Supplemental health insurance and equality of access in Belgium

Transcription

1 Supplemental health nsurance and equalty of access n Belgum by Erk SCHOKKAERT Tom VAN OURTI Dane DE GRAEVE Ann LECLUYSE Carne VAN DE VOORDE Publc Economcs Center for Economc Studes Dscussons Paper Seres (DPS) August 2007

2 SUPPLEMENTAL HEALTH INSURANCE AND EQUALITY OF ACCESS IN BELGIUM Erk Schokkaert a,*,tom VanOurt b,c,dana De Graeve d,annlecluyse d and Carne Van de Voorde e a Department ofeconomcs,kuleuven,belgum and CORE,Unverstécatholque de Louvan,Belgum b ErasmusSchoolofEconomcs,ErasmusUnverstyRotterdam,the Netherlands c TnbergenInsttute,Rotterdam,The Netherlands d FacultyofAppled Economcs,UnverstyofAntwerp,Belgum e BelganHealth Care Knowledge Centre,Brussels,Belgum August 2007 * Correspondence to: Erk Schokkaert, Department of Economcs, Naamsestraat 69, B 3000 Leuven, Belgum. Emal: erk.schokkaert@econ.kuleuven.be. Tel.: Fax: Acknowledgements: Ths paper s partaly a spn-off of De Graeve D., Lecluyse A., Schokkaert E., Van Ourt T., Van de Voorde C. Egen betalngen n de Belgsche gezondhedszorg. De mpact van supplementen. Equty and Patent Behavour (EPB). Brussel: Federaal Kennscentrum voor de gezondhedszorg (KCE); KCE reports 50 A (D/2006/10.273/68). We are grateful to Helke Buddelmeyer for hs helpful comments. Tom Van Ourt s a Postdoctoral Felow of the Netherlands Organzaton for Scentfc Research Innovatonal Research Incentves Scheme Ven. 1

3 SUPPLEMENTAL HEALTH INSURANCE AND EQUALITY OF ACCESS IN BELGIUM Summary It has been suggested that the unequal coverage of dfferent soco-economc groups by supplemental nsurance could be a partal explanaton for the nequalty n access to health care n many countres. We analyse the stuaton n Belgum, a country wth a very broad coverage n compulsory socal health nsurance and where supplemental nsurance manly refers to extra-bllng n hosptals. We fnd that ths nsttutonal background s crucal for the explanaton of the effects of supplemental nsurance. We fnd no evdence of adverse selecton n the coverage of supplemental health nsurance, but strong effects of soco-economc background. A count model for hosptal care shows that supplemental nsurance has no sgnfcant effect on the number of spells, but a negatve effect on the number of nghts. Ths s n lne wth patterns of socoeconomc stratfcaton that have been well documented for Belgum. It s also n lne wth the regulaton on extra-bllng protectng patents n common rooms. For ambulatory care, we fnd a postve effect of supplemental nsurance on vsts to a dentst and on number of spells at a day centre but no effect on vsts to a GP, on drugs consumpton and on vsts to a specalst. Keywords:supplemental nsurance, adverse selecton, moral hazard, hosptal spells, equalty of access, health care use. 2

4 Introducton In recent decades, many European countres have experenced a growng pressure on the fnancal resources of ther publc health care systems and a parallel ncrease n the mportance of dfferent forms of voluntary health nsurance (Mossalos and Thomson, 2002; OECD, 2004). There are worres that ths development threatens the deal of equalty of access n these countres, as voluntary health nsurance seems manly concentrated among the better-off groups n socety. Related to ths s the concern about the pro-rch nequty n the probablty of seeng a specalst found n many European countres (van Doorslaer et al., 2004) and the queston of whether ths phenomenon can be explaned by the unequal dstrbuton of supplemental nsurance coverage (Van Doorslaer et al., 2002; Buchmueller et al., 2004; Rodrguez and Stoyonova, 2004; Van Doorslaer and Massera, 2004; Jones et al., 2006). As emphaszed by Jones et al. (2006), a good dagnoss of the stuaton requres that one s able to dstngush carefully between the dfferent factors nfluencng the lnk between supplemental nsurance and health care consumpton. If there s adverse selecton,.e. f those wth hgher health care rsks are more lkely to take out supplemental nsurance, t becomes crucal to dsentangle ths selecton effect from the nsurance effect. 1 More specfcally, hgher health care consumpton of those wth supplemental nsurance may be due ether to the fact that they are less healthy, or to the fact that they have supplemental nsurance, or to both. From the pont of vew of equty, dstngushng 1 In addton to the tradtonal moral hazard effect, Jones et al. (2006) menton a seres of other nsurance effects: rsk reducton, ncome transfer and access. Emprcally, t s mpossble to dstngush between all these and we wll use the terms moral hazard and nsurance effect nterchangeably. 3

