (including
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medications) for those identified at high risk for the events, and the training and screening costs associated with the intervention. The major inputs, including personnel costs, are reported in Appendix Exhibit A7.24 Whenever possible, we used country-level data; otherwise, we used international estimates. Costs of drugs commonly used for nonoptimal blood pressure were obtained from the International Drug Price Indicator Guide for Mexico and Guatemala.28 Health care delivery costs—salaries, health care visits, diagnostic tests, and hospital stays—are estimates from the WHO expressed in 2013 US dollars.29
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Costs of the intervention were the costs of training the community health workers to use the tools, of equipment, and of labor. The cost for a single visit to a public primary health center by people who were determined to be at high risk for cardiovascular disease and who followed through on the community health worker’s recommendation to see a health professional was determined using the latest WHO data (for 2008) for clinics without beds.29 Quality-of-life (that is, utility) decrements were applied to each year spent in cardiovascular disease event states and were based on quality-of-life estimates from the Medical Expenditure Panel Survey.30 BASE-CASE COST-EFFECTIVENESS ANALYSIS
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We projected the lifetime health care costs related to cardiovascular disease and qualityadjusted life-years (QALYs) accrued under usual care, the paper-based intervention, and the mobile app intervention. The three strategies were ranked by cost, and incremental costeffectiveness ratios were calculated. Inefficient strategies were ruled out if they had strong dominance (higher incremental costs and lower incremental QALYs) or weak dominance (both less effective and more costly than a linear combination of two other strategies) according to conventional cost-effectiveness analysis rules.31 Costs and QALYs were each adjusted with a discount rate of 3 percent, as recommended by the US Panel on Cost-Effectiveness in Health and Medicine.32 The discount rate takes into account the risk of future events and is used to determine the present value of future cash flows or health preferences. We used cost-effectiveness thresholds of one and three times the gross domestic product (GDP) per capita, respectively, for each country. SENSITIVITY ANALYSES
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We varied values for all variables (or groups of related variables) through plausible ranges, or used alternative values, to assess the robustness of our cost-effectiveness analysis results to changes in these input parameters. For example, we used a discount rate of up to 7 percent. LIMITATIONS The study had several limitations that should be noted. First, we assumed persistent statin and blood pressure medication benefits over the course of a lifetime for those who were
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eligible for and began using the medications, which is a common cardiovascular disease modeling assumption.33 Second, we were not sure of overall compliance rates with initiated medications in the three countries in our study. However, we used long-term compliance rates that declined over time to as low as 50 percent. Efforts to improve compliance at low costs would improve the cost-effectiveness of screening strategies followed by initiation of treatment. Third, we assumed that the time needed to screen individuals would be equivalent to the times we measured in our previous studies.16 It is possible that in some rural areas, where people live farther apart, travel time would increase the time required for in-home screening. However, screening time in rural areas may be reduced by conducting screenings at sites where members of the community congregate, such as churches or community centers.
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Finally, when cost information was not available for a specific country, we used international estimates for the countries, particularly for the cost of chronic care driven by international drug pricing estimates. For this reason, we ran sensitivity analyses on the cost of medications.
Study Results BASE-CASE ANALYSIS Both the paper and mobile app screening methods would lead to reductions in fatal and nonfatal stroke as well as coronary heart disease events, when compared to the usual standard of care. The rates differed by country, mainly because of varying rates of treatment initiation for those identified as high risk.
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Using the mobile app would save 471 lives in South Africa, 281 lives in Mexico, and 34 lives in Guatemala, per 210,000 adults screened (Exhibit 1). The screening cost would be approximately $1.00, $3.00, and $0.67 per screening, respectively (Appendix Exhibit A7).24 Similar numbers of nonfatal events would also be prevented in each country.
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Using the paper tool, 336 deaths in South Africa, 201 in Mexico, and 24 in Guatemala were averted per 150,000 adults screened (Exhibit 1). When we set an ideal treatment initiation rate of at least 75 percent for those with a cardiovascular disease risk above 20 percent, we found that approximately 800–1,200 cardiovascular disease deaths could be prevented per 200,000 adults screened across the three countries using the mobile app, with a similar number of nonfatal events averted. This ideal rate was based on upper limits for current use of antihypertensive medications in the United States.34 If the rate was applied to the whole country, there would be up to 40,000 deaths due to cardiovascular disease averted in South Africa, 110,000 in Mexico, and 15,000 in Guatemala. COST-EFFECTIVENESS ANALYSES Both intervention strategies added QALYs compared to the usual standard of care. However, the mobile application was the most cost-effective intervention, with an incremental cost-effectiveness ratio of $565 per QALY gained in Guatemala and $3.57 per
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QALY gained in Mexico (Exhibit 2). Use of the mobile application was cost-saving (it increased QALYs and reduced overall costs) in South Africa. When we compared the paperbased tool to the usual standard of care, the incremental cost-effectiveness ratios were approximately $47, $195, and $1,890 per QALY gained in South Africa, Mexico, and Guatemala, respectively (Appendix Exhibit A10).24 Increased efficiencies are also likely with the use of an electronic data collection system at a national level. We did not include these potential savings, so our estimates may be conservative. However, developing a national system would also have costs associated with it, and thus we cannot estimate the full effects. SENSITIVITY ANALYSES
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The strategies were not sensitive to the cost of the intervention across the range of estimated and calculated costs tested (Appendix Exhibit A9).24 However, the strategies were sensitive to the costs of the statins. At one-half of the base-case costs, the incremental costeffectiveness ratios in Guatemala and Mexico were reduced by nearly half for the mobile app, and the strategy remained cost-saving for South Africa (Exhibit 3). Using the upper limit of available generic pricing for atorvastatin of $149 per year, the ratios were $2,292, $2,329, and $5,035 per QALY gained for South Africa, Mexico, and Guatemala, respectively. The mobile application was still better than the paper application when we used discount rates of 4.5 percent35 and 7.0 percent (Appendix Exhibit A9).24
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All but one of the incremental cost-effectiveness ratios were well below the threshold of the GDP per capita in each of the three countries (Exhibit 4). Only at the highest cost estimate for atorvastatin in Guatemala was the ratio above that threshold, and even then it was below the threshold of three times the GDP per capita. When we used the GDP per capita threshold as a measure of willingness to pay, the results were not significantly sensitive to the initiation threshold for statins in primary prevention in the three countries. When we lowered the treatment threshold to a five-year cardiovascular risk score of greater than 10 percent, community health workers’ use of the mobile application remained the preferred strategy (Exhibit 3). There were offsetting costs: Increased numbers of people treated meant increased drug and outpatient costs but decreased costs from events averted. And there was decreased risk for the population as the threshold was lowered.
