The Global Economic Consequences of Selected Surgical Diseases: A Modelling Study

Abstract

Background

The surgical burden of disease is substantial, but little is known about the associated economic consequences. We estimate the global macroeconomic impact of the surgical burden of disease due to injury, neoplasm, digestive diseases, and maternal and neonatal disorders from two distinct economic perspectives.

Methods

The value of lost output (VLO) approach projects annual market economy losses during 2015–2030 by relating disease mortality to changes in the labor force and gross domestic product (GDP). The value of lost welfare (VLW) approach uses a broader measure of nonmarket losses based on a concept termed the value of a statistical life and estimates the present value of long-run welfare losses resulting from mortality and short-run welfare losses resulting from morbidity incurred during 2010. Sensitivity analyses are performed for both approaches.

Findings

During 2015–2030, the VLO approach projects surgical conditions to result in losses of 1·25%of potential GDP, or$20·7 trillion (2010 USD, PPP). When expressed as a proportion of potential GDP, annual GDP losses are greatest in low- and middle-income countries, with up to a 2·5% loss in output by 2030. When nonmarket losses are assessed (VLW), the present value of economic welfare losses is estimated to be equivalent to 17% of 2010 GDP, or $14.5 trillion (2010 USD, PPP). Neoplasm and injury account for greater than 95% of total economic losses in each approach, but maternal, digestive, and neonatal disorders, which represent only 4% of losses in high-income countries in the VLW approach, contribute to 26% of losses in low-income countries.

Interpretation

The macroeconomic impact of surgical disease is substantial and inequitably distributed. When paired with the growing number of favorable cost-effectiveness analyses of surgical interventions in low- and middle-income countries, our results suggest that building surgical capacity should be a global health priority.

Funding

Partial funding for Dr. Shrime from NIH/NCI R25 CA92203.

INTRODUCTION

The global burden of surgical diseasehas only recently been defined and subsequently estimated. While original estimates suggested that up to 11% of global morbidity and mortality is secondary to surgical disease,¹ more recent efforts have suggested that number is a vast underestimate and that up to 33% of the global burden of disease is surgical.²

While an understanding of surgical morbidity and mortality is of paramount concern to researchers and policy-makers alike, the downstream consequences of this burden arealso of importance. One manner in which to contextualize the impact of disease is to estimate the economic consequencesit imposes. Although there is continued debate in the economic literature regarding how health and income are connected,³ there is strong evidence that improved population health contributes positively to aggregate economic growth.^4–10 Broadly speaking, the effect of poor health can be examined at the microeconomic level, in which individuals, households, firms, or other specified economic agents are studied, or at the macroeconomic level, in which the broader impacts on society as a whole are assessed.¹¹

While there have been studies that investigate the economic impact of specific surgical diseases at regional and global levels,^12–14 little is known about the global economic impact of a more comprehensive set of surgical conditions. Using two distinct macroeconomic approaches, this study sought to estimate: (a) the effect of surgical disease mortality on annual global economic outputduring 2015–2030, and (b) the effect of surgical disease during a single year, 2010, on a more broadly defined measure of economic welfare which incorporates a combination of long-run effects of mortality and short-run effects of morbidity.

METHODOLOGY

The Surgical Burden of Disease for Selected Conditions

We examined five major surgical disease categories: neoplasm, injury, maternal disorders, neonatal disorders, and digestive disorders. We assumed that only a portion of the burden of each disease category is surgical. To this end, we used results from a survey instrument by Shrime et. al., which asked respondents, “What proportion of patients with the following conditions would, in an ideal world, require a surgeon for management?”for each of the 21 Institute for Health Metric and Evaluation’s (IHME) Global Burden of Disease categories.^2,15,16

We selected the disease groups listed above as they have been repeatedly acknowledged to contribute to a large burden of surgical disease;^1,17 using Shrime’s survey instrument, they contribute to greater than 85% of all surgical deaths.² Table 1 provides the mean responses from the survey, and the specific diseases contained within each IHME category are listed in appendix table 1.¹⁸ Table 1 also gives an estimate of the global burden of the surgical proportions of the included conditions for 2010 using IHME estimates.^15,16 The survey instrument and the definition of surgical disease are discussed further in the appendix.