5 these effects s essental. However, t s well known that ther dentfcaton rases dffcult methodologcal ssues, especally when only cross-secton data are avalable (Holly et al., 1998; Vera-Hernandez, 1999; Schellhorn, 2001; Buchmueller et al., 2004; Gardol et al., 2005; Jones et al., 2006). Whle prevous emprcal work gves much evdence for the exstence of a moral hazard (or utlzaton) effect, the results wth respect to adverse selecton are mxed. The strongest effects seem to be found for the free choce of deductbles n Swtzerland (Schellhorn, 2001; Gardol et al., 2005). Ths s not very surprsng, gven the nsttutonal settng n Swtzerland wth a strong tradton of prvate health nsurance. The latter pont suggests an mportant nsght,.e. that the nature of demand for prvate health nsurance tself depends on the nsttutonal context n whch that nsurance operates (Harmon and Nolan, 2001, p. 135). It s ndeed obvous that both the degree of adverse selecton n the voluntary nsurance system and the (voluntary) nsurance effect on health care consumpton wll crucally depend on the degree of populaton, servce and cost coverage n the publc (compulsory) system and thus the type of voluntary nsurance. The wde varety of possble arrangements has been descrbed n the nternatonal comparson reports (Mossalos and Thomson, 2002; OECD, 2004), but untl now there have not been many structured attempts to formulate and test specfc hypotheses whch are lnked to these nsttutonal dfferences. In fact, a careful analyss of the nsttutonal settng may n some cases lead to emprcal predctons of an nsurance effect that does not n the frst place nduce ncreased consumpton. 4

6 In ths paper, we analyse the take-up and the consumpton effects of voluntary health nsurance n Belgum. Belgum has a socal nsurance system wth a very broad coverage. The mportance of voluntary nsurance s growng, manly n the form of supplemental hosptal nsurance coverng addtonal costs of sngle rooms, co-payments and extra-bllng n the hosptal sector. It also covers some dentstry and the copayments of ambulatory pre- and post-hosptal care. It s very uncommon n Belgum that a supplemental polcy covers all ambulatory co-payments. We wll descrbe the Belgan system n more detal n the next secton and we wll argue that t leads to specfc predctons on the effect of supplemental nsurance. It s worth emphaszng that our data taken from the Belgan Health Intervew Survey for 2001 have two major advantages. Frst, they contan very rch nformaton on the health stuaton of the ndvduals, whch s useful n dstngushng the adverse selecton effect from the nsurance effect. Second, npatent care s recorded as the number of spells and the number of nghts per spell durng the last year. To the best of our knowledge (Pohlmeer and Ulrch, 1995; Deb and Trved, 1997 & 2002; Gerdtham, 1997; Gurmu, 1997; Deb and Holmes, 2000; Schellhorn et al., 2000; Gerdtham and Trved, 2001; Jménez-Martín et al., 2002; Rphahn et al., 2003; van Doorslaer et al., 2004; Van Ourt, 2004; Wnkelmann, 2004; Bago d Uva, 2005 & 2006), the lterature on the determnants of the number of contacts wth the medcal sector has only focused on modellng the total number of contacts/nghts wthout dstngushng between the spells. The most popular models are two-part and latent class count data models, or combnatons of both. The former models assume a sngle spell, whereas the latent class models only dstngush between so-called hgh - and low -users. A notable 5

7 excepton s Santos Slva and Wndmejer (2001), who propose modellng strateges to account for multple spells f only the total number of contacts/nghts s known. However, we observe the number of spells and the number of nghts per spell drectly, whch allows us to model the ndvdual decson process more explctly. In the followng secton we descrbe our data. Next, we present our results for the demand of supplemental nsurance and the effects of supplemental nsurance coverage on health care use. We dstngush between npatent care (number of spells and number of nghts per spell) and outpatent care and argue that the results are well n lne wth what could be expected wthn the Belgan nsttutonal context. We also dscuss the ssue of endogenety of supplemental nsurance. The fnal secton concludes. Supplemental health nsurance n Belgum Belgum has a system of compulsory health nsurance, coverng the entre populaton (wth some restrctons for the self-employed, to whch we wll return). 2 Health nsurance s organzed through prvate, non-proft sckness funds. Membershp of a sckness fund s compulsory, but the choce of sckness fund s free. By law, the compulsory health nsurance market s closed to new entrants. The servce and cost coverage wthn the compulsory system and the socal contrbuton rates leved are dentcal for all funds. 2 More detaled nformaton on the Belgan health care system and on recent reforms can be found n Schokkaert and Van de Voorde (2005). 6

8 Compulsory health nsurance s combned wth ndependent medcal practce. Payment s manly fee-for-servce and patents have a large degree of freedom n ther choce of provder. Hosptal care s provded ether by prvate non-proft or by publc hosptals. The system of hosptal fnancng dstngushes between medcal and non-medcal servces. The latter refer to the general hosptal costs and to accommodaton expenses (also ncludng costs of equpment and nursng staff). The medcal servces are fully ntegrated nto the system of health nsurance and are covered by the sckness funds. Here also, remuneraton s manly fee-for-servce. Perhaps due to the domnance of feefor-servce (but certanly also because of the relatvely large number of provders per capta), there are hardly any watng lsts. At the same tme, the Belgan system s characterzed by large co-payments, coverng overall about 20% of total health expendtures. There are no supplemental nsurance polces avalable whch fully cover these co-payments. However, the Belgan government ntroduced socal protecton mechansms for the poor and the sck, the most mportant beng a maxmum bllng celng, lnked to ncome. The (compulsory) nsurance package and the offcal fees are defned explctly through a complex process of negotatons, nvolvng the sckness funds, the provders, the government and the representatves of employers and employees who are the payers of the system. Compared to most other countres, the servce coverage s very broad, ncludng e.g. many dentstry tems and care n nursng homes for the elderly. The complcated decson procedure leads to a rather long delay between medcal nnovaton and ncluson n the compulsory cover. Ths s especally strkng for new 7

