metadata: authors: 0: author: Wagstaff,Adam
count: World
docna: 0: docna: Catastrophic Medical Expenditures :
            Reflections on Three Issues
docty: Policy Research Working Paper
subtopic: Health Care Services Industry,Inequality,Health Economics & Finance,Financial Sector Policy
teratopic: Industry,Poverty Reduction,Health, Nutrition and Population
abstracts: cdata!: There is a large empirical literature
            analyzing 'catastrophic' medical expenses. The
            'basic' approach defines expenses as catastrophic
            if they exceed a prespecified percentage of total
            consumption or income; the approach, in effect, tells us
            whether expenses cause a large percentage reduction in
            living standards. An alternative 'ability-to-pay
            approach' defines expenses as catastrophic if they
            exceed a prespecified percentage of consumption or income
            less actual expenses on nonmedical necessities or an
            allowance for them. This paper argues that this approach
            does not, contrary to what is sometimes claimed, tell us
            whether expenses are large enough to undermine a
            household's ability to purchase nonmedical necessities.
            The paper also compares the income- and consumption-based
            variants of the 'basic' approach, showing that if
            the individual is a borrower after a health shock, the
            income-based ratio will exceed the consumption-based ratio,
            while the opposite is true when the individual continues to
            be a saver after a health shock. The paper also explores the
            relationship between the income- and consumption-based
            ratios and the more theoretically correct ratio proposed by
            Flores et al. It shows that if the individual is a borrower
            after a health shock, both the consumption- and income-based
            ratios will exceed the Flores et al. ratio, with the
            income-based ratio overestimating it by more, while in the
            case when the individual continues to be a saver after a
            health shock, the income-based ratio will overestimate
            Flores et al.'s ratio by less and may not overestimate
            it at all. Last, the paper proposes a lifetime money metric
            utility approach that defines medical expenses as
            catastrophic in terms of their lifetime (rather than
            single-period) consequences. It shows that under certain
            assumptions, the money-metric utility approach and the
            Flores et al. approaches are identical, and both are
            operationalizable without data on how households finance
            their medical expenses.
repnme: repnme: Catastrophic Medical Expenditures :
            Reflections on Three Issues
display_title: Catastrophic Medical Expenditures :
            Reflections on Three Issues
listing_relative_url: /research/2018/11/30639311/catastrophic-medical-expenditures-reflections-three-issues
topicv3: Poverty m1326687 695,Financial Inclusion m1327456 363,Health m1504661 3480,Out of Pocket Payments(OPP) m1504817 -1,Catastrophic Expenditures m1504842 3571
publishtoextweb_dt: 2018-11-26T00:00:00Z
historic_topic: Industry,Poverty Reduction,Health, Nutrition and Population
no_of_pages: 22
model_extractions: WPS8651 Policy Research Working Paper 8651 Catastrophic Medical Expenditures Reflections on Three Issues _Adam Wagstaff_ Development Economics Development Research Group November 2018
Policy Research Working Paper 8651

# **Abstract**

There is a large empirical literature analyzing ‘catastrophic’ medical expenses. The ‘basic’ approach defines expenses as catastrophic if they exceed a prespecified percentage of total consumption or income; the approach, in effect, tells us whether expenses cause a large percentage reduction in living standards. An alternative ‘ability-to-pay approach’ defines expenses as catastrophic if they exceed a prespecified percentage of consumption or income less actual expenses on nonmedical necessities or an allowance for them. This paper argues that this approach does not, contrary to what is sometimes claimed, tell us whether expenses are large enough to undermine a household’s ability to purchase nonmedical necessities. The paper also compares the income- and consumption-based variants of the ‘basic’ approach, showing that if the individual is a borrower after a health shock, the income-based ratio will exceed the consumption-based ratio, while the opposite is true when the individual continues to be a saver after a health shock. The paper also explores the relationship between the income- and consumption-based ratios and the more theoretically correct ratio proposed by Flores et al. It shows that if the individual is a borrower after a health shock, both the consumption- and income-based ratios will exceed the Flores et al. ratio, with the income-based ratio overestimating it by more, while in the case when the individual continues to be a saver after a health shock, the income-based ratio will overestimate Flores et al.’s ratio by less and may not overestimate it at all. Last, the paper proposes a lifetime money metric utility approach that defines medical expenses as catastrophic in terms of their lifetime (rather than single-period) consequences. It shows that under certain assumptions, the money-metric utility approach and the Flores et al. approaches are identical, and both are operationalizable without data on how households finance their medical expenses.