Discussion Author Manuscript
Our analyses show that having community health workers screen members of the community for high risk of cardiovascular disease with a simple noninvasive tool would cost relatively little to implement and would be highly cost-effective in three diverse low- and middle-income countries. The mobile application version of the tool is simple to learn and can be used with as little as four hours of training. Some countries may wish to use the paper-based tool first, which is cost-effective in the absence of mobile phone availability or network coverage. However, the mobile phone
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penetration rates (the number of mobile phones divided by the population) in the three study countries are 144 percent for Guatemala, 84 percent for Mexico, and 143 percent for South Africa, which suggests that the availability of mobile phones should not be a major limitation in at least the urban areas of these countries.36 Furthermore, when we included the cost of a mobile phone (approximately $20) in the three countries, the cost per screening changed by less than one cent.
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Our results show that while the intervention was cost-effective in Guatemala, it was less so than in South Africa and Mexico as a result of low drug treatment initiation rates. Countries must not only be committed to screening for chronic conditions, but they must also be committed to initiating treatment or other effective lifestyle interventions for people at high risk for cardiovascular disease. Treatment initiation barriers—particularly for statins, but also for blood pressure medications—include limited staff at primary health centers, the relatively recent addition of statins to the WHO’s essential medicines list, and lack of awareness and belief in the utility of medications for chronic conditions among the population.
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Effective screening interventions require increased commitment to treating chronic conditions and making low-cost medications available. They also require the acceptance of community health workers as an integral part of the health sector—by both other health professionals and community members—along with well-structured referral pathways. The rates at which referred people (those whose cardiovascular disease risk score was over 20 percent) completed a visit to a primary health center were as low as 33 percent in the three countries in our study.17 Formal studies are needed to evaluate how mobile health tools can also be used for improving referral rates and initiation of appropriate treatment at primary health centers.
Workforce Implications
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To scale the intervention to the national level, approximately 450 community health workers (90 full-time equivalents) per million people would be needed to screen the entire adult population. In South Africa this would mean up to 20,000 workers, which is a small proportion of the 700,000 positions for such workers proposed by the Republic of South Africa National Planning Commission.19 Costs per screened adult using the mobile application were $0.67 in Guatemala, $1.00 in South Africa, and $3.00 in Mexico. At these rates, depending on which version of the intervention was used, the overall annual cost would be $4–$8 million in South Africa, $0.5–$1 million in Guatemala, and $29–$47 million in Mexico. The differences across the countries reflect both the sizes of the populations and the higher wages paid in Mexico, compared to the other two countries. While the numbers of community health workers required are relatively small, the training and certification process to ensure quality needs to be addressed. Currently, there is no career path with certification processes for community health workers in any of the three countries we studied. We made many of our cost estimates based on the best available data. However, some cost data in particular were lacking in Mexico and Guatemala. We used international estimates Health Aff (Millwood). Author manuscript; available in PMC 2016 September 01.
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provided by the WHO and other organizations, but government policy makers should improve their cost accounting for health care expenditures to better understand the financial implications of certain interventions.
Conclusion
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Our analysis shows that having community health workers screen for noncommunicable diseases such as cardiovascular disease in the community can be highly cost-effective with the use of a simple noninvasive screening tool. Scaling the project to a national level would be reasonably inexpensive given current salaries for community health workers. Strengthening the referral process to health centers for community members identified as at high risk for cardiovascular disease and ensuring adequate access to essential medications would improve the overall efficiency of care. Over time, there will likely be increasing demands on community health workers’ time as more services are shifted to them. The best uses of their time should be formally evaluated on a country-by-country basis as those competing tasks evolve.
Supplementary Material Refer to Web version on PubMed Central for supplementary material.
Acknowledgments This project was funded in part by grants from the National Heart, Lung, and Blood Institute of the National Institutes of Health (Grant Nos. HHSN268200900030C and 5R01HL104284-04). The Centro de Estudios en Salud y Sociedad at El Colegio de Sonora also received funding from the UnitedHealth Chronic Disease Initiative.