9 pharmaceutcals. Other tems not ncluded n the compulsory cover are orthodontcs, some less necessary pharmaceutcals, some physotherapy and non-tradtonal therapes such as acupuncture and homeopathy. Patents can buy supplemental nsurance for these treatments, but the mportance of ths remans rather lmted. Supplemental nsurance plays a much more mportant role n another respect. The Belgan system allows n some cases for extra-bllng ( supplements n the Belgan termnology). Extra-bllng plays an mportant role n hosptal fnancng. On top of copayments, patents can be charged a part of the prce of the materals used. Manly those optng for a sngle room can also be charged room and fee supplements. Physcans who do not subscrbe to the offcally negotated fees are allowed to rase supplements rrespectve of room choce for all patents wth the excepton of some vulnerable groups. Whle average co-payments per hosptal stay n a sngle room n 2003 were between 150 and 200, supplements were on average above Supplemental ( hosptal ) nsurance covers these costs and n addton usually the co-payments and supplements n the ambulatory sector, whch are lnked to the stay n the hosptal. Ths hosptal nsurance s by far the most mportant type of supplemental health nsurance n Belgum and the only one analysed n ths artcle. Both sckness funds and prvate nsurers provde supplemental nsurance. Gven that for-proft nsurers cannot enter the market for compulsory nsurance, tradtonal sckness funds have huge nformatonal and scale advantages. In the prvate sector, both group contracts and ndvdual contracts are offered. However, the prvate market share 3 More nformaton about supplements n Belgum can be found n De Graeve et al. (2006). 8

10 n supplemental health nsurance has remaned rather lmted and prvate nsurers focus on the hgher-ncome market segment. Accordng to Berghman and Meerbergen (2005), supplemental nsurance by the sckness funds and by prvate nsurers covered n 2001 the year of our data about 2.35% and 0.65% of total health care expendtures, respectvely. However, snce 2001, the mportance of supplemental nsurance has certanly grown. It should be clear that ths nsttutonal background wll nfluence both the coverage of the supplemental health nsurance and ts mpact on health care use. As mentoned before, there are hardly any watng lsts and patents wth and wthout supplemental nsurance are treated n the same hosptals. Supplements n hosptals are strctly regulated for patents n two-person and n common rooms and t can reasonably be expected that most patents n sngle rooms have supplemental nsurance. Whle a stay n a sngle room wll undoubtedly be more comfortable, t s much less obvous that t wll also mply a larger consumpton of health care or a better qualty of care n any case, f there s an effect, t must be due more to dfferences n provder behavour than to reactons by patents on prce dfferences. Moreover, gven the broad coverage of the compulsory system, we would only expect mnor effects of supplemental nsurance n the ambulatory sector manly for the few tems whch are not covered and perhaps for ambulatory treatment related to a hosptal stay. We wll analyse whether these predctons are confrmed by the data. In addton to supplemental hosptal nsurance, there s also n Belgum some substtutve voluntary health nsurance (Mossalos and Thomson, 2002) for the self- 9

11 employed. For them, the benefts package n the compulsory system s more restrcted n that t does not nclude the so-called mnor rsks (such as ambulatory care, medcnes, dental care). The sckness funds (and one prvate nsurer) offer voluntary nsurance for these mnor rsks. In ths paper, we do not analyse the effects and the coverage of ths substtutve system. In fact, t has been decded by the Belgan government that the compulsory coverage for the self-employed wll be harmonzed wth the overall system n the followng years, so that the substtutve voluntary health nsurance wll soon dsappear. Data Our data come from the Health Intervew Survey (HIS) 4 n 2001, a Belgan health survey that was set up by the Scentfc Insttute of Publc Health. The man objectve of the HIS s to provde nformaton on health status, lfestyle and utlzaton of preventve and health care servces of the whole populaton resdng n Belgum. All analyses n ths paper make use of samplng weghts provded by the HIS. The respondents of the HIS provded nformaton on supplemental nsurance. They frst receved some background nformaton to help them to answer the queston adequately,.e. the personal contrbuton n case of hosptalzaton can be heavly reduced n case of a supplemental nsurance for hosptalzaton. Such nsurance can be at your own cost or at the ntatve of your employer. The nsurance can be provded by a sckness fund or a prvate nsurer. Next, the respondents had to answer the actual queston: Do you have such supplemental hosptalzaton nsurance at your own cost or provded by your 4 More nformaton on the HIS can be found n Demarest et al. (2002). 10

