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Catastrophic expenditure to pay for surgery worldwide: a modelling study
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Catastrophic expenditure to pay for surgery worldwide: a modelling study Mark G Shrime, Anna J Dare, Blake C Alkire, Kathleen O’Neill, John G Meara
Summary Lancet Glob Health 2015; 3 (S2): S38–44 Department of Global Health and Population, Harvard School of Public Health, Boston, MA, USA (M G Shrime MD); King’s Centre for Global Health, King’s Health Partners, King’s College London, London, UK (A J Dare MBChB); Department of Otology and Laryngology, Harvard Medical School, Boston, MA, USA (M G Shrime, B C Alkire MD); Office of Global Surgery, Massachusetts Eye and Ear Infirmary, Boston, MA, USA (M G Shrime, B C Alkire); University of Pennsylvania Medical School, Philadelphia, PA, USA (K O’Neill BS); Program in Global Surgery and Social Change, Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA (M G Shrime, B C Alkire, J G Meara MD); and Department of Plastic and Oral Surgery, Boston Children’s Hospital, Boston, MA, USA (J G Meara) Correspondence to: Dr Mark G Shrime, Massachusetts Eye and Ear Infirmary, 243 Charles Street, Boston, MA 02114,USA [email protected]
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Background Approximately 150 million individuals worldwide face catastrophic expenditure each year from medical costs alone, and the non-medical costs of accessing care increase that number. The proportion of this expenditure related to surgery is unknown. Because the World Bank has proposed elimination of medical impoverishment by 2030, the effect of surgical conditions on financial catastrophe should be quantified so that any financial risk protection mechanisms can appropriately incorporate surgery. Methods To estimate the global incidence of catastrophic expenditure due to surgery, we built a stochastic model. The income distribution of each country, the probability of requiring surgery, and the medical and non-medical costs faced for surgery were incorporated. Sensitivity analyses were run to test the robustness of the model. Findings 3·7 billion people (posterior credible interval 3·2–4·2 billion) risk catastrophic expenditure if they need surgery. Each year, 81·3 million people (80·8–81·7 million) worldwide are driven to financial catastrophe—32·8 million (32·4–33·1 million) from the costs of surgery alone and 48·5 million (47·7–49·3) from associated non-medical costs. The burden of catastrophic expenditure is highest in countries of low and middle income; within any country, it falls on the poor. Estimates were sensitive to the definition of catastrophic expenditure and the costs of care. The inequitable burden distribution was robust to model assumptions. Interpretation Half the global population is at risk of financial catastrophe from surgery. Each year, surgical conditions cause 81 million individuals to face catastrophic expenditure, of which less than half is attributable to medical costs. These findings highlight the need for financial risk protection for surgery in health-system design. Funding MGS received partial funding from NIH/NCI R25CA92203. Copyright © Shrime et al. Open Access article distributed under the terms of CC BY-NC-ND.
Introduction Access to health care is not always free, and its use commonly carries a risk of impoverishment. In many parts of the world, out-of-pocket payments for health care remain the predominant form of health financing.1 About 150 million cases of catastrophic expenditure— defined as an expenditure of more than 40% of non-food household expenditure2 or 10% of overall household expenditure3—occur each year as a result of accessing care.2 Little is known, however, about the magnitude of catastrophic expenditure attributable to various parts of the health system—both worldwide and in countries at differing stages of development. In particular, the contribution of surgical care to catastrophic health expenditure has not previously been estimated. Access to surgery is increasingly recognised as a crucial component of a functioning health system for countries at all stages of development.4 About 30% of the global burden of disease is surgical,5 and the delivery of basic, life-saving surgical care is highly cost-effective in both high-income countries and those of low and middle income.6 However, cost-effectiveness at the population level does not necessarily translate into affordability for an individual patient. In the absence of financial risk protection measures, accessing surgery can be catastrophically
expensive for patients. Because common effectiveness measures (such as quality-adjusted or disability-adjusted life years) do not explicitly capture the potentially impoverishing effects of care, these financial effects on individuals have tended to be overlooked. The need for surgical care can be time-critical, unpredictable, and resource-intensive, so surgery is difficult to plan or save for. In addition, treatment seeking is more impoverishing for surgical conditions than for other conditions.7 As well as the financial burden of paying for surgical services, individuals face the costs of getting to care. These non-medical costs of transportation, food, and lodging8 are substantial and can themselves drive patients into poverty.9 The high costs associated with accessing surgical care not only increase the chance of catastrophic health expenditure, but can also act to prevent healthseeking behaviour, especially among the poor.10 Protection of households against catastrophic health expenditure has emerged as a leading policy goal for global health. The WHO,11 the World Bank,12 and the UN13 have lately renewed calls for the introduction of universal health coverage and the assurance of financial risk protection against the costs of illness. The World Bank stated that, “By 2030, no one should fall into poverty because of out-of-pocket health care expenses.” 14 www.thelancet.com/lancetgh Vol 3 (S2) April 2015
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A greater understanding of the financial catastrophe attributable to various health interventions, including surgical care, has therefore become necessary to inform policy. Our aim was to estimate the number of patients worldwide who experience catastrophic expenditure each year from accessing surgery. We also investigated how rates of catastrophic expenditure from surgery change according to national development status and individual wealth quintile. We postulated that a large portion of worldwide financial catastrophe caused by medical care would be attributable to surgery, and that this burden would fall most heavily on the poor.
Methods Model construction Several thresholds have been proposed for catastrophic expenditure. Here, we chose to use a threshold of 10% of overall household expenditure,15 which we explored in sensitivity analyses. An individual faces catastrophic expenditure when the out-of-pocket costs faced to access care are greater than this threshold. That is: OOP × c ≥ ty where c is the total cost of a service, OOP the out-ofpocket proportion of that cost, y household expenditure before care was sought, and t the threshold, expressed as a proportion of household expenditure, at which catastrophic expenditure is said to have occurred. For example, an individual whose expenditure before health care was sought was $1000 would face catastrophic expenditure if he or she had to pay more than $100 for health care. The methodology behind the application of the equation to the world population is given in detail in the appendix. Briefly, the income distribution of a country’s population was modelled, and the proportion of the population undergoing surgery estimated, by wealth quintile, from published data (see data sources, below, and appendix p 2–6). For individuals who need surgical services, an out-of-pocket cost was assessed. If that amount was greater than 10% of their preceding income, they were counted as having experienced catastrophic expenditure. This calculation was repeated across all countries to obtain a global estimate. To estimate the number of individuals at risk of catastrophic expenditure, the same calculation was repeated, with the probability of getting surgery factored out.