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NOTES
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EXHIBIT 4. Cost-Effectiveness Of Cardiovascular Disease Screening Using A Mobile App In Three Countries, By Cost Of Treatment With Statins
SOURCE Authors’ analysis. NOTES The incremental cost-effectiveness ratio is expressed in US dollars per qualityadjusted life-year (QALY). The curves for South Africa and Mexico are superimposed on each other because of nearly identical cost-effectiveness ratios. The three costs for atorvastatin reflect the minimum, the median, and the maximum for an annual supply of the medication. GDP is gross domestic product (expressed as US dollars, not QALYs).
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Paper
Mobile app
156 242 94
Cerebrovascular accident events
Ischemic heart disease deaths
Cerebrovascular accident deaths
123
348
219
366
57
144
95
173
75
206
126
238
320 634 192
Cerebrovascular accident events
Ischemic heart disease deaths
Cerebrovascular accident deaths
268
901
452
905
155
463
256
539
205
653
350
769
134
429
229
436
7
17
17
30
Paper
189
613
324
609
9
25
22
34
Mobile app
Guatemala
NOTES The interventions were training community health workers to screen people ages 35–74 for cardiovascular disease in community settings, using either a paper-based risk chart or the same risk chart embedded in a mobile phone–based application, and to refer people at high risk to primary health centers. “Usual care” is opportunistic screening at the centers. The numbers of events averted are per 150,000 people screened by paper and per 210,000 people screened by mobile application.
SOURCE Authors’ analysis.
649
Myocardial infarction events
AVERTED AT THE IDEAL TREATMENT INITIATION RATE (75%)
262
Myocardial infarction events
AVERTED AT THE CURRENT TREATMENT INITIATION RATE
Mobile app
South Africa
Estimated Numbers Of Cardiovascular Morbidity And Mortality Events Averted By The Use Of Two Interventions Compared To Usual Care In South Africa, Mexico, And Guatemala
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EXHIBIT 1 Gaziano et al. Page 13
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EXHIBIT 2
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Cost-Effectiveness Of Current Medication Use In Three Countries, Base Case Versus Paper Intervention Or Mobile Application Intervention Discounted cost (2013 $)
Discounted QALYs
Incremental cost-effectiveness ratio
SOUTH AFRICA Base case
870.62
16.4201
Dominated
Paper
870.78
16.4236
Dominated
Mobile app
870.56
16.4248
Cost-saving
Base case
1,446.51
19.3173
—a
Paper
1,446.52
19.3193
Dominated
Mobile app
1,446.90
19.3201
3.57
MEXICO
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GUATEMALA Base case
491.55
19.1412
—a
Paper
491.74
19.1413
Dominated
Mobile app
491.67
19.1414
565.00
SOURCE Authors’ analysis. NOTES “Discounted” means that the results include the adjustment after the discount rate was applied to each year in the model. The incremental cost-effectiveness ratios are the net difference in costs divided by the net differences in quality-adjusted life-years (QALYs) between two different sequential strategies in the list for each country. “Dominated” means that the intervention costs more than, and is equal to or less effective than, the comparison strategy. “Cost-saving” means that the intervention costs less than, and is at least as effective as, the comparison strategy. “Base case” is the standard of care at present. a
Not applicable.
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Author Manuscript Dominated Dominated 2,186
Atorvastatin ($17)
Atorvastatin ($30)
Atorvastatin ($149)
2,292
325
112
Cost-saving
Dominated
Dominated
Dominated
Dominated
Dominated Dominated Dominated
Base case
200% of base case
75%
Cost-saving
Cost-saving
Cost-saving
15
Dominated
Dominated
Dominated
Dominated
Cost-saving
Cost-saving
4
64
2,329
357
136
4
Mobile app
Dominated
Dominated
Dominated
Dominated
Dominated
Dominated
Dominated
Dominated
Paper
Guatemala
137
557
565
Dominated
5,035
1,240
820
565
Mobile app
Dominated
More than 20% (base case)
Cost-saving
22 Dominated
Dominated 4
Cost-saving Dominated
Dominated 565
340
NOTES The three costs for atorvastatin reflect the minimum, the median, and the maximum for an annual supply of the medication. The base case rates are 0.23 for South Africa, 0.18 for Mexico, and 0.03 for Guatemala. The incremental cost-effectiveness ratios are the net difference in costs divided by the net differences in quality-adjusted life-years (QALYs) between two different sequential strategies in the list for each country. “Dominated” means that the intervention costs more than, and is equal to or less effective than, the comparison strategy. “Cost-saving” means that the intervention costs less than, and is at least as effective as, the comparison strategy.
SOURCE: Authors’ analysis.
Dominated
More than 10%
STATIN TREATMENT THRESHOLD (FIVE-YEAR CARDIOVASCULAR DISEASE RISK SCORE)
Dominated
50% of base case
STATIN TREATMENT RATE FOR PRIMARY PREVENTION
Dominated
Paper
Mobile app
Paper
Simvastatin ($9; base case)
STATIN (COST)
Mexico
South Africa
Incremental cost-effectiveness ratio
Statin Costs, Treatment Rates, And Treatment Thresholds For Paper Intervention Versus Mobile Application Intervention In Three Countries
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Health Aff (Millwood). Author manuscript; available in PMC 2016 September 01. Published in final edited form as: Health Aff (Millwood). 2015 September ; 34(9): 1538–1545. doi:10.1377/hlthaff.2015.0349.