Table 1.

Percentage of patients with each condition requiring surgeon for management and implied burden of disease in 2010 for included conditions by deaths (thousands) and DALYs^b (YLL and YLD)(thousands)^2,15,16

Disease	Percentage	Deaths	YLLs b	YLDs b
Digestive Disorders	30·3%	337	8,246	1,658
Injury a	60·8%	3,085	141,283	30,144
Maternal Disorders	36·7%	93	5,251	657
Neonatal Disorders	27·3%	611	52,594	2,586
Neoplasm	62·0%	4,943	113,995	2,777

^a: The mean surgical burden of disease estimates from Shrime et. al. presented.

^b: DALY = disability-adjusted life year, YLL = non-discounted years of life lost (mortality) using IHME standardized life-expectancy, YLD = years lost to disability (morbidity)

Overview of Approaches

This study uses two approaches to describe the macroeconomic consequences of surgical disease (Figure 1). These approaches were chosen as both allow for global economic modeling in the face of limited data, and each provides different information. The first is based on a model supplied by the World Health Organization (WHO) known as EPIC (Projecting the Economic Cost of Ill-health). We use the EPIC model to project annual market economy losses during 2015–2030, and to be consistent with others who have used it,¹⁹ term this approach the value of lost output (VLO). The second approach estimates the value of lost economic welfare (VLW) resulting from surgical disease in 2010. The counterfactual in both approaches is absence of disease. Estimates from both approaches are gross estimates, as they are not net of the cost of treatment.

Figure 1.

Overview of economic approaches.

The two approaches differ in two important ways: the definition of economic loss, and the time period over which the loss is calculated. The VLO approach relates disease mortality to the labor supply and capital accumulation of a country over time. Changes in these factors result in decreased output of marketed goods and services, as measured in forgone gross domestic product (GDP). The EPIC model does not incorporate disease morbidity, which also affects GDP. In this study, the VLO approach estimates the effects of mortality on output in a given year during 2015–2030. It is therefore a short-run measure, although the annual estimates can be summed to calculate cumulative impacts.

The VLW, also termed the full-income approach,²⁰ relies on a concept known as the value of a statistical life (VSL), which incorporates nonmarket losses, such as forgone leisure, non-health consumption, and the value of good health in and of itself. Consistent with prior studies of a similar scope as this one,^19,21,22 we utilize the VSL to value disability-adjusted life years (DALYs), which captures both mortality and morbidity due to a disease in one metric. Due to the manner in which DALYs are calculated,¹⁶ the VLW approach estimates the long-run effects of life-years lost secondary to mortality, which is measured from an incidence perspective. Mortality estimates therefore include the effects in 2010 plus the present value of future effects. Morbidity, however, is measured from a prevalence perspective, and therefore DALYs only capture the effects of poor health in 2010. Although a case of nonfatal surgical disease that occurred in 2010 could have persistent health effects, future morbidity effects of incident cases in 2010 are not what the current global burden of disease approach measures; rather, the prevalence of the disease of interest is estimated for 2010, and consequently this approach includes morbidity from diseases that were diagnosed prior to 2010.”¹⁸ Since the VLW estimates include nonmarket welfare losses due to mortality and morbidity, and, in the context of mortality represent long-run losses, they can be expected to be many times larger than the VLO estimates, which account only for market losses due to mortality (not morbidity) in the short-term.

Given data availability, a total of 128 countries were evaluated with the VLO approach (Appendix Table 2), and 175 countries were evaluated with the VLW approach (Appendix Table 3). Results are presented in 2010 United States dollars (USD) and adjusted for purchasing power parity (PPP).²³ ThePPP method compares the price levels of a fixed basket of goods between countries to establish a currency conversion rate, such that the price of the basket of goods is the same in both countries when stated in the reference currency, usually the United States dollar. For each approach, countries were evaluated by IHME region and their respective 2010 World Bank income classification.^18,23

The supplementary appendix provides the mathematical details, assumptions, and data sources for each approach.