Data sources World Bank data were used for each of the necessary variables in 199 countries. Household expenditure was used where available.16 If it was not available, gross domestic product (GDP) per person17 was used as a proxy. WHO-CHOICE estimates for the unit cost of a caesarean section were taken to represent costs of surgery,18 an www.thelancet.com/lancetgh Vol 3 (S2) April 2015
assumption that was tested in sensitivity analyses. According to WHO, this cost includes “initiation of labour at referral level, diagnosis of obstructed labour and referral, devices and medicines associated with caesarean delivery, operative facility time, medical human resources time, management of shock including hysterectomy and blood transfusion (assumed for 1% of procedures), postoperative hospital stay for stabilisation, programme administration, training, and the corresponding office space, electricity, and other services, as well as various standard consumables and equipment”.18 In probabilistic sensitivity analysis, a multiplier was applied to this cost. The reported cost for one country (Iceland) was a significant outlier. Its cost was taken as the result of a linear regression on its GDP per head. Out-of-pocket expenditure was calculated as a proportion of total health expenditure.19 The model was run with and without the inclusion of non-medical costs faced by patients when accessing surgical services (eg, transportation, lodging, food). When these costs were included, we used a conservative estimate consistent with estimates from Ethiopia,20 Bangladesh,7,21–23 India,24–29 and Vietnam;30 specifically, the non-medical costs were constructed as a multiplier to direct medical costs on the basis of these data, with the introduction of error from the varied estimates. This approach was examined in detail in sensitivity analyses, below. All costs, expenditure, and income estimates were adjusted to 2007 international dollars, by use of UN purchasing power parity conversion factors and World Bank GDP deflators, as previously described.31 2007 was chosen because it was the year for which the most robust primary data were available. The probability of accessing surgery was taken from previously published estimates.32 For countries in which estimates of cases per population were not available, regional estimates for countries with similar overall health-care expenditure per head were used instead. Similarly, when Gini indices for individual countries were not available, regional indices were used.33 The
See Online for appendix
Cases of catastrophic expenditure (95% PCI) Base case (without non-medical costs) Base case (including non-medical costs)
32 768 603 (32 447 074–33 090 131) 81 262 319 (80 793 101–81 731 536)
Increasing non-medical costs
145 395 830 (144 777 380–146 014 280)
Lowered threshold for catastrophic expenditure (without non-medical costs)
63 268 868 (61 608 121–64 929 614)
Lowered threshold for catastrophic expenditure (including non-medical costs)
119 781 104 (117 504 932–122 057 276)
Average cost of surgery halved (without non-medical costs) Average cost of surgery halved (with non-medical costs) Average cost of surgery doubled (without non-medical costs) Average cost of surgery doubled (with non-medical costs)
7 692 269 (7 255 498–8 129 041) 28 034 971 (27 127 473–28 942 470) 79 232 250 (77 546 379–80 918 122) 135 634 968 (133 213 154–138 056 782)
PCI=posterior credible interval.
Table: Cases of catastrophic expenditure per year, by assumption
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probability of surgery was broken down by quintiles as follows: access to caesarean section was calculated for Ethiopia, India, and Bangladesh from their respective Demographic and Health Surveys.34–36 Access by quintile was compared with mean access, and the average proportion of access faced by people in each quintile was then taken as an access multiplier for the model as a whole. The assessment of the gradient was limited by the data available and is discussed below. The following countries did not have sufficient data available: the Cook Islands, North Korea, Nauru, Niue, Puerto Rico, Somalia, South Sudan, and Taiwan. Data were missing for these countries from both the World Bank economic and population indicators and from estimates of surgical delivery. The combined population of these countries represents only 1·03% of the overall global population; we therefore made an assumption of random missingness, and the results from the remaining countries were scaled up linearly to encompass the world’s population.
Scenario and sensitivity analyses Sensitivity analyses were done to test the robustness of our results. Because the cost of surgery is a driver of the model, as seen in the equation, and because the cost of a caesarean section could under-represent the cost of surgery overall,37 we ran a sensitivity analysis on the average cost of an operation. We ran a similar sensitivity analysis on the average non-medical costs faced by patients, with both high and low estimates from the sources listed above. WHO and the World Bank have
lately redefined catastrophic expenditure as any spending that is more than 25% of post-subsistence expenditure.38 With application of the linear transformation that previously converted thresholds based on postsubsistence expenditure to thresholds based on total expenditure, this new definition translates to 6·25% of overall expenditure. We did a sensitivity analysis with this value as the cut-off. Finally, the World Bank estimates of out-of-pocket expenditure differ from estimates published directly from examination of national health accounts.39 We substituted the latter estimates where available in a fourth sensitivity analysis. First-order heterogeneity was modelled by use of Monte Carlo simulations at each of the probability nodes. Second-order uncertainty was incorporated by drawing from probability distributions around c × OOP, the surgical cost scaling factor, and the proportion of the population accessing surgical care (appendix p 7). 200 parameter sets were drawn from each distribution; 1000 iterations of each parameter set were run, over all 199 countries, and for each of the three model versions. The mean and 95% posterior credible intervals (PCI) are reported for overall numbers of cases of catastrophic expenditure and for cases per million in the population. Model construction and data analysis were performed in Microsoft Excel 2011 and R version 3.0.2 (www. rproject.org).
Role of the funding source This study had no direct funding. No entity besides the authors had a role in any part of this study, including
Risk of catastrophic expenditure if surgery is required 1·0 0·9 0·8 0·7 0·6 0·5 0·4 0·3 0·2 0·1 0
Figure 1: Risk of catastrophic expenditure if surgical care is necessary Red=high risk. Yellow=low risk. A risk of catastrophic expenditure of 0·5 means that, conditional on needing surgery, an individual has a 50% chance of going into financial catastrophe were he or she to get that surgery.
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conception and design, data acquisition, data analysis, report preparation, revision, or the decision to submit for publication. All authors had access to the data in the study.