Cardiovascular Disease Screening By Community Health Workers Can Be Cost-Effective In Low-Resource Countries Thomas Gaziano, Assistant professor in the Cardiovascular Division of Brigham and Women’s Hospital, in Boston, Massachusetts
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Shafika Abrahams-Gessel, Research manager at the Center for Health Decision Science in the Harvard T. H. Chan School of Public Health, in Boston Sam Surka, Researcher in the Chronic Diseases Initiative for Africa at Old Groote Schuur Hospital, in Cape Town, South Africa Stephen Sy, Programmer at the Center for Health Decision Science in the Harvard T. H. Chan School of Public Health Ankur Pandya, Assistant professor of health policy and management at the Harvard T. H. Chan School of Public Health
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Catalina A. Denman, Professor in the Centro de Estudios en Salud y Sociedad at El Colegio de Sonora, in Hermosillo, Mexico Carlos Mendoza, Coinvestigator at the Instituto de Nutricion de Centro America y Panama, in Guatemala City, Guatemala Thandi Puoane, and Professor in the School of Public Health at the University of the Western Cape, in Bellville, South Africa
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Naomi S. Levitt Director of the Division of Diabetes and the Chronic Diseases Initiative for Africa, both at Old Groote Schuur Hospital Thomas Gaziano: [email protected]
Abstract In low-resource settings, a physician is not always available. We recently demonstrated that community health workers—instead of physicians or nurses—can efficiently screen adults for cardiovascular disease in South Africa, Mexico, and Guatemala. In this analysis we sought to determine the health and economic impacts of shifting this screening to community health workers equipped with either a paper-based or a mobile phone–based screening tool. We found that
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screening by community health workers was very cost-effective or even cost-saving in all three countries, compared to the usual clinic-based screening. The mobile application emerged as the most cost-effective strategy because it could save more lives than the paper tool at minimal extra cost. Our modeling indicated that screening by community health workers, combined with improved treatment rates, would increase the number of deaths averted from 15,000 to 110,000, compared to standard care. Policy makers should promote greater acceptance of community health workers by both national populations and health professionals and should increase their commitment to treating cardiovascular disease and making medications available.
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Noncommunicable diseases cause the majority of death worldwide, with nearly 80 percent of these deaths occurring in low- and middle-income countries.1–3 Among noncommunicable diseases, cardiovascular disease is the leading cause of morbidity and mortality. The burden of cardiovascular disease is high in both high-income and low- and middle-income countries, but the future of that burden differs in the two groups of countries.1,4 In low- and middle-income countries, rates of cardiovascular disease are increasing, and it is the leading cause of death—especially of premature deaths, of which 82 percent are the result of cardiovascular disease.5 For example, South Africa has one of the most quickly increasing cardiovascular disease death rates in the world, and the rate of premature death in South African adults as a result of cardiovascular disease is projected to increase by 41 percent between 2000 and 2030.6 Although preventive treatment is available at low cost in many low- and middle-income countries, as few as 10 percent of the people in those countries receive recommended care. Significant gaps occur between developing countries in disease awareness, treatment, control, and continuity of treatment.7
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In contrast, in high-income countries such as the United States, age-adjusted mortality rates per 100,000 population from ischemic heart disease declined from 419 in 1983 to 103 in 2013. Half of this reduction can be attributed to improved primary prevention actions (actions to prevent disease before it occurs), including effective population screening and treatment programs.8–10 Reductions in mortality rates for chronic conditions require awareness of the condition, initiation of treatment when the condition is identified, and control of the condition through appropriate follow-up.
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Barriers to improving control rates for those at high risk for cardiovascular disease include health worker shortages, crowded primary health centers, and high costs associated with traditional screening programs. Shifting some of the responsibilities for hypertension and diabetes screening from doctors to nurses has been shown to improve quality of care and reduce costs.11 Even more shifting, from nurses to community health workers, is needed. Community health workers in low- and middle-income countries are typically lay people with no formal professional training in health service delivery who are selected to serve members of the communities in which they reside. The evidence for the cost-effectiveness of shifting the task of primary screening for cardiovascular disease to community health workers in low- and middle-income countries is very limited.12,13
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We recently demonstrated that community health workers in South Africa, Mexico, and Guatemala can screen for cardiovascular disease risk as effectively as physicians or nurses can, by using a previously validated inexpensive nonlaboratory paper-based screening tool.14,15 The paper tool was subsequently converted into a mobile phone–based application. Compared to community health workers who used the paper tool, those who used the mobile application were trained in less time, took fifteen minutes less on average to conduct a screening, and had a lower error rate in cardiovascular disease risk assessment measurements.16 Approximately30–70percent of individuals identified as high risk sought care at primary health centers, where a high percentage were started on appropriate treatment for their cardiovascular disease risk factors.17
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Mexico and other countries have invested in community health workers, so they can take on some parts of the management of noncommunicable diseases.18 The government of South Africa is restructuring its primary health care program, in part by training and deploying 700,000 community health workers by 2030, with the goal of better integrating them into the overall health system.19,20 Two issues have not yet been evaluated: Which roles would be most appropriate for newly trained community health workers, and how can they best be integrated into the overall health system? We evaluated the potential cost-effectiveness of using community health workers to screen for cardiovascular disease in community settings using a paper-based tool or a mobile app and to refer people at high risk to primary health centers for further evaluation and treatment in Guatemala, Mexico, and South Africa.