Sensitivity Analyses

For each approach, we account for uncertainty in the estimation of the burden of disease by utilizing the uncertainty intervals given by the Institute for Health Metrics and Evaluation (IHME)¹⁸ in addition to a lower and upper bound estimate of the proportion of disease considered to be surgical, which we derive from 95% confidence intervals from Shrime’s survey. This was performed as a two-way sensitivity analysis in which the models were run with the upper and lower bounds from Shrime and IHME. Although probabilistic sensitivity analysis would have been preferred, the lack of information regarding the distribution and meaning of IHME uncertainty intervals precludes such analysis. Our baseline results are presented with these intervals for comparison. For the VLW approach we also test assumptions regarding the reference VSL and how VSL is correlated with income, discussed in depth in the appendix, to account for uncertainty in VSL estimates.²⁴ Finally, for each approach, economic losses are presented without PPP conversion to compare our estimates with results from similar studies.^2,19

ROLE OF THE FUNDING SOURCE

The funding agency played no role in the acquisition or analysis of data, manuscript writing, or the decision to submit.

RESULTS

Value of lost output (2015–2030)

One-hundred and twenty-eight countries with a combined population of 6·4 billion people (2013 population),²³ or 90% of the global population, were evaluated with the value of lost output approach (Appendix Table 3). When aggregated by World Bank income classification, 75% and 90% of low-income countries’ population and lower-middle income countries’ population were assessed, respectively. Greater than 95% of the upper-middle income and high-income groups’ populations were evaluated.

During 2015–2030, and using Shrime’s mean estimates, the surgical component of the diseases included in this study is estimated to result in a cumulative loss of $20·7 trillion (2010 USD, PPP), or 1·25% of projected economic output across the 128 countries included in this study (Figure 2). This aggregate estimate is sensitive to uncertainty with respect to the burden of disease and the proportion of disease that is considered surgical, ranging from $12·1 trillion to$33.2 trillion(Table 2). Annual losses as a share of total GDP are projected to rise, approximately doubling for all income groups between 2015 and 2030 (Figure 3). They are also unevenly distributed by World Bank income classification and IHME region (Figure 3, 4). Ninety-six percent of losses are projected to be secondary to injury and neoplasm, but the drivers of lost economic output vary significantly by region (Figure 4). Results by country and disease are given in appendix table 3.

Figure 2.

Annual and cumulative gross domestic product losses secondary to surgical disease with baseline assumptions and values.

Table 2.

Total value of gross domestic product losses secondary to surgical diseases, 2015–2030 (VLO)(Billions 2010 USD, PPP)

Disease	Baseline	Lower Bound a	Upper Bound
Digestive Disorders	$470	$220	$1,010
Injury	$7,860	$4,330	$13,240
Maternal Disorders	$80	$20	$220
Neonatal Disorders	$190	$70	$360
Neoplasm	$12,120	$7,450	$18,360
Total	$20,720	$12,090	$33,190

^a: The upper and lower bound estimates are the result of accounting for uncertainty in the surgical burden of disease. Please see methods for details.

Figure 3.

Percent loss in GDP secondary to surgical disease by World Bank Income Group during 2015–2030.

Figure 4.

Percent change in GDP secondary to surgical disease in 2030 by IHME region.¹⁸ The blue bars represent the losses from all five studied diseases, while the lines represent the relative contribution of each condition

Value of lost welfare (2010)

One-hundred and seventy-five countries with a population of 6·9 billion (2013), or 97% of the global population, were evaluated with the value of lost welfare (VLW) approach (Appendix Table 4). When aggregated by World Bank income classification, 90% of the population of low-income countries was evaluated, and greater than 97% of the population of the remaining groups was included.