12 employer? We decded to focus our analyss of the take-up at the ndvdual (and not at the household) level, because health status s supposed to be a crucal varable and can be defned adequately only at the ndvdual level. 5 We therefore omtted from the sample the respondents that were stll gong to school, because the supplementary nsurance queston dd not apply to them. We lost addtonal observatons due to temnon-response n the ndependent varables. However, the share of ndvduals wth supplemental hosptal nsurance (62.30%) n our estmaton sample (n = 6441) hardly devates from that n the total sample. 6 We wll now summarze the data on health care consumpton, on ndvdual (nonhealth) characterstcs and on ndvdual health. Summary statstcs for the estmaton sample are gven n Table 1. For categorcal varables we ndcated the reference category wth an astersk. Table 1 about here 5 For the analyss of the determnants of health care consumpton, we constructed a varable at the ndvdual level ndcatng whether the ndvdual or a famly member has supplemental health nsurance for hosptalzaton. Indeed, all common supplemental nsurance polces n Belgum nclude coverage of household members. 6 There s no good nformaton to cross-valdate ths percentage n Belgum. Statstcal analyss of the dfferences between the total sample and the estmaton sample gves no reasons to queston the assumpton of exogenous sample selecton. 11

13 Health care consumpton The HIS contans nformaton on utlzaton of the general practtoner, the specalst, emergency department, dentst, prescrbed and non-prescrbed drugs, and hosptal care. 7 GP and dentst care are recorded as the number of vsts durng the last two months. The same holds for emergency department and specalst care, although the former does exclude contacts wth an emergency department that resulted n hosptalzaton, and the latter excludes () contacts durng hosptalzaton and day care and () contacts at an emergency department. Utlzaton of hosptal care refers to general and psychatrc hosptals, but excludes hosptal vsts due to delveres. Vsts to day centres are not ncluded n the defnton of hosptal care, but are taken up as a separate queston. The nformaton on hosptalzatons allows us to defne at the ndvdual level the number of hosptal spells (wth a maxmum of three) durng the last year and the number of nghts durng each hosptalzaton. Ths allows us to mprove on the sngle spell hypothess whch has been common n prevous research (see e.g. the dscusson n Santos Slva and Wndmejer, 2001). Indvdual (non-health)characterstcs Table 1 summarzes the avalable demographc nformaton (male, age, famly type, natonalty). Wth respect to the constructon of the dummes on famly type, the HIS defnes chldren as household members who are 18 years or younger. A complex household was defned as a household whch cannot be attrbuted to one of the other four groups (e.g. three adults or more). 7 Note that n Table 1 there s addtonal tem-non-response for some tems of health care consumpton. 12

14 As for the soco-economc varables, we know monthly dsposable household ncome n Belgan Francs (1 = BEF). We equvalzed ncome usng the modfed OECD scale that weghs the frst ndvdual wth 1, subsequent ndvduals wth 0.5 and chldren (defned as 13 or younger) wth 0.3, and then categorzed t nto a set of sx ncome ranges n order to allow for a flexble functonal form. Educaton s captured by fve dummes on the hghest degree ever obtaned. Occupatonal status s measured wth a set of sx dummes. 8 We also observe whether an ndvdual qualfes for lower copayments due to preferental treatment ( verhoogde tegemoetkomng ) such preferental treatment s provded by the compulsory health nsurance system to patents wth a weaker soco-economc background. Fnally, we dspose of nformaton on lfestyle: sports actvtes, smokng and alcohol consumpton. Health varables One of the man strengths of the Belgan HIS s the large battery of questons on health status. Frst, we use self-assessed health (measured on a fve-pont scale) and a dummy ndcatng whether the ndvdual suffers from a chronc llness or s handcapped. Second, we calculated the body mass ndex on the bass of the avalable nformaton on heght and weght. We construct four regons of the body mass ndex (see e.g. Garrow, 8 The HIS does not nform on job characterstcs. Ths s unfortunate snce Berghman and Meerbergen (2005) have shown that these characterstcs are mportant for the take-up of employer-provded nsurance polces. The latter are more often taken out/provded to employees wth a long-term contract, workng n large frms and workng n specfc sectors. 13

15 1992): an ndex between 18 and 25 ndcates regular weght, whle (>=25) <18 ndcates (over-) underweght, and >=30 ndcates obesty. Thrd, the survey ncludes two constructed health ndcators. The frst GHQ12 aggregates nformaton from 12 questons on general well-beng nto one ndex (Goldberg et al., 1997). Hgher values of the ndex correspond to more severe states of well-beng. The second SF-36 physcal functonng score s based on 10 questons and captures physcal functonng wth hgher values correspondng to better physcal functonng. 9 Fourth, we have nformaton on 38 chronc and 3 acute dseases. Instead of ncludng separate dummes for each of these, we ncluded two dummy varables measurng the presence of at least one acute and one chronc dsease. 10 Fnally, the HIS ncludes 42 questons on health complants durng the last week: e.g. havng had a headache, breathng dffcultes, problems to breath, havng unpleasant thoughts, pan n chest, etc. Each queston has 5 categores, rangng from no problems at all to many problems. These questons are a subset of the 90 questons of the Symptom Checklst-90-Revsed whch has been used to evaluate psychologcal problems n the medcal lterature (see e.g. Derogats et al., 1981). We have decded to 9 The questons on the other SF-36 domans were not ncluded n the HIS. 10 Countng the number of dseases was not consdered as t assumes equal weghts for each of the dseases. 14