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Without non-medical costs With non-medical costs
Proportion of surgical patients facing catastrophic expenditrure (%)
8 7 6 5 4 3 2 1 0 Poorest
B Proportion of catastrophic expenditure (%)
Globally, an estimated 32·8 million (95% PCI 32·4–33·1 million) cases of catastrophic expenditure occur each year as a result of patients accessing surgical services (table) Roughly 3·7 billion individuals (3·2–4·2 billion) are at risk of financial catastrophe should they need surgical care. Most of these people live in sub-Saharan Africa, and south and southeast Asia (figure 1). Catastrophic expenditure to pay medical costs falls primarily on the poor, with differences by region. Worldwide, about 6·1% (5·2–7·0) of the poorest patients who undergo surgery face catastrophic expenditure, whereas less than 0·10% (0·01–0·19) of the richest do. In low-income countries, this gradient is nearly flat, but in upper-middle and high-income countries, nearly all catastrophic expenditure falls on the poor (figure 2). When the multisectoral nature of health seeking was examined, the estimates of catastrophic expenditure increased greatly. Direct non-medical costs to patients (transportation, lodging, food, and informal payments) produced an additional 48·5 million cases of catastrophic expenditure (47·7–49·3), leading to a total estimate of 81·3 million cases (80·8–81·7 million). When these costs were counted in the model, the gradient among wealth quintiles flattened somewhat. Globally, risk of catastrophic expenditure increased, more in the richer than in the poorer quintiles (figure 2). Previous estimates of catastrophic expenditure have used the threshold used in our base case analysis. Newer thresholds have, however, been proposed. When we lowered the threshold for counting a case of catastrophic expenditure to 6·25%, the estimated number of cases of catastrophic expenditure predictably increased. At this threshold, 63·3 million (61·6–64·9 million) cases of catastrophic expenditure were predicted as a result of medical costs alone, and 119·8 million (117·5–122·1 million) cases were predicted as a result of medical and non-medical costs together. When we halved the average cost of surgery, the number of cases of catastrophic expenditure fell to 7·7 million (7·3–8·1 million) for direct medical costs only and 28·0 million (27·1–28·9 million) for medical and nonmedical costs together. When the cost of an average surgical procedure was estimated to be double that of a caesarean section, the estimate of cases of catastrophic expenditure increased to 79·2 million (77·5–80·9 million) for direct medical costs and 135·6 million (133·2–138·1 million) for medical and non-medical costs together. Our estimates were sensitive to assumptions around the magnitude of direct non-medical costs, but only moderately. An increase of six times in these costs increased the estimate of total cases of catastrophic
World
9
Poor
Middle Wealth quintile
Rich
Richest
Low-income countries
C
Low–middle-income countries
Upper–middle-income countries
E
High-income countries
20 18 16 14 12 10 8 6 4 2 0
D Proportion of catastrophic expenditure (%)
Results
A
20 18 16 14 12 10 8 6 4 2 0 Poorest
Poor
Middle
Rich
Richest
Poorest
Poor
Wealth quintile
Middle
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Richest
Wealth quintile
Figure 2: Catastrophic expenditure by wealth quintile and national income group, conditional on seeking surgery
expenditure by only four times. The higher the estimate of non-medical costs, the more catastrophic expenditure people in the richer quintiles faced. Our results were robust to the source of out-of-pocket proportion estimates. Use of estimates directly from national health accounts39 did not change our estimates significantly.
Discussion Globally, 3·7 million people are at risk of financial catastrophe should they need surgery, and 33 million face catastrophic expenditure each year accessing and paying for surgical care. This number represents about S41
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22% of the 150 million individuals who face catastrophic expenditure accessing the health system each year,2 commensurate with the proportion of global disease burden that is surgical.5 Financial catastrophe affects individuals in countries of low and middle income most severely; within any one country, the poorest people fare the worst. Access to health care involves more than simply paying for services. Non-medical costs, such as transportation, lodging, and food, can contribute substantially to catastrophic expenditure.20 These costs, however, are not included in many estimates of out-of-pocket financial expenditures.2 When these costs were accounted for in our model, an additional 48·5 million cases of catastrophic expenditure were predicted, leading to an overall estimate of 81 million annual cases of catastrophic expenditure from accessing surgical care worldwide. These cases of financial catastrophe are not being created by the addition of these non-medical costs; they are already happening, but have not been accounted for in models that consider only the direct cost of services. Our results show an interesting, if somewhat counterintuitive, finding; financial catastrophe from surgical access is more common in individuals in lower-middleincome countries than in those in low-income countries. The reason is that, on average, the cost of surgery, as a function of income, is 15% higher in lower-middle-income countries than in low-income countries, which suggests that, as the financial status of a country improves, the costs of seeking surgery could increase more rapidly than average household income. This finding highlights the importance of incorporating financial risk protection into health systems at all stages of development, particularly as countries transition from a low-income to lower-middleincome group. This concept is consistent with findings by the Commission on Investing in Health.40 When non-medical costs are taken into account, catastrophic expenditure appears to accrue more heavily on people in the richer wealth quintiles. This finding is artifactual. Poor people have already hit the catastrophic expenditure threshold, whether or not non-medical costs are included. Because catastrophic expenditure does not measure the depth of impoverishment, addition of further costs to those already impoverished is not counted. The apparent increase in catastrophic expenditure among the better off arises because increased use among the rich makes the model more sensitive to catastrophic expenditure resulting from nonmedical costs payable by these individuals. This analysis has several strengths and limitations. First, the definition of catastrophic expenditure itself is controversial;3,9,15 we have chosen one definition in our base case and another in our sensitivity analysis, but we recognise that, in the absence of a universally accepted definition, these remain open to debate. More importantly, however, catastrophic expenditure captures only individuals who actually pay for services. It S42
cannot address patients who need services but cannot afford them, nor the impoverishment caused if services are not obtained by the primary income-earner in a household. This weakness is inherent in most current measures of the financial burden of health care. Borrowed from taxation studies, these metrics40—any expenditure, amount of expenditure, catastrophic expenditure, poverty head count, poverty gap or squared poverty gap, indebtedness, and borrowing and selling to pay for care—all inherently count only payment made. They do not account for a lack of access and do not include indirect costs such as lost wages and decreased economic productivity. As a result, the financial impact that results from a lack of access cannot be fully captured by these metrics. Our choice of threshold for catastrophic expenditure could lead to an underestimation in countries of low and middle income. Individuals whose expenditure on food forms a substantial part of their total expenditure would face financial ruin with smaller out-of-pocket spending than is captured in this model. In addition, expenditures for individuals near the poverty line might not count as catastrophic, by definition, but could still have devastating effects on household welfare. This model is based on limited data. The income