Study Data And Methods Author Manuscript
To assess the benefits, risks, and costs of two interventions to increase screening for cardiovascular disease by community health workers, we used an established microsimulation cardiovascular disease policy model developed with age-varying probabilities of cardiovascular disease events. The first intervention trained community health workers to use a simple nonlaboratory, paper-based cardiovascular disease risk chart in community settings. The second intervention trained the workers to use the same risk chart embedded in a mobile application. In both interventions, community health workers referred people with a five-year cardiovascular disease risk score of greater than 20 percent to the local primary health center for further evaluation and management. Both interventions were compared to the usual care of opportunistic screening at the primary health center.
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MODEL DESCRIPTION We used the cardiovascular disease policy model to project the lifetime health outcomes and costs related to cardiovascular disease of 1,000,000 hypothetical adults ages 35–74 with no prior history of stroke or ischemic heart disease in Guatemala, Mexico, and South Africa. This decision analytic model was based on a previously published cardiovascular disease model21–23 and is described in greater detail in the online Appendix.24
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The model was populated by a weighted sample of individuals from a previous community health worker study conducted in these three countries.14 Mean values for the risk factor distributions for the cohort for each country from the community health worker trial are listed in Appendix Exhibit A1.24 All other model parameters were estimated from published sources. Complete model inputs for the basic model structure, risk equations, and inputs unique to the interventions in each country, along with references for the published sources, are listed in the Appendix (Exhibits A2–8).24 KEY INTERVENTION ASSUMPTIONS AND PARAMETERS
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Given the average household size of 4 people (of whom 1.15 were estimated to be ages 35– 74),25 we assumed that each community health worker would be responsible for about 2,300 adults in that age range. Based on data from our previous studies,14,16 the model assumed that each worker would be able to screen seven adult community members per day with the paper-based intervention. Using the same data, the model assumed that each worker would be able to screen ten community members per day with the mobile application. Assuming that the workers devoted, on average, 20 percent of their time to prevention and screening, they would be able to screen either 336 or 480 new adults for cardiovascular disease per year using the paper tool or mobile application, respectively. That is, roughly 15 percent (paper) or 21 percent (mobile) of the local population would be screened over the course of a year. With a screening frequency of once every five years per adult, the workers would be able to screen the majority, if not all, of the community every five years.
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Screened people with a five-year cardiovascular disease risk score of greater than 20 percent would be referred to the primary health center for treatment with statins or hypertension medications as indicated. Our previous work established that of those referred to treatment, approximately 37 percent overall and 69 percent of those at highest risk actually visited a local clinic within the recommended two weeks of screening.17 However, each country has different rates of initiation for treatment with essential blood pressure medications or statins. We therefore used current treatment rate information for hypertension from published surveys for each country studied25–27 (Appendix Exhibit A7).24 Statin initiation data exist for secondary prevention (which attempts to reduce the impact of a disease on health), but data for primary prevention are sparse. We assumed that the initiation rate among people eligible to take statins would be half of that for blood pressure medications because simvastatin (a common and effective statin) has been on the essential drug list of the World Health Organization (WHO) only since 2009, and adoption in each country lags.
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We then conducted sensitivity analyses for rates of initiation both higher and lower than these values. Relative risk reductions for stroke and ischemic heart disease for those who are ultimately on either type of medication are listed in the Appendix (Exhibit A5).24 COSTS AND UTILITIES Estimated costs were the costs of care after acute myocardial infarction or stroke, the chronic care costs associated with surviving such acute events, treatment (including
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medications) for those identified at high risk for the events, and the training and screening costs associated with the intervention. The major inputs, including personnel costs, are reported in Appendix Exhibit A7.24 Whenever possible, we used country-level data; otherwise, we used international estimates. Costs of drugs commonly used for nonoptimal blood pressure were obtained from the International Drug Price Indicator Guide for Mexico and Guatemala.28 Health care delivery costs—salaries, health care visits, diagnostic tests, and hospital stays—are estimates from the WHO expressed in 2013 US dollars.29
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Costs of the intervention were the costs of training the community health workers to use the tools, of equipment, and of labor. The cost for a single visit to a public primary health center by people who were determined to be at high risk for cardiovascular disease and who followed through on the community health worker’s recommendation to see a health professional was determined using the latest WHO data (for 2008) for clinics without beds.29 Quality-of-life (that is, utility) decrements were applied to each year spent in cardiovascular disease event states and were based on quality-of-life estimates from the Medical Expenditure Panel Survey.30 BASE-CASE COST-EFFECTIVENESS ANALYSIS
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We projected the lifetime health care costs related to cardiovascular disease and qualityadjusted life-years (QALYs) accrued under usual care, the paper-based intervention, and the mobile app intervention. The three strategies were ranked by cost, and incremental costeffectiveness ratios were calculated. Inefficient strategies were ruled out if they had strong dominance (higher incremental costs and lower incremental QALYs) or weak dominance (both less effective and more costly than a linear combination of two other strategies) according to conventional cost-effectiveness analysis rules.31 Costs and QALYs were each adjusted with a discount rate of 3 percent, as recommended by the US Panel on Cost-Effectiveness in Health and Medicine.32 The discount rate takes into account the risk of future events and is used to determine the present value of future cash flows or health preferences. We used cost-effectiveness thresholds of one and three times the gross domestic product (GDP) per capita, respectively, for each country. SENSITIVITY ANALYSES
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We varied values for all variables (or groups of related variables) through plausible ranges, or used alternative values, to assess the robustness of our cost-effectiveness analysis results to changes in these input parameters. For example, we used a discount rate of up to 7 percent. LIMITATIONS The study had several limitations that should be noted. First, we assumed persistent statin and blood pressure medication benefits over the course of a lifetime for those who were
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eligible for and began using the medications, which is a common cardiovascular disease modeling assumption.33 Second, we were not sure of overall compliance rates with initiated medications in the three countries in our study. However, we used long-term compliance rates that declined over time to as low as 50 percent. Efforts to improve compliance at low costs would improve the cost-effectiveness of screening strategies followed by initiation of treatment. Third, we assumed that the time needed to screen individuals would be equivalent to the times we measured in our previous studies.16 It is possible that in some rural areas, where people live farther apart, travel time would increase the time required for in-home screening. However, screening time in rural areas may be reduced by conducting screenings at sites where members of the community congregate, such as churches or community centers.