Economic welfare losses (VLW) do not represent actual losses in GDP, but they can be expressed relative to GDP to provide a sense of scale. Our baseline VSL assumptions suggest that the value of economic welfare losses in 2010 for the countries included in this study were equivalent to 17% of their 2010 GDP, or $14·5 trillion(2010 USD, PPP) (Table 3). When burden of disease uncertainty was accounted for, the estimates ranged from $8 ·7 trillion to $22·4 trillion. Welfare losses secondary to mortality, which are long-run estimates, make up $11·4 trillion of the estimated impact, while the short-run effects of morbidity incurred in 2010 contributed $3·1 trillion in losses. Our aggregate estimates are moderately sensitive to variations in the relationship between VSL and income, and assuming otherwise baseline values range between $12·0 trillion and $16·9 trillion (appendix table 2). If the reference VSL is adjusted from the Environmental Protection Agency’s²⁵ recommendation of $7.6 million (2006 USD) to the Organization for Economic Development and Cooperation’s recommendation of $3.0 million (2005) USD,²⁶ the aggregate estimate falls to $8·2 trillion if all other assumptions are held constant. Injuries and neoplasm contribute to 95% of total economic losses. When stratified by income group, maternal, neonatal, and digestive disorders on average make up 26% and 14% of total losses in low-income and lower-middle income countries, respectively, compared to 4% in high-income countries (Figure 5). Results by country and disease are given in appendix table 4.

Table 3.

Total value of economic welfare losses by disease^a (Billions 2010 USD, PPP)

	Baseline		Lower Bound		Upper Bound
Disease	Mortality	Morbidity	Mortality	Morbidity	Mortality	Morbidity
Digestive Disorders	$297	$139	$229	$68	$570	$315
Injury	$3,465	$2,392	$2,736	$1,496	$5,541	$3,936
Maternal Disorders	$52	$27	$26	$8	$132	$149
Neonatal Disorders	$237	$105	$1,591	$73	$442	$222
Neoplasm	$7,383	$398	$2,281	$190	$10,668	$470
Total	$11,434	$3,061	$6,863	$1,835	$17,353	$5,092

^a: The upper and lower bound estimates are the result of accounting for uncertainty in the surgical burden of disease. Please see methods for details.

Figure 5.

Total value of annual economic welfare losses secondary to surgical disease by World Bank Income classification using baseline assumptions regarding VSL and income; please see appendix for details.

DISCUSSION

This study demonstrates that surgical conditions impose a massive and previously unrecognized economic burden on a global scale. The value of lost output (VLO) approach, which accounts for market losses during 2015–2030, suggests that surgical diseases will result in a cumulative loss of 1·25% of potential GDP, or $20·7 trillion dollars (2010 USD, PPP), for the 128 countries we examined (Table 2, Figure 2). These losses are expected to rise over time, and they will have the greatest impact on the most vulnerable populations as low-income and lower-middle-income countries are projected to experience losses that are almost 50% greater than high-income countries (Figure 3). The inequitable distribution of surgical conditions’ economic impact is further magnified when examined by region, as central and southern sub-Saharan Africa are estimated to lose up to 2·5% of GDP in 2030 (Figure 4). While injury is the main driver of these losses, maternal and neonatal disorders account on average for 10% of central sub-Saharan Africa’s foregone GDP; in comparison, maternal and neonatal disorders contribute to only 0·05% of Western Europe’s projected economic losses, a more than 200 fold difference.

While the VLO approach incorporates only market losses, the value of lost welfare approach (VLW) accounts for nonmarket losses, including the intrinsic value of health; moreover, with respect to mortality, it captures losses over the long-run (Figure 1). With the VLW approach, the death and disability incurred in 2010 for the 175 countries we examined are equivalent to roughly 17% of their aggregate 2010 GDP, or $14.5 trillion dollars (2010 USD, PPP). As an equivalent share of GDP, high-income countries are affected most, with up to a 19% loss (Figure 5). These results, however, are driven largely by the crude, or non-age-adjusted, neoplasm-related mortality rates, which are currently more than twice as high in developed countries due in part to their older demographic profiles.²⁷ When neoplasm is excluded, we find a similar pattern as with the VLO approach, in which low-income countries bear the greatest share of the burden (Figure 5). We would re-emphasize here that the VLW and VLO estimates should not be compared as they are attempting to measure two conceptually distinct values: the VLW estimates include nonmarket welfare losses and in the context of mortality represent long-run losses and are therefore many times larger than the VLO estimates, which account only for market losses due to mortality (not morbidity) during the time period included in this study.