This paper is a product of the Development Research Group, Development Economics. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/research. The author may be contacted at awagstaff@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# Catastrophic Medical Expenditures: Reflections on Three Issues

### By

## Adam Wagstaff

Development Research Group, World Bank, Washington DC, USA Key words: catastrophic medical expenditures; impoverishing medical spending; impoverishment; out-of-pocket medical expenditures; financial protection; financial hardship Corresponding author: Adam Wagstaff, Development Research Group, World Bank, Washington DC 20433, USA, <u>awagstaff@worldbank.org</u> JEL classification: I10, I14, I15

### Acknowledgements

My thanks to Eddy van Doorslaer and Patrick Eozenou for helpful comments on a draft on which this paper is based. The findings, interpretations and conclusions expressed in this paper are entirely mine, and do not necessarily represent the views of the World Bank, its Executive Directors, or the governments of the countries they represent.
An extensive applied literature exists, dating back to the 1980s (see e.g. Berki 1986; Wyszewianski 1986), measuring ‘catastrophic’ out-of-pocket medical expenses — expenses that exceed a specific that it has become one ofthe UN Sustainable Development Goals (indicator 3.8.2).

paper explores three of them: whether to relate out-of-pocket expenses to income (or consumption) or to a transformation of income (or consumption) that might better proxy a and how to capture the lifetime consequences of the various ways offinancing (or<sup>‘coping’</sup> with) expenditures in studies of poverty and income distribution (Blinder 1985; Citro and Michael 1995; Deaton and Zaidi 2002). medical expenditures (or at least some elements thereof) that may be discretionary (plastic surgery for aesthetic reasons is the commonest example), and while this view contrasts with the (cf. e.g. Grossman 1972), the consensus seems to be that, on balance, it makes sense when <u>As Blinder</u> (1985) put it: “...dollars [spent on medical care] do not buy happiness; they just maintain human capital”. Or as the US National Academy of Sciences (NAS) Panel on Poverty and Family Assistance put it: “A state” (Citro and Michael 1995, p236). Or as Deaton and Zaidi (2002) put it when discussing whether a (p32).

nondiscretionary underpins the approach of the U.S. Census Bureau which subtracts them (and health insurance premiums) from income in its supplemental poverty measure (SPM)(Fox 2017). Interestingly, despite the recommendations of Deaton and Zaidi (2002), in practice 95% of World Bank poverty ( ) yielded 178 documents of which 76 were actual aggregate. Of the rest, 5 used income (and did not subtract medical expenses), 24 explicitly included medical
When measuring catastrophic medical expenses, it has been suggested (Wagstaff and van Doorslaer 2003) that one might relate out-of-pocket medical expenses to income (or consumption) or to a transformation of income (or consumption) that might be thought to better proxy a household’s ‘ability-to-pay’ (ATP). The ATP approach, it was suggested, might be operationalized either by expenses. In practice, as reported in Wagstaff et al. (2018a), articles published in health and medical journals have tended to follow the ATP approach, often citing Xu et al. (2003) who denote consumption before and after (or without and with) the health shock necessitating out-of-pocket medical expenses, M@. (Or we can think of C as nonmedical consumption.) Then we have the ‘basic’ catastrophic paste ~ ~~=~~ = ~~PreT Crosr~~ PRE post +M BASIC as the (negative of the) proportionate reduction in (nonmedical) consumption associated with the catastrophic out-of-pocket medical expenses. This is in line with Berki’s (1986) rationale for his
aw ~~LS Cros=~~ YN pre~N pre —N As suggested by Wagstaff and van Doorslaer (2003), Ncould be actual food expenditure ora flatrate allowance for food spending. Xu et al. (2003) adopt the latter approach, setting Mequal to an argue, as pointed out by Wagstaff and van Doorslaer (2003), that Wshould probably capture more that are also likely to be of concern to a policy maker. This leads Wagstaff and Eozenou (2014) to nonmedical needs. Thomson et al. (2016) build on this suggestion empirically.