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Finally, when cost information was not available for a specific country, we used international estimates for the countries, particularly for the cost of chronic care driven by international drug pricing estimates. For this reason, we ran sensitivity analyses on the cost of medications.
Study Results BASE-CASE ANALYSIS Both the paper and mobile app screening methods would lead to reductions in fatal and nonfatal stroke as well as coronary heart disease events, when compared to the usual standard of care. The rates differed by country, mainly because of varying rates of treatment initiation for those identified as high risk.
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Using the mobile app would save 471 lives in South Africa, 281 lives in Mexico, and 34 lives in Guatemala, per 210,000 adults screened (Exhibit 1). The screening cost would be approximately $1.00, $3.00, and $0.67 per screening, respectively (Appendix Exhibit A7).24 Similar numbers of nonfatal events would also be prevented in each country.
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Using the paper tool, 336 deaths in South Africa, 201 in Mexico, and 24 in Guatemala were averted per 150,000 adults screened (Exhibit 1). When we set an ideal treatment initiation rate of at least 75 percent for those with a cardiovascular disease risk above 20 percent, we found that approximately 800–1,200 cardiovascular disease deaths could be prevented per 200,000 adults screened across the three countries using the mobile app, with a similar number of nonfatal events averted. This ideal rate was based on upper limits for current use of antihypertensive medications in the United States.34 If the rate was applied to the whole country, there would be up to 40,000 deaths due to cardiovascular disease averted in South Africa, 110,000 in Mexico, and 15,000 in Guatemala. COST-EFFECTIVENESS ANALYSES Both intervention strategies added QALYs compared to the usual standard of care. However, the mobile application was the most cost-effective intervention, with an incremental cost-effectiveness ratio of $565 per QALY gained in Guatemala and $3.57 per
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QALY gained in Mexico (Exhibit 2). Use of the mobile application was cost-saving (it increased QALYs and reduced overall costs) in South Africa. When we compared the paperbased tool to the usual standard of care, the incremental cost-effectiveness ratios were approximately $47, $195, and $1,890 per QALY gained in South Africa, Mexico, and Guatemala, respectively (Appendix Exhibit A10).24 Increased efficiencies are also likely with the use of an electronic data collection system at a national level. We did not include these potential savings, so our estimates may be conservative. However, developing a national system would also have costs associated with it, and thus we cannot estimate the full effects. SENSITIVITY ANALYSES
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The strategies were not sensitive to the cost of the intervention across the range of estimated and calculated costs tested (Appendix Exhibit A9).24 However, the strategies were sensitive to the costs of the statins. At one-half of the base-case costs, the incremental costeffectiveness ratios in Guatemala and Mexico were reduced by nearly half for the mobile app, and the strategy remained cost-saving for South Africa (Exhibit 3). Using the upper limit of available generic pricing for atorvastatin of $149 per year, the ratios were $2,292, $2,329, and $5,035 per QALY gained for South Africa, Mexico, and Guatemala, respectively. The mobile application was still better than the paper application when we used discount rates of 4.5 percent35 and 7.0 percent (Appendix Exhibit A9).24
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All but one of the incremental cost-effectiveness ratios were well below the threshold of the GDP per capita in each of the three countries (Exhibit 4). Only at the highest cost estimate for atorvastatin in Guatemala was the ratio above that threshold, and even then it was below the threshold of three times the GDP per capita. When we used the GDP per capita threshold as a measure of willingness to pay, the results were not significantly sensitive to the initiation threshold for statins in primary prevention in the three countries. When we lowered the treatment threshold to a five-year cardiovascular risk score of greater than 10 percent, community health workers’ use of the mobile application remained the preferred strategy (Exhibit 3). There were offsetting costs: Increased numbers of people treated meant increased drug and outpatient costs but decreased costs from events averted. And there was decreased risk for the population as the threshold was lowered.
Discussion Author Manuscript
Our analyses show that having community health workers screen members of the community for high risk of cardiovascular disease with a simple noninvasive tool would cost relatively little to implement and would be highly cost-effective in three diverse low- and middle-income countries. The mobile application version of the tool is simple to learn and can be used with as little as four hours of training. Some countries may wish to use the paper-based tool first, which is cost-effective in the absence of mobile phone availability or network coverage. However, the mobile phone
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penetration rates (the number of mobile phones divided by the population) in the three study countries are 144 percent for Guatemala, 84 percent for Mexico, and 143 percent for South Africa, which suggests that the availability of mobile phones should not be a major limitation in at least the urban areas of these countries.36 Furthermore, when we included the cost of a mobile phone (approximately $20) in the three countries, the cost per screening changed by less than one cent.