Not surprisingly given incidence rates, neoplasm and injury account for greater than 95% of the total economic losses attributable to surgical disease in both approaches. However, maternal, digestive, and neonatal disorders make up a significantly greater proportion of losses in low- and middle-income countries—up to 26% of VLW in low-income countries. These estimates reflect in part the lack of access to basic obstetric and surgical care in these countries, as well as the higher burden of non-communicable disease in high-income countries. The stark contrasts in maternal and neonatal mortality rates between the developed and developing world, recently demonstrated by the Global Burden of Disease 2013 study, suggests that much of the burden we identified is avertable.^28,29 Although one cannot estimate with certainty the potential economic gains to be realized with scaling up access to surgical services, the relative absence of maternal and neonatal burden in high-income countries suggests there could be substantial economic benefit to low- and middle-income countries in investing in surgical care. Finally, while neoplasm currently results in the greatest losses in the VLW approach for high-income countries, age-standardized rates of mortality are converging between the developed and developing world;²⁷ as populations in low-and middle-income countries age,³⁰ these countries will face a similar if not greater economic impact than high-income countries currently, especially if surgical services are not available as these remain the curative backbone of a large portion of cancer care.

These estimates, while concerning from the perspective of economic development, tell only a part of the story. Bickler et. al. assessed the impact of scaling up basic surgical services in low- and middle-income countries and concluded that up to 1·8 million deaths could be averted annually with access to surgery.¹⁷ From a purely humanitarian perspective, this degree of unnecessary mortality is indicative of striking inequality and the human toll of surgical conditions, falling most heavily on the poor and marginalized. However, policy-makers necessarily require additional information to assist in decision-making, and therefore economic impact estimates such as these can indicate the degree of urgency of different policy problems, and their broader impacts on development.¹¹ While we recognize that decisions regarding resource allocation cannot be made on the basis of economic burden studies alone, we would argue that our findings regarding the magnitude and inequitable distribution of the economic costs of surgical disease complement the existing global surgery literature on cost-effectiveness³¹ and avertable burden.¹⁷ Ultimately, if one is concerned with saving lives and promoting economic growth, surgical conditions cannot be ignored.

Our results are not directly comparable to estimates produced by other studies as the assumptions applied across economic burden studies differ greatly. However, others have performed studies with similar approaches and scope.^19,32,33 Most recently, Bloom used the WHO EPIC model to assess non-communicable diseases (NCDs) (cardiovascular disease, neoplasm, chronic respiratory disease, mental illness, and diabetes), and estimated that they will result in $47 trillion (2010 USD) in lost output from 2011–2030. Notably, these estimates did not adjust for purchasing power parity (PPP). When our VLO results are expressed in USD without PPP during 2011–2030, we estimate $16·0 trillion in GDP losses, well in line with Bloom’s estimates given that the attributable burden of disease for the conditions we studied is less than the NCD study, especially since we only account for the surgical proportion of each disease. Bloom also applied a model similar to our VLW approach to NCDs and found $22·8 trillion (2010 USD) in economic welfare losses in 2010; without adjusting for PPP and using baseline VSL assumptions, the VLW for surgical conditions is $11·4 trillion (2010 USD). While the assumptions of the NCD study and our study differ, the similarity of the results is reassuring.

Our study is notable for several reasons. To our knowledge, it is the first to provide an estimate of the macroeconomic impact of surgical diseases at this scale through two distinct economic lenses. Our results suggest not only that surgical diseases will exact a large toll on the global economy, but that the costs are inequitably distributed with markedly greater impact on poor countries. Finally, the decision to include only countries with available data makes our aggregate estimates conservative.