distribution in individual countries is approximated by a statistical distribution; although it fits population income distributions on average,41 it might do so more or less accurately in countries in which most of the workforce is based in the informal sector. Similarly, we base our surgical costs on the costs of caesarean section because this is the only procedure for which we had reliable global data. In the absence of other data, we chose to inflate and deflate this estimate probabilistically, as well as to examine it explicitly in sensitivity analyses, mitigating this weakness. Of note, although many countries have financing in place specifically for caesarean sections, this financing does not always protect against catastrophic expenditure.42 The gradient of use across nations comes from a small sample of countries, which introduces uncertainty into our equity results. Data on disease burden are limited also. This limitation, however, does not affect our results; because this paper looks at catastrophic expenditure from patients actually accessing the surgical system, as opposed to latent demand for surgical services, the studies on surgical disease burden that have been done will be important for any further scale-up of a surgical system.43 Data on insurance are also limited—although out-ofpocket data used here will, by definition, take the presence of insurance into account, the purpose of insurance is to smooth an out-of-pocket function. Evidence suggests that the expansion of insurance does increase health-care use, but with varying effects on actual health outcomes.44 Although the institution of an insurance scheme in countries without one might allay some catastrophic expenditure, it does so with an www.thelancet.com/lancetgh Vol 3 (S2) April 2015
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important caveat; because surgical conditions are commonly associated with large up-front costs, even a patient whose out-of-pocket spending is reimbursed by insurance will still face catastrophic expenditure before the reimbursement. Finally, this paper is a static picture; the modelling techniques used cannot project the effects of financial catastrophe over time. Not enough evidence is available to construct a global model addressing future financial impact. The strengths of this study, however, lie in what it shows about the nature of global catastrophic health expenditure (panel). This model does what many other estimates of catastrophic expenditure have not done. First, it includes the direct non-medical costs that individuals face, giving a more realistic estimate of impoverishment. In the previous global estimate of medical impoverishment, Xu and colleagues2 noted that no data on transportation costs were available, so the analysis underestimated the financial consequences of obtaining care. This particular underestimation is avoided in our analysis. By taking into account the full costs of care, we hope to provide a more complete picture of the need for financial risk protection. The previous global estimate of medical impoverishment2 did not break the impoverishment down by disease condition. To our knowledge, no study has proposed a global estimate for catastrophic expenditure due, for example, to chronic disorders or critical care. This step is important—since the elimination of medical impoverishment is the stated goal of many world bodies,14 detailed information on the distribution of financial catastrophe is necessary to inform sound policies aimed at preventing it. The nature of a stochastic model such as ours allows for an explicit assessment of heterogeneity and uncertainty around parameters. Any global estimate is fraught with uncertainty—this model makes the uncertainty explicit. The sensitivity analyses also document the factors in the model on which the results are reliant. Redefinition of the threshold at which catastrophic expenditure is counted, for example, drastically changes the number of individuals with catastrophic expenditure per year. This study approached the question of financial catastrophe by use of a different modelling technique from other estimates; nevertheless, it arrived at estimates that are in line with previous ones, lending credence both to this modelling technique and to the external validity of the estimates. Surgery is a substantive part of any health system,4,20,45 and surgical conditions can uniquely put patients at risk of financial catastrophe because they tend to be timecritical, life-threatening, and fraught with large up-front costs. In January, 2014, the President of the World Bank, Jim Y Kim, detailed the Bank’s goals for catastrophic expenditure: “The proposed target is, by 2020, to reduce by half the number of people who are impoverished due to out-of-pocket health care expenses. By 2030, no one www.thelancet.com/lancetgh Vol 3 (S2) April 2015
Panel: Research in context Systematic review We searched PubMed and Google Scholar for publications in English, without restriction by date, with the terms “catastrophic expenditure”, “surgery”, and “surgical delivery”. We also identified pertinent references from the bibliographies of these publications. Catastrophic expenditure is one of many metrics to address the financial burden borne by individuals seeking health care. As for all similar metrics, it has moderate construct validity but has limitations. Although catastrophic expenditure resulting from surgical conditions has been addressed in small series within individual countries, there has been no systematic review of this subject, and no attempt to construct a global estimate. Few studies have incorporated the financial burden of the cost of getting to care with the cost of care itself. Interpretation To the best of our knowledge, this is the first systematic study to make a global estimate of financial catastrophe due to accessing surgical services and the first to assess medical impoverishment from specific segments of the health sector. We found that catastrophic expenditure from surgery makes up about 22% of the overall incidence of financial catastrophe from medical care in general, and the burden more than doubles when the non-medical costs associated with care are added. Because impoverishment has such a large role in access to surgery—and as a barrier to that access—our hope is that these findings will bring surgery to the forefront of the discussion as countries develop policies to assure financial risk protection from catastrophic health expenses and move towards universal health coverage, as well as to spur more study into the interplay between health improvement and financial catastrophe.
should fall into poverty because of out-of-pocket health care expenses.”14 The results of our analysis highlight that, with more than 30 million of the previously estimated 150 million cases of medical catastrophic expenditure resulting from surgery, no zero target for impoverishment can be met without providing financial risk protection for surgical conditions. Surgery must therefore be considered an integral part in universal health coverage. Importantly, this analysis suggests that countries must take account of the potential catastrophic effects of both medical and non-medical costs in the design of policies. Simply making surgery free at the point of care will not completely alleviate the risk of financial catastrophe to patients; coverage of non-medical costs (for example, vouchers for travel, or some form of negative user fees)20 might be necessary for full attainment of the goal of eliminating medically driven financial catastrophe by 2030. Contributors MGS, AD, BCA, and JGM conceived the study. MGS, BCA, and JGM were responsible for design. MGS, AD, BCA, and KO took part in data acquisition. MGS, AD, and BCA analysed the data. MGS prepared the report and all the other authors revised it. All the authors approved the version to be submitted and are accountable for the results. Declaration of interests MGS received speaking fees from Ethicon for a talk unrelated to this present work. The other authors declare no competing interests. References 1 Scheiber GJ, Gottret P, Fleisher LK, Leive AA. Financing global health: Mission unaccomplished. Health Aff 2007; 26: 921–34. 2 Xu K, Evans DB, Carrin G, Aguilar-Rivera AM, Musgrove P, Evans T. Protecting households from catastrophic health spending. Health Aff (Millwood) 2007; 26: 972–83.