The ATP-based ratio allows us to classify people into three groups (cf. Wagstaff and Eozenou 2014): a) nonmedical needs: M/(C -N)<0; b) 0<M/(C -N)<1; and c) spending but cannot ‘after’ medical spending: M/(C _-N)>1. If Nis set equal to the poverty line per Wagstaff and Eozenou’s suggestion, individuals in group (a) are pushed further into poverty by out-of-pocket expenses, while those in group (c) are pushed pocket expenses (i.e. they are ‘impoverished’ by out-of-pocket expenses). All of those in group (c) and some in group (b) incur catastrophic expenses in the ATP approach.

expenditure required to meet nonmedical needs (or the poverty line) is assumed to be $1.90-a-day
~~M/(C_ -N)~~ Individuals 1 and2 illustrate case (a). In such cases, CATA Individuals 3, 4 and 5 illustrate case (b). Individuals 3 and 4 are not classified as having incurred Individuals 7 and8 illustrate case (c). Both suffer from health shocks that results in them going tells us whether impoverishment occurs (case (c)), whether an already-poor individual is pushed still further into poverty (case (a)), or whether, despite incurring medical expenses, the individual
manages to stay above the poverty line (case (b)). But ~~within each of these cases,~~ the ATP-based Doorslaer (2003) developed their arguments using income. But then in the empirical illustration, ~~The case of zero borrowing (or saving)~~ Assume the individual derives utility from nonmedical consumption in just two periods (the current period (period 0) and the future (period 1)), but needs to be in good health to be able to (we relax this assumption in a moment), and chooses to consume the same amount in both periods, health shock. (The results that follow can be generalized to the case where point ais off the 45 spending.) The individual starts on indifference curve J, 0 0 5 equal to the distance OB. If we observe income (OA) and medical spending (BA) in our data, we can 0 INC = ~~—©~~ INC >= ~~—_~~ If we do not observe income, but do observe nonmedical consumption (OC), we can compute the consumption-based catastrophic payment ratio. We add medical spending (BA) to nonmedical consumption (OB) to get ‘consumption gross of medical expenditures’ (OA), which is our proxy for 0
coNS = ~~—_~~ inc = CATAcons Jo ~~=~~ consumption (including medical expenditures) has increased, as a result of the health shock, from OC to OD. If we observe medical spending (BA) and income (OA), we can compute the incomeINC = ~~—_~~ If we observe nonmedical consumption (OC) and medical spending (BA=CD), we can compute the cD cons ~~~~ >~~ CONS (- ~~—)~~ < CATAine (- ~~=),~~ BA
<!-- Start of picture text --> 1<br><!-- End of picture text --> CONS 0 0 CONS 04 ~~M2 90-S~~ <u>4 By</u> 0 0 CONS < CATA ~~—————— <—~~ = S<B INC 0—S+By 0 M cons < CATA,yc for sure when S < 0 (e.g. the income endowment is point ein Figure 2) or when S = 0 (i.e. the income endowment is point a). We also have CATAcgons < iwc When0 < S < By(i.e. the income endowment lies between points aand d), and we have cons = CATA;ycwhen S = By > 0 (i.e. the income endowment is point d). We only have cons > CATA;yc when S > By > 0 (i.e. the income endowment lies to the southeast of<sup>point</sup> d, e.g. point g). Thus, when the individual is a borrower after a health shock, the income-based ratio
<!-- Start of picture text --> we are trying to learn whether an individual’s (current) (nonmedical) consumption is substantially<br><!-- End of picture text --> interested in computing the percentage reduction in (current) (nonmedical) consumption due to the out-of-pocket medical expenses necessitated by the health shock (cf. Berki 1986). As pointed out in Wagstaff and van Doorslaer (Wagstaff and van Doorslaer 2003), the <!-- Start of picture text --> In the light of this, Flores, Krishnakumar, O'Donnell and van Doorslaer (2008) propose a coping-<br><!-- End of picture text --> <!-- Start of picture text --> FKOV — 0 4 MO? _ By<br><!-- End of picture text --> <!-- Start of picture text --> FKOV = —_<br><!-- End of picture text --> survey (conducted in 2004) did not contain the necessary breakdown. So, it is of interest to know how the theoretically incorrect (but readily computed) measures - the income- and consumptionbased measures - relate to the (more) theoretically correct (but more data-demanding) coping<!-- Start of picture text --> CONS (- —) > CATArxKov (- —), CA<br>FKOV<br>PROV"_ 04M°-By°=Bu _— 9S— Bu<br><!-- End of picture text -->
<!-- Start of picture text --> CONS < CATA —_——_—— 0 < —_———_—— 0 _ BM <0.<br>FKOV 04 mo 04+ M°—By M<br>FKOV INC<br>° M°-B M M M° M S<br>The above inequality cannot hold when S < 0, so in this case we have CATAggoy < CATAinc<br>reversed when S = 0, which is labeled zone 1/2. In the case where 0 < S < By (zone 2), we have<br>m/S > 1, and hence in this case too we have CATArgoy < CATAnc<br>S = By > 0, we can also conclude that CATAggoy < CATAnc o><br>° (zone 2/3). When S > By > 0, there are two possible outcomes: (a) the case where By ><br>9 9<br>M 9 >S y? FKOV < CAT Ajyc (zone 3);<br>and (b) the case where By <M°® ° um °<S Y°<br>FKov > CATA;yc (zone 4). This latter case is, in fact, impossible if, as is assumed in Figure 2,<br><!-- End of picture text --> 0 M mM ° = =Jjd/cdjd/cd **=** hg/ihg/ig > o s<0 S=0 0<S<By /S>1>M S = By > O;hence B /S=1 S > By > 0;and1>B /S> S>By>0;and B /S<M rrov < CATAcons < CATAine rrov < CATAcons < CATAine rkov < CATAcons < CATAinc rrov < CATAcons = CATAine prov < CATAiwe < CATAcons inc < CATArKov < CATAcons
of the exercise is to calculate the percentage reduction in (current) consumption due to the out-ofpocket medical expenses necessitated by the health shock, the (more) theoretically correct catastrophic expenditure measure is that proposed by Flores et al. (2008), equal to the reduction in The coping-adjusted catastrophic payment measure proposed by Flores et al. (2008) is superior to expenses (and coping strategies) for ~~current~~ consumption; they ignore the implications for future medical expenditures necessitated by the health shock (cf. Wagstaff 2010). This last section asks A natural ratio to get at the lifetime welfare reduction (in percentage terms) of out-of-pocket utility ~~before~~ it, i.e. the equivalent variation (EV).