16 reduce the number of dmensons from 42 to 2 usng factor analyss. 11 The frst factor measures mood, whle the second s an ndcator of pan, wth hgher values ndcatng worse mood/pan. Who takes up supplemental health nsurance? Snce the take-up of supplemental health nsurance s recorded as a dummy varable, we use a bnary probt model to analyse the take-up decson,.e. we specfy P I 1 x x (1) ' where the subscrpt 1,..., n stands for the th ndvdual, I takes the value 1 f the ndvdual has supplemental health nsurance (and 0 otherwse), x s a vector of explanatory varables, a vector of parameters to be estmated and. s the standard normal cumulatve dstrbuton functon. Although estmaton of the probt model n equaton (1) bols down to estmatng the parameters, we are not n the frst place nterested n the estmates of these parameters as such, but rather n the effect of 11 More nformaton about ths factor analyss can be obtaned from the authors on request. We dd not apply factor analyss to the other health varables (SAH, chronc, BMI, GHQ12, SF36 physcal functonng, acute, chron) for two reasons. Frst, self-assessed health, the dummy on chronc llnesses, and the body mass ndex have a clear nterpretaton. The propertes of the constructed ndces GHQ12 and SF36 physcal functonng score are well known (e.g. Goldberg et al., 1997, and summarzng the questons on acute and chronc llnesses nto two dummy varables has some ntutve appeal. Second, factor analyss s nadequate for varables wth fewer than fve categores (see e.g. Johnson and Wchern, 2002). Obvously, ths does hold for some of the health varables used n ths paper. 15

17 the determnants x upon the probablty of havng supplemental health nsurance. In the case of a contnuous varable x k, we calculate ths effect as: (2) Pˆ I 1 x x k x x ˆ ˆ k where hats are used for estmates and. denotes the standard normal densty functon. Ths expresson gves the change n the probablty of havng supplemental health nsurance for an ndvdual wth average (upper bar) characterstcs resultng from a one-unt change n the varable x k. In case of a dummy varable x d, we calculate ts effect pˆ ˆ ˆ d P I x; xd 1 P I x; xd 0 supplemental health nsurance by: on the probablty of havng (3) pˆ ˆ ˆ ˆ ˆ ˆ d d xd d d xd... d 1xd 1 d 1xd 1 Table 2 about here Estmates of expressons (2) and (3) are gven n Table 2. Statstcal nference s based on the sandwch estmator of the covarance matrx and corrects for clusterng at the household level. Regonal (dstrct) dummes are ncluded as controls, but the results for these dummes are not reported. The RESET-test (based on the jont sgnfcance of the square and cube of the predcted lnear ndex ' x ˆ n equaton (1)) has a p-value of whch rejects the alternatve hypothess of msspecfcaton (Peters, 2000) and we found no ndcatons of heteroskedastcty usng a probt model wth multplcatve varance functon. To test the robustness of our fndngs, we also estmated the model wth all knds of nteracton effects ncluded. Most of these nteracton effects were 16

18 nsgnfcant, and none led to convncng results whch would necesstate a renterpretaton of the fndngs of the smple model. 12 Let us now turn to the nterpretaton of the results n Table 2. Frst, we fnd that among the demographc varables, only age, beng sngle wthout chldren and beng a non-eu member are relevant determnants of supplemental nsurance. Compared to the reference age category of 40 44, persons aged between 50 and 70 are more lkely to have supplemental nsurance. Ths fndng seems to be demand-drven, whereas the declne n nsurance coverage for the 70+ (compared to those between 50 and 70) mght result from excluson restrctons n nsurance polces or from hgher prces offered to the elderly. Unsurprsngly, sngles are less lkely to have supplemental nsurance and the same holds for non-belgans, although the effect s much stronger for ndvduals orgnatng from outsde the European Unon. Second, there are strong soco-economc dfferences. Indvduals wth a unversty and hgher educaton degree are more lkely, and ndvduals wth no or prmary educaton are less lkely, to have supplemental nsurance. The results suggest that the relatonshp s non-monotonc,.e. ndvduals wth a unversty degree are less lkely to have supplemental nsurance than ndvduals wth a hgher (non-unversty) educaton degree. For equvalent ncome, a smlar pattern s found,.e. nsurance take-up s assocated wth hgher ncome, but agan the pattern s non-monotonc. Ths non- 12 We checked the predctve power of the model by analysng the percentage of correct predctons n the sample and by mplementng an out-of-sample forecastng exercse along the lnes of Jmenez-Martn et al. (2002). The latter was based on 100 random subdvsons of the sample n a tranng (80%) and a forecast sample (20%). The model performs well and we found no evdence of over-fttng. 17