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Mohanty SK, Srivastava A. Out-of-pocket expenditure on institutional delivery in India. Health Policy and Plann 2013; 28: 247–62. Pakseresht S, Ingle GK, Garg S, Singh MM. Expenditure audit of women with breast cancer in a tertiary care hospital of Delhi. Indian J Cancer 2011; 48: 428–37. Reddy GM, Negandhi H, Singh D, Singh AJ. Extent and determinants of cost of road traffic injuries in an Indian city. Indian J Med Sci 2009; 63: 549–56. Reddy GM, Singh A, Singh D. Community based estimation of extent and determinants of cost of injuries in a north Indian city. Indian J Med Sci 2012; 66: 23–29. Nguyen H, Ivers R, Jan S, Pham C. Cost of surgery and catastrophic expenditure in people admitted to hospital for injuries: estimates from a cohort study in Vietnam. Lancet 2015; 385 (Global Surgery special issue): S50. Schreyer P, Koechlin F. Purchasing power parity--measurement and uses. OECD Statistics Brief, 2002. http://www.oecd.org/std/pricesppp/2078177.pdf (accessed July 4, 2014). Weiser TG, Regenbogen SE, Thompson KD, et al. An estimation of the global volume of surgery: a modelling strategy based on available data. Lancet 2008; 372: 139–44. Ortiz I, Cummins M. Global inequality: Beyond the bottom billion. UNICEF social and economic policy working paper, 2011. http:// www.unicef.org/socialpolicy/files/Global_Inequality_ REVISED_-_5_July.pdf (accessed July 8, 2014). Central Statistical Agency [Ethiopia], ICF International. Ethiopia Demographic and Health Survey, 2011. Addis Ababa, Ethiopia and Calverton, MD: Central Statistical Agency and ICF International, 2012. http://dhsprogram.com/publications/publication-fr255-dhsfinal-reports.cfm (accessed Feb 27, 2015). International Institute for Population Sciences. National Family Health Survey (NFHS-3), 2005–06, India. Mumbai: IIPS; 2007. http://www.rchiips.org/nfhs/report.shtml (accessed Feb 27, 2015). National Institute of Population Research and Training, Mitra and Associates, ICF International. Bangladesh Demographic and Health Survey. Dhaka, Bangladesh, and Calverton, MD, USA: NIPORT, Mitra and Associates, and ICF International, 2013. http://dhsprogram.com/pubs/pdf/FR265/FR265.pdf (accessed Feb 27, 2015). Prinja S, Nandi A, Laxminarayan R. Costs, effectiveness, and costeffectiveness of selected surgical procedures and platforms: A summary from across the volume. In: Debas HT, Gawande AA, Jamison DT, Kruk ME, Mock C, Donkor P, eds. Disease Control Priorities in Developing Countries, 3rd edn. Washington, DC: World Bank, 2015. http://www.dcp-3.org/disease-control-prioritiesthird-edition (accessed Feb 11, 2015). World Health Organization, World Bank. Monitoring progress towards universal health coverage at country and global levels: Framework, measures and targets 2014. http://www.who.int/ healthinfo/country_monitoring_evaluation/universal_health_ coverage/en/ (accessed Feb 11, 2015). Institute for Health Metrics and Evaluation. National health accounts visualization 2014. http://vizhub.healthdata.org/nha/ (accessed Aug 31, 2014). Jamison DT, Summers LH, Alleyne G, et al. Global health 2035: a world converging within a generation. Lancet 2013; 382: 1898–955. Salem ABZ, Mount TD. A convenient descriptive model of income distribution: the Gamma distribution. Econometrica 1974; 42: 1115–27. Arsenault C, Fournier P, Philibert A, et al. Emergency obstetric care in Mali: catastrophic spending and its impoverishing effects on households. Bull World Health Organ 2013; 91: 207–16. Groen R, Samai M, Stewart K-A, et al. Untreated surgical conditions in Sierra Leone: a cluster randomised, cross-sectional, countrywide survey. Lancet 2012; 380: 1082–87. Baicker K, Taubman SL, Allen HL, et al. The Oregon experiment— effects of Medicaid on clinical outcomes. N Engl J Med 2013; 368: 1713–22. Shrime MG, Sleemi A, Ravilla TD. Charitable platforms in global surgery: a systematic review of their effectiveness, costeffectiveness, sustainability, and role in training. World J Surg 2014; 39: 10–20.
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Catastrophic expenditure to pay for surgery worldwide: a modelling study Mark G Shrime, Anna J Dare, Blake C Alkire, Kathleen O’Neill, John G Meara
Summary Lancet Glob Health 2015; 3 (S2): S38–44 Department of Global Health and Population, Harvard School of Public Health, Boston, MA, USA (M G Shrime MD); King’s Centre for Global Health, King’s Health Partners, King’s College London, London, UK (A J Dare MBChB); Department of Otology and Laryngology, Harvard Medical School, Boston, MA, USA (M G Shrime, B C Alkire MD); Office of Global Surgery, Massachusetts Eye and Ear Infirmary, Boston, MA, USA (M G Shrime, B C Alkire); University of Pennsylvania Medical School, Philadelphia, PA, USA (K O’Neill BS); Program in Global Surgery and Social Change, Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA (M G Shrime, B C Alkire, J G Meara MD); and Department of Plastic and Oral Surgery, Boston Children’s Hospital, Boston, MA, USA (J G Meara) Correspondence to: Dr Mark G Shrime, Massachusetts Eye and Ear Infirmary, 243 Charles Street, Boston, MA 02114,USA [email protected]
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Background Approximately 150 million individuals worldwide face catastrophic expenditure each year from medical costs alone, and the non-medical costs of accessing care increase that number. The proportion of this expenditure related to surgery is unknown. Because the World Bank has proposed elimination of medical impoverishment by 2030, the effect of surgical conditions on financial catastrophe should be quantified so that any financial risk protection mechanisms can appropriately incorporate surgery. Methods To estimate the global incidence of catastrophic expenditure due to surgery, we built a stochastic model. The income distribution of each country, the probability of requiring surgery, and the medical and non-medical costs faced for surgery were incorporated. Sensitivity analyses were run to test the robustness of the model. Findings 3·7 billion people (posterior credible interval 3·2–4·2 billion) risk catastrophic expenditure if they need surgery. Each year, 81·3 million people (80·8–81·7 million) worldwide are driven to financial catastrophe—32·8 million (32·4–33·1 million) from the costs of surgery alone and 48·5 million (47·7–49·3) from associated non-medical costs. The burden of catastrophic expenditure is highest in countries of low and middle income; within any country, it falls on the poor. Estimates were sensitive to the definition of catastrophic expenditure and the costs of care. The inequitable burden distribution was robust to model assumptions. Interpretation Half the global population is at risk of financial catastrophe from surgery. Each year, surgical conditions cause 81 million individuals to face catastrophic expenditure, of which less than half is attributable to medical costs. These findings highlight the need for financial risk protection for surgery in health-system design. Funding MGS received partial funding from NIH/NCI R25CA92203. Copyright © Shrime et al. Open Access article distributed under the terms of CC BY-NC-ND.
Introduction Access to health care is not always free, and its use commonly carries a risk of impoverishment. In many parts of the world, out-of-pocket payments for health care remain the predominant form of health financing.1 About 150 million cases of catastrophic expenditure— defined as an expenditure of more than 40% of non-food household expenditure2 or 10% of overall household expenditure3—occur each year as a result of accessing care.2 Little is known, however, about the magnitude of catastrophic expenditure attributable to various parts of the health system—both worldwide and in countries at differing stages of development. In particular, the contribution of surgical care to catastrophic health expenditure has not previously been estimated. Access to surgery is increasingly recognised as a crucial component of a functioning health system for countries at all stages of development.4 About 30% of the global burden of disease is surgical,5 and the delivery of basic, life-saving surgical care is highly cost-effective in both high-income countries and those of low and middle income.6 However, cost-effectiveness at the population level does not necessarily translate into affordability for an individual patient. In the absence of financial risk protection measures, accessing surgery can be catastrophically
expensive for patients. Because common effectiveness measures (such as quality-adjusted or disability-adjusted life years) do not explicitly capture the potentially impoverishing effects of care, these financial effects on individuals have tended to be overlooked. The need for surgical care can be time-critical, unpredictable, and resource-intensive, so surgery is difficult to plan or save for. In addition, treatment seeking is more impoverishing for surgical conditions than for other conditions.7 As well as the financial burden of paying for surgical services, individuals face the costs of getting to care. These non-medical costs of transportation, food, and lodging8 are substantial and can themselves drive patients into poverty.9 The high costs associated with accessing surgical care not only increase the chance of catastrophic health expenditure, but can also act to prevent healthseeking behaviour, especially among the poor.10 Protection of households against catastrophic health expenditure has emerged as a leading policy goal for global health. The WHO,11 the World Bank,12 and the UN13 have lately renewed calls for the introduction of universal health coverage and the assurance of financial risk protection against the costs of illness. The World Bank stated that, “By 2030, no one should fall into poverty because of out-of-pocket health care expenses.” 14 www.thelancet.com/lancetgh Vol 3 (S2) April 2015
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A greater understanding of the financial catastrophe attributable to various health interventions, including surgical care, has therefore become necessary to inform policy. Our aim was to estimate the number of patients worldwide who experience catastrophic expenditure each year from accessing surgery. We also investigated how rates of catastrophic expenditure from surgery change according to national development status and individual wealth quintile. We postulated that a large portion of worldwide financial catastrophe caused by medical care would be attributable to surgery, and that this burden would fall most heavily on the poor.