money metric utility (LMMU) reduction measure IH/OH and the Flores et al. measure CA/OA are Figure 1, i.e. consumption is equalized across periods, before and after (or with and without) the down to the level of utility after the health shock, i.e. the compensating variation (CV).
<!-- Start of picture text --> PRE = CPRE = Cpre<br>OH<br>—= Cpe“PRET + 7 4.PRE =~ “PRECopp T2 tt 4.<br>0 oltr<br>LMMU = — = ——~—— = 477<br>PRET 2+r PRE<br>+7<br><!-- End of picture text --> <!-- Start of picture text --> The measure of Flores et al. (hereafter FKOV) is equal to CA/OA. We know the denominator is C°<br>2+r<br>o1r=C<br>— “POST 74>,<br><!-- End of picture text --> <!-- Start of picture text --> But we know OH — OJ = M°<br>0 2+r 2+r 2+r<br>= Core Lor Crosr Tor 14r (Core — Cposr),<br>1+r<br>CA = (Core(Corp —— CCposr) = M° ——247<br>FKOV= —=- < 2PRE(C CPost) ) _ olt2+ r<br>PRE PRE<br><!-- End of picture text --> only a fraction of medical expenses to current consumption (the first formulation in the expression for LMMU above) or as relating the entire amount of medical expenses to the present value of consumption (the second formulation).