19 monotoncty at the top s hard to explan, but should not detract from the man concluson that there s a clear soco-economc gradent n the take-up of supplemental nsurance. Ths s confrmed by the fndngs for the occupatonal groups. Employees are more lkely than any other occupatonal category to have supplemental nsurance. Among the other categores, we observe n decreasng order the self-employed, retred, sck, others not workng and the unemployed. The fndng for the self-employed s reasonable snce compared to some employees they have to fnance ther nsurance polces prvately. The lower degree of rsk poolng due to the absence of collectve contracts probably mples hgher nsurance premums. Fnally, whether an ndvdual s elgble for reduced co-payments s not mportant. Thrd, the results wth respect to health and lfestyle varables are mxed. Compared to ndvduals n good self-assessed health, ndvduals n very good health are less lkely to buy supplemental health nsurance, whch may pont to some adverse selecton. However, ndvduals n far and poor health are also less lkely to take out nsurance. 13 Ths does not necessarly mply that there s no adverse selecton at all, snce the (a pror postve) effect of the lower health status may be offset by the (negatve) effect of the prcng and selecton behavour of the nsurers (see, e.g. Shmuel, 2001), but t nevertheless suggests that the adverse selecton effect s not very strong. Moreover, and more mportantly, none of the other health ndcators s sgnfcant at the 5% level. Wth respect to the lfestyle varables, we fnd that practcng sport has a postve effect, 13 The nsgnfcance of the effect for those n very poor health s not surprsng, snce the number of respondents n very poor health n the sample s very small. 18

20 whereas the effect of smokng s negatve. Ths mght capture nter-ndvdual dfferences n health awareness. Summarzng our results, we fnd only weak evdence of adverse selecton and much stronger evdence for soco-economc nequaltes n take-up. Ths s well n lne wth what could be predcted on the bass of our descrpton of the Belgan nsttutonal settng, characterzed by the very broad coverage of the compulsory system and the (relatve) luxury character of the tems covered by supplemental nsurance. One does not need supplemental nsurance to be treated well when ll or to avod watng lsts. However, when one can afford t, takng supplemental nsurance may lead to a more comfortable (and less expensve) stay n the hosptal. Let us now see whether we fnd some effects of supplemental nsurance coverage on health care use. Supplemental nsurance and health care use We frst analyse npatent care consumpton. We use a model that dstngushes between the number of spells and the number of nghts per spell. In the second subsecton we analyse the results for the categores of outpatent care that are avalable n our data. In these two subsectons we treat the supplemental nsurance dummy as exogenous. We wll return to that assumpton n a thrd subsecton. Inpatent care The HIS nforms on the number of spells and the number of nghts per spell durng the last year. Ths allows us to model the ndvdual decson process more explctly than s 19

21 tradtonally done n the lterature on the determnants of hosptal nghts. Ths may be mportant, snce t can be argued that the decson on the number of occasons to go to the hosptal (.e. to start a spell) s dfferent from the decson on the number of nghts, n that the patent has much less decson power on the latter than on the former decson. We stck to the popular ndependence assumpton of two-part models, but account for spells,.e. we assume that the data generatng process of the number of spells s ndependent from the data generatng process of the number of nghts per spell. We further assume that the data generatng process of the number of nghts per spell s smlar for each spell and ndependent between spells (see further for addtonal argumentaton). Both ndependence assumptons enable us to estmate the number of spells and the number of nghts per spell separately, rather than jontly, whch s easly seen from the condtonal densty: (4) k 1 s 0 f ns P s 0 P s k P n l nl 0 k 1 l 1 k 1 s k 1 s 1 k s l P s k P n l nl 0 k 0 k 1 l 1 number of spells number of nghts per spell 1 s l 1 s k where we have for ease of exposton not explctly accounted for condtonng on explanatory varables. n s denotes the number of nghts ndvdual spends n the hosptal durng spell s, s s the number of spells, 1. s an ndcator functon. 20

22 To analyse the number of spells, we use the negatve bnomal densty. 14,15 Ths model assumes that the number of hosptal spells of ndvdual s Posson dstrbuted, condtonal on the Posson parameter : (5) P s s exp s! The negatve bnomal regresson model s then obtaned by assumng that the Posson parameter can be parameterzed as an exponental functon of the explanatory varables y and a gamma dstrbuted random component ( ): ' (6) exp y v where s a vector of parameters to be estmated and follows a gamma dstrbuton wth unt mean and varance. It can be shown that the condtonal mean and varance of the number of spells are then gven by (7) ' E s y ; exp y (8) V s y; E s y; 1 E s y; Equaton (8) shows that the condtonal varance s allowed to be larger than the condtonal mean a commonly observed characterstc of health care data f 0 14 We dd not correct for censorng n the number of spells at 3 as t only concerns 44 ndvduals. Nor dd we correct for censorng n the number of hosptal nghts durng the last spell (.e. ongong hosptalzatons durng the tme of the ntervew) snce t only concerns 24 spells. 15 We checked the performance of a two-part count data model consstng of a probt to explan whether there s at least one spell, and a truncated at zero negatve bnomal model explanng the number of spells. Based on the Akake Informaton Crteron (.e and 6214 for, respectvely, the negatve bnomal and the two-part model), we preferred the negatve bnomal regresson model. 21

23 and E s y ; 0. If 0, the condtonal mean and varance are equal and the model reduces to the Posson regresson model. We are not nterested n the estmates of the parameters as such, but n the effect of the determnants y upon the number of spells s. Usng (7), we summarze the effects of contnuous and dummy varables (say y k and y d respectvely) as: (9) E s y,, y, y 1, y,, y ; 1, k 1 k, k 1 m E s y ; exp k (10) E s y,, y,1, y,, y ; 1, d 1, d 1 m E s y,, y,0, y,, y ; 1, d 1, d 1 m exp d Equaton (10) shows that the exponent of a coeffcent of a dummy varable can be nterpreted as the proportonal change n the number of spells f the dummy goes from zero to one. Equaton (9) shows that a smlar nterpretaton can be gven to the coeffcent of a contnuous varable,.e. the exponent of the coeffcent measures the proportonal change n the number of spells resultng from a one-unt ncrease of the contnuous varable. The second varable,.e. the number of hosptal nghts per spell, can only take strctly postve and nteger values. 16 We therefore analyse ths varable wth the truncated at zero negatve bnomal regresson model. The condtonal densty for the number of hosptal nghts per spell s wrtten as: 16 Note that the unt of analyss s here the spell (hence the subscrpt l), whereas t was the ndvdual for the number of spells. 22