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Our results show that while the intervention was cost-effective in Guatemala, it was less so than in South Africa and Mexico as a result of low drug treatment initiation rates. Countries must not only be committed to screening for chronic conditions, but they must also be committed to initiating treatment or other effective lifestyle interventions for people at high risk for cardiovascular disease. Treatment initiation barriers—particularly for statins, but also for blood pressure medications—include limited staff at primary health centers, the relatively recent addition of statins to the WHO’s essential medicines list, and lack of awareness and belief in the utility of medications for chronic conditions among the population.
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Effective screening interventions require increased commitment to treating chronic conditions and making low-cost medications available. They also require the acceptance of community health workers as an integral part of the health sector—by both other health professionals and community members—along with well-structured referral pathways. The rates at which referred people (those whose cardiovascular disease risk score was over 20 percent) completed a visit to a primary health center were as low as 33 percent in the three countries in our study.17 Formal studies are needed to evaluate how mobile health tools can also be used for improving referral rates and initiation of appropriate treatment at primary health centers.
Workforce Implications
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To scale the intervention to the national level, approximately 450 community health workers (90 full-time equivalents) per million people would be needed to screen the entire adult population. In South Africa this would mean up to 20,000 workers, which is a small proportion of the 700,000 positions for such workers proposed by the Republic of South Africa National Planning Commission.19 Costs per screened adult using the mobile application were $0.67 in Guatemala, $1.00 in South Africa, and $3.00 in Mexico. At these rates, depending on which version of the intervention was used, the overall annual cost would be $4–$8 million in South Africa, $0.5–$1 million in Guatemala, and $29–$47 million in Mexico. The differences across the countries reflect both the sizes of the populations and the higher wages paid in Mexico, compared to the other two countries. While the numbers of community health workers required are relatively small, the training and certification process to ensure quality needs to be addressed. Currently, there is no career path with certification processes for community health workers in any of the three countries we studied. We made many of our cost estimates based on the best available data. However, some cost data in particular were lacking in Mexico and Guatemala. We used international estimates Health Aff (Millwood). Author manuscript; available in PMC 2016 September 01.
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provided by the WHO and other organizations, but government policy makers should improve their cost accounting for health care expenditures to better understand the financial implications of certain interventions.
Conclusion
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Our analysis shows that having community health workers screen for noncommunicable diseases such as cardiovascular disease in the community can be highly cost-effective with the use of a simple noninvasive screening tool. Scaling the project to a national level would be reasonably inexpensive given current salaries for community health workers. Strengthening the referral process to health centers for community members identified as at high risk for cardiovascular disease and ensuring adequate access to essential medications would improve the overall efficiency of care. Over time, there will likely be increasing demands on community health workers’ time as more services are shifted to them. The best uses of their time should be formally evaluated on a country-by-country basis as those competing tasks evolve.
Supplementary Material Refer to Web version on PubMed Central for supplementary material.
Acknowledgments This project was funded in part by grants from the National Heart, Lung, and Blood Institute of the National Institutes of Health (Grant Nos. HHSN268200900030C and 5R01HL104284-04). The Centro de Estudios en Salud y Sociedad at El Colegio de Sonora also received funding from the UnitedHealth Chronic Disease Initiative.
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NOTES
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1. Lozano R, Naghavi M, Foreman K, Lim S, Shibuya K, Aboyans V, et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012; 380(9859):2095–128. [PubMed: 23245604] 2. World Health Organization. Health statistics and information systems: estimates for 2000–2012: cause-specific mortality [Internet]. Geneva: WHO; c 2015 [cited 2015 Jun 29]. Available from: http://www.who.int/healthinfo/global_burden_disease/estimates/en/index1.html 3. World Health Organization. WHO methods and data sources for global burden of disease estimates: 2000–2011 [Internet]. Geneva: WHO; 2013 Nov. [cited 2015 Jun 29]. Available from: http:// www.who.int/healthinfo/statistics/GlobalDALYmethods_2000_2011.pdf?ua=1 4. Gaziano TA, Bitton A, Anand S, Abrahams-Gessel S, Murphy A. Growing epidemic of coronary heart disease in low- and middle-income countries. Curr Probl Cardiol. 2010; 35(2):72–115. [PubMed: 20109979] 5. World Health Organization. 2008–2013 action plan for the global strategy for the prevention and control of noncommunicable diseases [Internet]. Geneva: WHO; [cited 2015 Jun 29]. Available from: http://www.who.int/nmh/publications/ncd_action_plan_en.pdf 6. Gaziano TA. Reducing the growing burden of cardiovascular disease in the developing world. Health Aff (Millwood). 2007; 26(1):13–24. [PubMed: 17211010] 7. Mendis S, Abegunde D, Yusuf S, Ebrahim S, Shaper G, Ghannem H, et al. WHO study on Prevention of REcurrences of Myocardial Infarction and StrokE (WHO-PREMISE). Bull World Health Organ. 2005; 83(11):820–9. [PubMed: 16302038]
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EXHIBIT 4. Cost-Effectiveness Of Cardiovascular Disease Screening Using A Mobile App In Three Countries, By Cost Of Treatment With Statins
SOURCE Authors’ analysis. NOTES The incremental cost-effectiveness ratio is expressed in US dollars per qualityadjusted life-year (QALY). The curves for South Africa and Mexico are superimposed on each other because of nearly identical cost-effectiveness ratios. The three costs for atorvastatin reflect the minimum, the median, and the maximum for an annual supply of the medication. GDP is gross domestic product (expressed as US dollars, not QALYs).