OH ~~PRE~~ | ~~_PRE PRE~~ = Corp + ~~——~~ + ~~—— SS~~ t+ + PRE 1+r (1497/2 (1+,r)"-1
<!-- Start of picture text --> OH =CPre E + =Gay t taoGane ) Gan|= ,T)COre<br>T<br>1 — (———<br>t(r,T) = (7 + 7)<br>1 TTF<br>LMMU = — = —M°® c(r,T)<br>PRE<br>OI = t(r,T)Cposr<br>But we know OH — OI = M°<br>° = t(r,T)Cprg — 107, T)Cposr = T(r, T)(Cpre — Cposr).<br>FKOV = _ _ ¢ Corp PRE —CPOST) _ ° <(r,T(r,T)<br>PRE PRE<br>consumption being equalized over time, consumption in period ¢+1 is a constant fraction or<br>PRE1 =— &Uppeac PRE2 _= &” 7,2 pre0<br>we have (see Annex):<br>LMMU = — = M° oo(r,T) _ pov = — = SexeCBee — CpPost) _ ° otg(r,T)<br>POST PRE POST<br><!-- End of picture text -->
<!-- Start of picture text --> T<br>1 — (———<br>g(r,T) = (ce)<br>+r<br><!-- End of picture text --> <!-- Start of picture text --> So, under certain assumptions, the Flores et al. approach gives the same answer as the (lifetime-<br>consistent) lifetime money metric method. The challenge with the Flores et al. method (and the<br>LMMU method) is that with the typical cross-section household survey, we do not have the<br>PRE —<br>0<br>PRE == —— TG. T) + + CCposr<br>LMMU = FKOV = —————° <t(r,T) = ° t(r,T)<br>PRE t(r,T) + Cposr<br>So, for example, if -=10%, 7-1=25, C =90 and MM =10, then the regular consumption-based<br>catastrophic spending ratio is 10%, while the LMMU and FKOV measures (under the assumptions<br>we have made) are only 1.1%. In empirical work, one would of course have to make an assumption<br>loans (perhaps specifically for medical expenses), one may also have to make an assumption about<br><!-- End of picture text --> <!-- Start of picture text --> consistent with studies that find that people borrow to finance medical expenses (Demirguc-Kunt<br>and Klapper 2012) and that nonhealth consumption falls after a health shock (see e.g. Gertler and<br>Gruber 2002; Jack and Suri 2014). The evidence is consistent, in other words, with one implication<br>consumption over time, or at least plan their consumption such that consumption in period ¢+1 isa<br><!-- End of picture text -->
over time (see e.g. Browning and Crossley 2001). And even the assumption that consumption in period ¢+1 is a constant fraction or multiple of consumption in period ¢is unlikely to be consistent and nonmedical consumption. (The “will likely” is because the assumptions are ~~sufficient~~ to give the results above.) With respect to the first issue considered (whether to relate out-of-pocket expenses to income (or consumption) or to ‘ability-to-pay’ (ATP)), the paper has argued that the ‘basic’ approach to
should express out-of-pocket expenses relative to consumption (or income) and not relative to explicitly on the concept of impoverishment (Wagstaff and van Doorslaer 2003; van Doorslaer et al. 2006; Wagstaff et al. 2018b).

With respect to the second issue (whether to relate out-of-pocket expenses to consumption or income), the paper has shown that the answer depends on whether, after the health shock of the exercise is to calculate the percentage reduction in (current) consumption due to the out-of(more) theoretically correct catastrophic expenditure measure proposed by Flores et al. (2008), project (Demirguc-Kunt et al. 2015) suggest that in the world as a whole 12% of households
Finally, with regard to the third issue (how to capture the lifetime consequences of alternative ways of coping with out-of-pocket expenses), the paper proposeda lifetime money metric utility (LMMU) The highest rates are in Uganda (39%), Kenya (32%) and Malawi (31%). Borrowing rates in high-income
<!-- Start of picture text --> period ¢+1 is a constant fraction or multiple of consumption in period & Thus, we assume C3pp =<br>PRE PRE = PRE<br>2 T-1<br>OH= C®,,PRE |1 +——~-+ ——— + --- + $—_—] = T)Co<br>+ (1 4 r) + (1 +4 r)2 + + (1 +4 ar er, ) PRE<br><!-- End of picture text -->

<!-- Start of picture text --> T<br>1-( {(—-—<br>1 TTF<br><!-- End of picture text --> <!-- Start of picture text --> LMM = —= Mot)M°® g(r,T<br>POST<br><!-- End of picture text --> Ol = 9(1,T)Cposr But we know OH — OJ = M° ° = o(r,T)Crre — 9(1,T)Cposr = G(r, T)(CPre - Chosr): 0 CA = Ceer — CRosr = ~~——X~~ PRE ~ “POST ~ ~~Oy~~ <u>T)</u> FKOV<sup>=</sup> ~~_~~<sup>_</sup><sup>~~(~~</sup> ~~CPre~~<sup>~~PRE~~</sup> ~~— Cp~~ <u>Post)</u> ~~° g(r,T~~ : _ ~~ot )~~ PRE POST which is again the same as the lifetime money metric measure (LMM).