Methods Model construction Several thresholds have been proposed for catastrophic expenditure. Here, we chose to use a threshold of 10% of overall household expenditure,15 which we explored in sensitivity analyses. An individual faces catastrophic expenditure when the out-of-pocket costs faced to access care are greater than this threshold. That is: OOP × c ≥ ty where c is the total cost of a service, OOP the out-ofpocket proportion of that cost, y household expenditure before care was sought, and t the threshold, expressed as a proportion of household expenditure, at which catastrophic expenditure is said to have occurred. For example, an individual whose expenditure before health care was sought was $1000 would face catastrophic expenditure if he or she had to pay more than $100 for health care. The methodology behind the application of the equation to the world population is given in detail in the appendix. Briefly, the income distribution of a country’s population was modelled, and the proportion of the population undergoing surgery estimated, by wealth quintile, from published data (see data sources, below, and appendix p 2–6). For individuals who need surgical services, an out-of-pocket cost was assessed. If that amount was greater than 10% of their preceding income, they were counted as having experienced catastrophic expenditure. This calculation was repeated across all countries to obtain a global estimate. To estimate the number of individuals at risk of catastrophic expenditure, the same calculation was repeated, with the probability of getting surgery factored out.
Data sources World Bank data were used for each of the necessary variables in 199 countries. Household expenditure was used where available.16 If it was not available, gross domestic product (GDP) per person17 was used as a proxy. WHO-CHOICE estimates for the unit cost of a caesarean section were taken to represent costs of surgery,18 an www.thelancet.com/lancetgh Vol 3 (S2) April 2015
assumption that was tested in sensitivity analyses. According to WHO, this cost includes “initiation of labour at referral level, diagnosis of obstructed labour and referral, devices and medicines associated with caesarean delivery, operative facility time, medical human resources time, management of shock including hysterectomy and blood transfusion (assumed for 1% of procedures), postoperative hospital stay for stabilisation, programme administration, training, and the corresponding office space, electricity, and other services, as well as various standard consumables and equipment”.18 In probabilistic sensitivity analysis, a multiplier was applied to this cost. The reported cost for one country (Iceland) was a significant outlier. Its cost was taken as the result of a linear regression on its GDP per head. Out-of-pocket expenditure was calculated as a proportion of total health expenditure.19 The model was run with and without the inclusion of non-medical costs faced by patients when accessing surgical services (eg, transportation, lodging, food). When these costs were included, we used a conservative estimate consistent with estimates from Ethiopia,20 Bangladesh,7,21–23 India,24–29 and Vietnam;30 specifically, the non-medical costs were constructed as a multiplier to direct medical costs on the basis of these data, with the introduction of error from the varied estimates. This approach was examined in detail in sensitivity analyses, below. All costs, expenditure, and income estimates were adjusted to 2007 international dollars, by use of UN purchasing power parity conversion factors and World Bank GDP deflators, as previously described.31 2007 was chosen because it was the year for which the most robust primary data were available. The probability of accessing surgery was taken from previously published estimates.32 For countries in which estimates of cases per population were not available, regional estimates for countries with similar overall health-care expenditure per head were used instead. Similarly, when Gini indices for individual countries were not available, regional indices were used.33 The
See Online for appendix
Cases of catastrophic expenditure (95% PCI) Base case (without non-medical costs) Base case (including non-medical costs)
32 768 603 (32 447 074–33 090 131) 81 262 319 (80 793 101–81 731 536)
Increasing non-medical costs
145 395 830 (144 777 380–146 014 280)
Lowered threshold for catastrophic expenditure (without non-medical costs)
63 268 868 (61 608 121–64 929 614)
Lowered threshold for catastrophic expenditure (including non-medical costs)
119 781 104 (117 504 932–122 057 276)
Average cost of surgery halved (without non-medical costs) Average cost of surgery halved (with non-medical costs) Average cost of surgery doubled (without non-medical costs) Average cost of surgery doubled (with non-medical costs)
7 692 269 (7 255 498–8 129 041) 28 034 971 (27 127 473–28 942 470) 79 232 250 (77 546 379–80 918 122) 135 634 968 (133 213 154–138 056 782)
PCI=posterior credible interval.
Table: Cases of catastrophic expenditure per year, by assumption
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probability of surgery was broken down by quintiles as follows: access to caesarean section was calculated for Ethiopia, India, and Bangladesh from their respective Demographic and Health Surveys.34–36 Access by quintile was compared with mean access, and the average proportion of access faced by people in each quintile was then taken as an access multiplier for the model as a whole. The assessment of the gradient was limited by the data available and is discussed below. The following countries did not have sufficient data available: the Cook Islands, North Korea, Nauru, Niue, Puerto Rico, Somalia, South Sudan, and Taiwan. Data were missing for these countries from both the World Bank economic and population indicators and from estimates of surgical delivery. The combined population of these countries represents only 1·03% of the overall global population; we therefore made an assumption of random missingness, and the results from the remaining countries were scaled up linearly to encompass the world’s population.
Scenario and sensitivity analyses Sensitivity analyses were done to test the robustness of our results. Because the cost of surgery is a driver of the model, as seen in the equation, and because the cost of a caesarean section could under-represent the cost of surgery overall,37 we ran a sensitivity analysis on the average cost of an operation. We ran a similar sensitivity analysis on the average non-medical costs faced by patients, with both high and low estimates from the sources listed above. WHO and the World Bank have
lately redefined catastrophic expenditure as any spending that is more than 25% of post-subsistence expenditure.38 With application of the linear transformation that previously converted thresholds based on postsubsistence expenditure to thresholds based on total expenditure, this new definition translates to 6·25% of overall expenditure. We did a sensitivity analysis with this value as the cut-off. Finally, the World Bank estimates of out-of-pocket expenditure differ from estimates published directly from examination of national health accounts.39 We substituted the latter estimates where available in a fourth sensitivity analysis. First-order heterogeneity was modelled by use of Monte Carlo simulations at each of the probability nodes. Second-order uncertainty was incorporated by drawing from probability distributions around c × OOP, the surgical cost scaling factor, and the proportion of the population accessing surgical care (appendix p 7). 200 parameter sets were drawn from each distribution; 1000 iterations of each parameter set were run, over all 199 countries, and for each of the three model versions. The mean and 95% posterior credible intervals (PCI) are reported for overall numbers of cases of catastrophic expenditure and for cases per million in the population. Model construction and data analysis were performed in Microsoft Excel 2011 and R version 3.0.2 (www. rproject.org).