Author Manuscript Author Manuscript Health Aff (Millwood). Author manuscript; available in PMC 2016 September 01.
Author Manuscript
Author Manuscript
Author Manuscript Mexico Paper
Paper
Mobile app
156 242 94
Cerebrovascular accident events
Ischemic heart disease deaths
Cerebrovascular accident deaths
123
348
219
366
57
144
95
173
75
206
126
238
320 634 192
Cerebrovascular accident events
Ischemic heart disease deaths
Cerebrovascular accident deaths
268
901
452
905
155
463
256
539
205
653
350
769
134
429
229
436
7
17
17
30
Paper
189
613
324
609
9
25
22
34
Mobile app
Guatemala
NOTES The interventions were training community health workers to screen people ages 35–74 for cardiovascular disease in community settings, using either a paper-based risk chart or the same risk chart embedded in a mobile phone–based application, and to refer people at high risk to primary health centers. “Usual care” is opportunistic screening at the centers. The numbers of events averted are per 150,000 people screened by paper and per 210,000 people screened by mobile application.
SOURCE Authors’ analysis.
649
Myocardial infarction events
AVERTED AT THE IDEAL TREATMENT INITIATION RATE (75%)
262
Myocardial infarction events
AVERTED AT THE CURRENT TREATMENT INITIATION RATE
Mobile app
South Africa
Estimated Numbers Of Cardiovascular Morbidity And Mortality Events Averted By The Use Of Two Interventions Compared To Usual Care In South Africa, Mexico, And Guatemala
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EXHIBIT 1 Gaziano et al. Page 13
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EXHIBIT 2
Author Manuscript
Cost-Effectiveness Of Current Medication Use In Three Countries, Base Case Versus Paper Intervention Or Mobile Application Intervention Discounted cost (2013 $)
Discounted QALYs
Incremental cost-effectiveness ratio
SOUTH AFRICA Base case
870.62
16.4201
Dominated
Paper
870.78
16.4236
Dominated
Mobile app
870.56
16.4248
Cost-saving
Base case
1,446.51
19.3173
—a
Paper
1,446.52
19.3193
Dominated
Mobile app
1,446.90
19.3201
3.57
MEXICO
Author Manuscript
GUATEMALA Base case
491.55
19.1412
—a
Paper
491.74
19.1413
Dominated
Mobile app
491.67
19.1414
565.00
SOURCE Authors’ analysis. NOTES “Discounted” means that the results include the adjustment after the discount rate was applied to each year in the model. The incremental cost-effectiveness ratios are the net difference in costs divided by the net differences in quality-adjusted life-years (QALYs) between two different sequential strategies in the list for each country. “Dominated” means that the intervention costs more than, and is equal to or less effective than, the comparison strategy. “Cost-saving” means that the intervention costs less than, and is at least as effective as, the comparison strategy. “Base case” is the standard of care at present. a
Not applicable.
Author Manuscript Author Manuscript Health Aff (Millwood). Author manuscript; available in PMC 2016 September 01.
Author Manuscript
Author Manuscript
Author Manuscript Dominated Dominated 2,186
Atorvastatin ($17)
Atorvastatin ($30)
Atorvastatin ($149)
2,292
325
112
Cost-saving
Dominated
Dominated
Dominated
Dominated
Dominated Dominated Dominated
Base case
200% of base case
75%
Cost-saving
Cost-saving
Cost-saving
15
Dominated
Dominated
Dominated
Dominated
Cost-saving
Cost-saving
4
64
2,329
357
136
4
Mobile app
Dominated
Dominated
Dominated
Dominated
Dominated
Dominated
Dominated
Dominated
Paper
Guatemala
137
557
565
Dominated
5,035
1,240
820
565
Mobile app
Dominated
More than 20% (base case)
Cost-saving
22 Dominated
Dominated 4
Cost-saving Dominated
Dominated 565
340
NOTES The three costs for atorvastatin reflect the minimum, the median, and the maximum for an annual supply of the medication. The base case rates are 0.23 for South Africa, 0.18 for Mexico, and 0.03 for Guatemala. The incremental cost-effectiveness ratios are the net difference in costs divided by the net differences in quality-adjusted life-years (QALYs) between two different sequential strategies in the list for each country. “Dominated” means that the intervention costs more than, and is equal to or less effective than, the comparison strategy. “Cost-saving” means that the intervention costs less than, and is at least as effective as, the comparison strategy.
SOURCE: Authors’ analysis.
Dominated
More than 10%
STATIN TREATMENT THRESHOLD (FIVE-YEAR CARDIOVASCULAR DISEASE RISK SCORE)
Dominated
50% of base case
STATIN TREATMENT RATE FOR PRIMARY PREVENTION
Dominated
Paper
Mobile app
Paper
Simvastatin ($9; base case)
STATIN (COST)
Mexico
South Africa
Incremental cost-effectiveness ratio
Statin Costs, Treatment Rates, And Treatment Thresholds For Paper Intervention Versus Mobile Application Intervention In Three Countries
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EXHIBIT 3 Gaziano et al. Page 15
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