24 (11) P n n 0, z ; ' l l l exp l nl! 1 exp n l l l ' wth Posson parameter l exp zl l, where z l s the vector of explanatory varables 17, s a vector of parameters to be estmated, and dstrbuton wth unt mean and varance l follows a gamma '. Analogous to equatons (9) and (10) we wll present the estmaton results n the form of exponentated coeffcents, whch can be nterpreted as the proportonal ncrease n the untruncated number of nghts. The estmaton results are shown n Table 3. All statstcal nference s based on the sandwch estmator of the covarance matrx and corrects for clusterng at the household level. Agan, we dd nclude but do not report the regonal (dstrct) controls. The columns (1a) and (1b) gve the results for the number of spells; columns (2a) and (2b) gve the results for the number of nghts per spell. In both cases we ntroduced a dummy ndcatng whether the ndvdual was lvng n a household wth at least one member havng supplemental nsurance (ns_famly). In fact, we know that all common supplemental nsurance polces n Belgum nclude coverage of household members (see data secton). Recall that utlzaton refers to general and psychatrc hosptals, but excludes hosptal spells for delveres. The RESET-tests (p-values of and for the number of spells and the number of nghts per spell respectvely) do not pont to msspecfcaton (Peters, 2000), and the estmates of show that the (truncated) negatve bnomal model s preferred to the (truncated) Posson model. 17 In the emprcal exercse, we have only explanatory varables at the ndvdual level. Nevertheless, the use of the l subscrpt s justfed snce we also nclude dummy varables for the second and thrd spell. 23

25 Table 3 about here Let us frst look at the results for the number of spells n the columns (1a) and (1b). Frst, the number of spells s smaller for the unemployed and for the smokers. These two effects weakly suggest some soco-economc bas (whch would then not be captured by educaton and ncome, that do not play a sgnfcant role). Second, the health varables are sgnfcant n explanng the number of hosptal spells. Havng an acute or a chronc llness, or a poor level of self-assessed health, ncreases the number of spells and the same s true for worse physcal functonng as measured by SF-36. Thrd (and most mportantly), the number of hosptal spells s not related to whether the ndvdual or one of hs/her famly members has supplemental health nsurance for hosptalzaton. Let us now turn to the estmaton results for the number of nghts per spell (columns 2a and 2b). We ncluded n the model dummes for the second and thrd spell (the frst spell s the reference category). These dummes are jontly nsgnfcant, whch gves some justfcaton () for our assumpton of ndependence between the data generaton process of the number of spells and the number of nghts per spell, and () for assumng that the data generatng process of the number of nghts per spell s smlar for each spell (nstead of havng a separate equaton for each subsequent spell). Compared to columns (1a) and (1b), other determnants play a role now. We fnd that males, the elderly and the age category spend more nghts n hosptal. Sngles have more nghts whch mght have to do wth lack of famly support. We further observe that an equvalent ncome above BEF a month (about 2.000) s correlated wth fewer 24

26 nghts. The effect of the health varables s slghtly weaker here than for the number of spells. Self-assessed health s not sgnfcant, but a BMI below 18 and SF-36 have sgnfcant and expected effects. When nterpretng ths fndng, one should take nto account that our dependent varable s the number of nghts per spell and not the ntensty of treatment. The most strkng result s the strongly negatve effect of havng a supplemental nsurance on the number of nghts per spell. 18 We do not fnd the slghtest ndcaton of moral hazard n the form of an ncrease n the number of days spent n the hosptal. Remember that ths s not surprsng n the Belgan context, n whch the supplemental nsurance covers luxury servces and the ambulatory treatment after havng left the hosptal. If supplemental nsurance leads to a hgher ntensty (perhaps even a better qualty) of care n one-person rooms, shorter spells are not really surprsng. Note n ths respect that many hosptals have a shortage of one-person rooms, and therefore no strong ncentves to keep ther patents for a longer perod. Qute the contrary, f supplemental nsurance s taken up by the better educated and hgher-ncome groups, a shorter stay n sngle rooms may be good for the reputaton of the hosptal among the groups concerned. Outpatent care Let us now have a look at the effect of supplemental nsurance on outpatent care consumpton. As mentoned before, HIS contans nformaton about the number of vsts 18 Ths result s very robust when we change the specfcaton of the model by omttng some of the ncluded varables. 25