Role of the funding source This study had no direct funding. No entity besides the authors had a role in any part of this study, including
Risk of catastrophic expenditure if surgery is required 1·0 0·9 0·8 0·7 0·6 0·5 0·4 0·3 0·2 0·1 0
Figure 1: Risk of catastrophic expenditure if surgical care is necessary Red=high risk. Yellow=low risk. A risk of catastrophic expenditure of 0·5 means that, conditional on needing surgery, an individual has a 50% chance of going into financial catastrophe were he or she to get that surgery.
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conception and design, data acquisition, data analysis, report preparation, revision, or the decision to submit for publication. All authors had access to the data in the study.
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Without non-medical costs With non-medical costs
Proportion of surgical patients facing catastrophic expenditrure (%)
8 7 6 5 4 3 2 1 0 Poorest
B Proportion of catastrophic expenditure (%)
Globally, an estimated 32·8 million (95% PCI 32·4–33·1 million) cases of catastrophic expenditure occur each year as a result of patients accessing surgical services (table) Roughly 3·7 billion individuals (3·2–4·2 billion) are at risk of financial catastrophe should they need surgical care. Most of these people live in sub-Saharan Africa, and south and southeast Asia (figure 1). Catastrophic expenditure to pay medical costs falls primarily on the poor, with differences by region. Worldwide, about 6·1% (5·2–7·0) of the poorest patients who undergo surgery face catastrophic expenditure, whereas less than 0·10% (0·01–0·19) of the richest do. In low-income countries, this gradient is nearly flat, but in upper-middle and high-income countries, nearly all catastrophic expenditure falls on the poor (figure 2). When the multisectoral nature of health seeking was examined, the estimates of catastrophic expenditure increased greatly. Direct non-medical costs to patients (transportation, lodging, food, and informal payments) produced an additional 48·5 million cases of catastrophic expenditure (47·7–49·3), leading to a total estimate of 81·3 million cases (80·8–81·7 million). When these costs were counted in the model, the gradient among wealth quintiles flattened somewhat. Globally, risk of catastrophic expenditure increased, more in the richer than in the poorer quintiles (figure 2). Previous estimates of catastrophic expenditure have used the threshold used in our base case analysis. Newer thresholds have, however, been proposed. When we lowered the threshold for counting a case of catastrophic expenditure to 6·25%, the estimated number of cases of catastrophic expenditure predictably increased. At this threshold, 63·3 million (61·6–64·9 million) cases of catastrophic expenditure were predicted as a result of medical costs alone, and 119·8 million (117·5–122·1 million) cases were predicted as a result of medical and non-medical costs together. When we halved the average cost of surgery, the number of cases of catastrophic expenditure fell to 7·7 million (7·3–8·1 million) for direct medical costs only and 28·0 million (27·1–28·9 million) for medical and nonmedical costs together. When the cost of an average surgical procedure was estimated to be double that of a caesarean section, the estimate of cases of catastrophic expenditure increased to 79·2 million (77·5–80·9 million) for direct medical costs and 135·6 million (133·2–138·1 million) for medical and non-medical costs together. Our estimates were sensitive to assumptions around the magnitude of direct non-medical costs, but only moderately. An increase of six times in these costs increased the estimate of total cases of catastrophic
World
9
Poor
Middle Wealth quintile
Rich
Richest
Low-income countries
C
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Upper–middle-income countries
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20 18 16 14 12 10 8 6 4 2 0
D Proportion of catastrophic expenditure (%)
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20 18 16 14 12 10 8 6 4 2 0 Poorest
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Figure 2: Catastrophic expenditure by wealth quintile and national income group, conditional on seeking surgery
expenditure by only four times. The higher the estimate of non-medical costs, the more catastrophic expenditure people in the richer quintiles faced. Our results were robust to the source of out-of-pocket proportion estimates. Use of estimates directly from national health accounts39 did not change our estimates significantly.
Discussion Globally, 3·7 million people are at risk of financial catastrophe should they need surgery, and 33 million face catastrophic expenditure each year accessing and paying for surgical care. This number represents about S41
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22% of the 150 million individuals who face catastrophic expenditure accessing the health system each year,2 commensurate with the proportion of global disease burden that is surgical.5 Financial catastrophe affects individuals in countries of low and middle income most severely; within any one country, the poorest people fare the worst. Access to health care involves more than simply paying for services. Non-medical costs, such as transportation, lodging, and food, can contribute substantially to catastrophic expenditure.20 These costs, however, are not included in many estimates of out-of-pocket financial expenditures.2 When these costs were accounted for in our model, an additional 48·5 million cases of catastrophic expenditure were predicted, leading to an overall estimate of 81 million annual cases of catastrophic expenditure from accessing surgical care worldwide. These cases of financial catastrophe are not being created by the addition of these non-medical costs; they are already happening, but have not been accounted for in models that consider only the direct cost of services. Our results show an interesting, if somewhat counterintuitive, finding; financial catastrophe from surgical access is more common in individuals in lower-middleincome countries than in those in low-income countries. The reason is that, on average, the cost of surgery, as a function of income, is 15% higher in lower-middle-income countries than in low-income countries, which suggests that, as the financial status of a country improves, the costs of seeking surgery could increase more rapidly than average household income. This finding highlights the importance of incorporating financial risk protection into health systems at all stages of development, particularly as countries transition from a low-income to lower-middleincome group. This concept is consistent with findings by the Commission on Investing in Health.40 When non-medical costs are taken into account, catastrophic expenditure appears to accrue more heavily on people in the richer wealth quintiles. This finding is artifactual. Poor people have already hit the catastrophic expenditure threshold, whether or not non-medical costs are included. Because catastrophic expenditure does not measure the depth of impoverishment, addition of further costs to those already impoverished is not counted. The apparent increase in catastrophic expenditure among the better off arises because increased use among the rich makes the model more sensitive to catastrophic expenditure resulting from nonmedical costs payable by these individuals. This analysis has several strengths and limitations. First, the definition of catastrophic expenditure itself is controversial;3,9,15 we have chosen one definition in our base case and another in our sensitivity analysis, but we recognise that, in the absence of a universally accepted definition, these remain open to debate. More importantly, however, catastrophic expenditure captures only individuals who actually pay for services. It S42