There are important limitations to the conclusions that can be drawn from economic impact studies, however, and our study is no exception. While such studies can provide an assessment of the magnitude of a problem, they cannot be used in isolation for priority-setting, which requires information regarding the cost and effectiveness of interventions.¹¹ With that in mind, a robust literature base suggests that surgical interventions can be extremely cost-effective in low- and middle-income countries.^31,34

There are also important technical limitations to this study. As with all models, our estimates are limited by data availability. Much of the data we used from low- and middle-income countries is limited and the estimate of a model, as opposed to being measured directly. Data availability has also limited the ability to provide estimates in many countries, especially with the VLO approach, and high-income countries are necessarily over-represented given the relative degree of data availability. An important limitation with any economic model is that it cannot completely account for future technological advances, and the VLO approach in this study follows the EPIC model’s crude assumption of assigning a 1% rate of growth to productivity. We also recognize the significant role that uncertainty plays, especially with respect to supporting data and the inherent inexact, speculative nature of projection-based studies. When we incorporate the uncertainty intervals provided by IHME for their burden of disease estimates in addition to the confidence intervals from Shrime’s survey data, the resulting intervals for both approaches are not insignificant (VLO:$12·1–$33.2 trillion, VLW: $8·7–$22·4 trillion) These intervals in large part reflect the underlying uncertainty of IHME burden estimates, which incorporate a significant amount of modeling in addition to primary data.

The VLW approach has a number of limitations. First, VSL studies are based on willingness to pay for small changes in mortality risk, and the linear assumption that is consequently made to determine the VSL is likely an oversimplification.³⁵ There are further limitations to valuing morbidity,³⁶ and the small number of formal VSL studies in low- and middle-income countries for either mortality or morbidity makes these estimates best-guesses. We account for the latter by applying a wide range of assumptions regarding how VSL varies with income.²⁴ We would emphasize the effect of baseline assumptions regarding the VSL; while varying the relationship of income with VSL only moderately affected our results, varying the reference VSL had a significant impact on our results, with our baseline estimate falling from $14·5 to $8·2 trillion. We also emphasize that our estimates can be compared directly to GDP in the case of the VLO approach, but only indirectly in the case of the VLW estimates, which incorporate nonmarket losses. Unlike the VLO estimates, the VLW estimates should not be interpreted as actual GDP lost.

Finally, we have only considered five disease groups, and therefore our estimates may underestimate the total economic impact of surgical disease.

CONCLUSION

Our results suggest the macroeconomic impact of surgical disease is enormous and inequitably distributed, with poor countries often facing the largest burden. The notion that surgery is a necessary component of a fully-functioning healthcare system is rarely in dispute, and yet, surgery’s place within the larger global health agenda is ill-defined at best. When considered with the evidence of cost-effectiveness of surgical interventions in low- and middle-income countries,³¹ our results suggest that investing in surgery not only has the potential to save millions of lives, but could also contribute to improved overall economic welfare and development.

Research in Context.

Systematic Review

Prior to initiating the study, we searched Medline and Google Scholar and failed to identify any studies that attempted to estimate the global macroeconomic burden of surgical disease. For this reason, a systematic review was not performed. We would note that prior efforts have been made to identify the global surgical burden of disease,^1,2,17 but these studies were specific to morbidity and mortality. As noted by Chisholm in his review of economic burden methodology, there are countless studies that estimate the economic burden of diseases in the literature.¹¹ We could identify no studies, however, that address surgical diseases at the global level. Although not specific to surgery, others have attempted to identify the global macroeconomic burden of cancer and non-communicable diseases using similar methodology and are discussed further in the discussion.^19,21

Interpretation

When market losses secondary to surgical diseases are estimated during 2015–2030, we estimate up to 1·25% of GDP, or $20·7 trillion dollars, will be lost due to surgical disease. If welfare losses are incorporated, surgical diseases are estimated to result in $14·5 trillion dollars in 2010 alone. These losses are inequitably distributed, with low-and-middle income countries facing greater relative costs than high-income countries. While these findings cannot be used in isolation to inform decisions regarding resource allocation, there is a substantial and growing literature that supports the cost-effectiveness of surgical interventions³¹ and makes clear that much of the current surgical burden of disease is avertable.¹⁷ Therefore, when the existing evidence is considered with our results, a strong case is made for elevating surgery as a global health priority.