27 to the general practtoner, the specalst, the emergency department, or the dentst durng the past two months, about the number of spells n a day centre durng the past year and about the number of prescrbed and non-prescrbed drugs used durng the past two weeks. We estmated negatve bnomal regresson models for each of these outpatent care categores, but the negatve bnomal model dd not ft well for vsts to the general practtoner, the specalst, and the number of prescrbed and non-prescrbed drugs. 19 For the latter four categores, we estmated a two-part model consstng of a probt model (Probt) (see equaton (1)) and a truncated at zero negatve bnomal regresson model (Negbn0) (see equaton (10) wthout the l subscrpt), whch ftted the data consderably better. The estmaton results are presented n Table 4. Agan, regonal controls are ncluded but not reported. Table 4 about here The results for the dfferent categores speak for themselves and are generally n lne wth what could be expected a pror. Agan, the results for the supplemental nsurance dummy can easly be explaned wth the Belgan nsttutonal background n mnd. There s no effect on vsts to a GP or to a specalst, and on consumpton of prescrbed pharmaceutcals. All these are covered n the compulsory system and there are no watng lsts, whle supplemental nsurance n general does not cover co-payments. Supplemental nsurance has a postve effect on dentstry remember that orthodontc treatment s only ncompletely covered n the compulsory system. The lower tendency 19 The p-values of the RESET-test (Peters, 2000) were (gp, spec and med_p), (med_np), (emdep), (dent), and (daycentre). 26

28 to go to an emergency department and the hgher tendency for the use of day centres are n lne wth the atttude towards the hosptal system that also resulted n the shorter spells that were found n Table 3. The endogenety of the health nsurance dummy All our results n ths secton were derved wthn a model n whch we assumed that the dummy on supplemental health nsurance at the famly level could be seen as an exogenous ndependent varable. In fact, correctng for endogenety s not trval n the count models that we used. However, we do not thnk that ths nvaldates our results. Our most mportant argument for that clam s that, compared to other econometrc work n ths area, we have used very rch nformaton on the health status (and the lfestyle) of our respondents and t would be hghly surprsng ndeed f there was much unobservable health varaton left. 20 Moreover, the statstcal results do not suggest that there s a problem. Frst, the probt model n the secton on supplemental nsurance uptake gves hardly any evdence for adverse selecton. Second, the nsurance dummy s by far the most sgnfcant n the model for the number of nghts per hosptal spell, and ts effect s strongly negatve (contrary to what one would expect on the bass of the endogenety hypothess). Fnally, we have also expermented wth a relatvely smple model to correct explctly for endogenety,.e. the bvarate probt model that jontly models the probablty of at 20 Note that the nformaton that we used s much rcher than the nformaton that s avalable to the nsurers when decdng about polces and premums. 27

29 least one contact/nght and the uptake of supplemental nsurance (see e.g. Holly et al., 1998). Nether for npatent care, nor for the outpatent care categores, we could reject the null hypothess of a zero correlaton coeffcent of the bvarate normal dstrbuton. 21 Concluson When analysng the effects of supplemental health nsurance, t s essental to take nto account the overall nsttutonal background of the health care system. Both the take-up of supplemental nsurance and the (supplemental) nsurance effect on health care consumpton wll crucally depend on the specfc features of the publc (compulsory) system. Smplstc nternatonal comparsons may therefore be hghly msleadng. Ths general dea s well llustrated by our results for Belgum, a country n whch the compulsory system has a very broad coverage, where there are no watng lsts n the publc system and where supplemental nsurance (at least untl now) does not buy better health care qualty. Moreover, supplemental nsurance manly relates to extra-bllng, appled to patents who opt for a sngle room n the hosptal. Ths nsttutonal settng leads to specfc predctons whch are well corroborated n our emprcal analyss. There are only very weak ndcatons of adverse selecton n the 21 The lowest p-value was obtaned for the bvarate probt model for prescrbed drugs where we ncluded all regressors n the supplemental nsurance take-up equaton and excluded all regressors except male, age, ncome and educaton from the utlzaton equaton,.e For other health care categores or other assumptons on the excluson restrctons, we always got a hgher p-value. 28

30 take-up of supplemental nsurance, but there s a strong soco-economc gradent. Moreover, a count model for hosptal care that explctly accounts for the number of spells shows that supplemental nsurance has no effect on the number of hosptal spells and a sgnfcantly negatve effect on the number of nghts per spell. The latter result s n lne wth the fndng of soco-economc stratfcaton n supplemental nsurance and n the ensung choce of rooms. The results for outpatent care also confrm the theoretcal predctons: no effect on the number of vsts to the general practtoner or the specalst; a postve effect on dentstry (ncludng orthodontcs, whch are not covered n the compulsory system); and a tendency to go for a qualtatvely better use of the hosptal sector (more vsts to day centres, less vsts to emergency departments). In Belgum, therefore, supplemental nsurance as such can most probably not explan the pro-rch nequty n the use of specalst care. However, the overall pattern of socoeconomc bas n the take-up of supplemental nsurance rases subtle questons about soco-economc dfferences n the qualty of treatment. At ths stage, we have no ndcatons that the qualty of medcal treatment depends on the type of room and hence de facto on the soco-economc group (van de Glnd et al., 2007). But what s the relatve mportance of medcal and non-medcal factors n defnng qualty? And how to defne what should be ncluded n the compulsory coverage and what can be left to prvate decsons? The Belgan experence suggests that such more subtle questons should also be consdered when analysng the growng mportance of supplemental nsurance. 29

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