cannot address patients who need services but cannot afford them, nor the impoverishment caused if services are not obtained by the primary income-earner in a household. This weakness is inherent in most current measures of the financial burden of health care. Borrowed from taxation studies, these metrics40—any expenditure, amount of expenditure, catastrophic expenditure, poverty head count, poverty gap or squared poverty gap, indebtedness, and borrowing and selling to pay for care—all inherently count only payment made. They do not account for a lack of access and do not include indirect costs such as lost wages and decreased economic productivity. As a result, the financial impact that results from a lack of access cannot be fully captured by these metrics. Our choice of threshold for catastrophic expenditure could lead to an underestimation in countries of low and middle income. Individuals whose expenditure on food forms a substantial part of their total expenditure would face financial ruin with smaller out-of-pocket spending than is captured in this model. In addition, expenditures for individuals near the poverty line might not count as catastrophic, by definition, but could still have devastating effects on household welfare. This model is based on limited data. The income distribution in individual countries is approximated by a statistical distribution; although it fits population income distributions on average,41 it might do so more or less accurately in countries in which most of the workforce is based in the informal sector. Similarly, we base our surgical costs on the costs of caesarean section because this is the only procedure for which we had reliable global data. In the absence of other data, we chose to inflate and deflate this estimate probabilistically, as well as to examine it explicitly in sensitivity analyses, mitigating this weakness. Of note, although many countries have financing in place specifically for caesarean sections, this financing does not always protect against catastrophic expenditure.42 The gradient of use across nations comes from a small sample of countries, which introduces uncertainty into our equity results. Data on disease burden are limited also. This limitation, however, does not affect our results; because this paper looks at catastrophic expenditure from patients actually accessing the surgical system, as opposed to latent demand for surgical services, the studies on surgical disease burden that have been done will be important for any further scale-up of a surgical system.43 Data on insurance are also limited—although out-ofpocket data used here will, by definition, take the presence of insurance into account, the purpose of insurance is to smooth an out-of-pocket function. Evidence suggests that the expansion of insurance does increase health-care use, but with varying effects on actual health outcomes.44 Although the institution of an insurance scheme in countries without one might allay some catastrophic expenditure, it does so with an www.thelancet.com/lancetgh Vol 3 (S2) April 2015
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important caveat; because surgical conditions are commonly associated with large up-front costs, even a patient whose out-of-pocket spending is reimbursed by insurance will still face catastrophic expenditure before the reimbursement. Finally, this paper is a static picture; the modelling techniques used cannot project the effects of financial catastrophe over time. Not enough evidence is available to construct a global model addressing future financial impact. The strengths of this study, however, lie in what it shows about the nature of global catastrophic health expenditure (panel). This model does what many other estimates of catastrophic expenditure have not done. First, it includes the direct non-medical costs that individuals face, giving a more realistic estimate of impoverishment. In the previous global estimate of medical impoverishment, Xu and colleagues2 noted that no data on transportation costs were available, so the analysis underestimated the financial consequences of obtaining care. This particular underestimation is avoided in our analysis. By taking into account the full costs of care, we hope to provide a more complete picture of the need for financial risk protection. The previous global estimate of medical impoverishment2 did not break the impoverishment down by disease condition. To our knowledge, no study has proposed a global estimate for catastrophic expenditure due, for example, to chronic disorders or critical care. This step is important—since the elimination of medical impoverishment is the stated goal of many world bodies,14 detailed information on the distribution of financial catastrophe is necessary to inform sound policies aimed at preventing it. The nature of a stochastic model such as ours allows for an explicit assessment of heterogeneity and uncertainty around parameters. Any global estimate is fraught with uncertainty—this model makes the uncertainty explicit. The sensitivity analyses also document the factors in the model on which the results are reliant. Redefinition of the threshold at which catastrophic expenditure is counted, for example, drastically changes the number of individuals with catastrophic expenditure per year. This study approached the question of financial catastrophe by use of a different modelling technique from other estimates; nevertheless, it arrived at estimates that are in line with previous ones, lending credence both to this modelling technique and to the external validity of the estimates. Surgery is a substantive part of any health system,4,20,45 and surgical conditions can uniquely put patients at risk of financial catastrophe because they tend to be timecritical, life-threatening, and fraught with large up-front costs. In January, 2014, the President of the World Bank, Jim Y Kim, detailed the Bank’s goals for catastrophic expenditure: “The proposed target is, by 2020, to reduce by half the number of people who are impoverished due to out-of-pocket health care expenses. By 2030, no one www.thelancet.com/lancetgh Vol 3 (S2) April 2015
Panel: Research in context Systematic review We searched PubMed and Google Scholar for publications in English, without restriction by date, with the terms “catastrophic expenditure”, “surgery”, and “surgical delivery”. We also identified pertinent references from the bibliographies of these publications. Catastrophic expenditure is one of many metrics to address the financial burden borne by individuals seeking health care. As for all similar metrics, it has moderate construct validity but has limitations. Although catastrophic expenditure resulting from surgical conditions has been addressed in small series within individual countries, there has been no systematic review of this subject, and no attempt to construct a global estimate. Few studies have incorporated the financial burden of the cost of getting to care with the cost of care itself. Interpretation To the best of our knowledge, this is the first systematic study to make a global estimate of financial catastrophe due to accessing surgical services and the first to assess medical impoverishment from specific segments of the health sector. We found that catastrophic expenditure from surgery makes up about 22% of the overall incidence of financial catastrophe from medical care in general, and the burden more than doubles when the non-medical costs associated with care are added. Because impoverishment has such a large role in access to surgery—and as a barrier to that access—our hope is that these findings will bring surgery to the forefront of the discussion as countries develop policies to assure financial risk protection from catastrophic health expenses and move towards universal health coverage, as well as to spur more study into the interplay between health improvement and financial catastrophe.
should fall into poverty because of out-of-pocket health care expenses.”14 The results of our analysis highlight that, with more than 30 million of the previously estimated 150 million cases of medical catastrophic expenditure resulting from surgery, no zero target for impoverishment can be met without providing financial risk protection for surgical conditions. Surgery must therefore be considered an integral part in universal health coverage. Importantly, this analysis suggests that countries must take account of the potential catastrophic effects of both medical and non-medical costs in the design of policies. Simply making surgery free at the point of care will not completely alleviate the risk of financial catastrophe to patients; coverage of non-medical costs (for example, vouchers for travel, or some form of negative user fees)20 might be necessary for full attainment of the goal of eliminating medically driven financial catastrophe by 2030. Contributors MGS, AD, BCA, and JGM conceived the study. MGS, BCA, and JGM were responsible for design. MGS, AD, BCA, and KO took part in data acquisition. MGS, AD, and BCA analysed the data. MGS prepared the report and all the other authors revised it. All the authors approved the version to be submitted and are accountable for the results. Declaration of interests MGS received speaking fees from Ethicon for a talk unrelated to this present work. The other authors declare no competing interests. References 1 Scheiber GJ, Gottret P, Fleisher LK, Leive AA. Financing global health: Mission unaccomplished. Health Aff 2007; 26: 921–34. 2 Xu K, Evans DB, Carrin G, Aguilar-Rivera AM, Musgrove P, Evans T. Protecting households from catastrophic health spending. Health Aff (Millwood) 2007; 26: 972–83.
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