Bonus systems in health insurance: a microeconomic analysis

273

Health Policy, 7 (1987) 273-288 Elsevier HPE 00109

Bonus systems in health insurance: a microeconomic analysis* Peter Zweifel lnstitut fiir Empirische Switzerland Accepted

6 July

Wirtschaftsforschung

der Universitgt

Ziirich,

Ztirich,

7986

Summary Faced with the cost explosion in the health care sector, policy-makers in most industrialized countries have been focusing on cost-sharing in health insurance as a possible solution. This is a sanction meted out to users of medical care; the alternative of creating positive incentives for non-users has not yet received nearly as much attention. This paper reports on the experiences made by German private health insurers with their plans offering rebates as well as experience-rated bonuses for no claims. It is argued that a rebate offer may be at least as attractive as conventional cost-sharing plans from the point of view of the consumer since these new options allow him to choose the time at which he is to bear the financial consequences of an illness. In the second part of the paper, predictions are derived concerning the incentives contained in the policies written by three particular insurers. Clear evidence of a decrease in demand for ambulatory medical care at the lower end of the billings distribution is found in rebate and bonus plans. The concluding section of the paper contains a discussion of the results with a view on the continuing debate about the reform of social health insurance. Health insurance;

Bonus system; Health care cost

* Revised version of a paper presented at the 3rd Symposium on Health Instelling Antwerpen. Antwerp, Belgium, September 12-13, 1985. Address for correspondence: Prof. P. Zweifel, Institut fur Empirische versitlt Zurich. KleinstraRe 15. 8008 Zurich. Switzerland.

0168-8510/87/$03.50

0

1987 Elsevier

Science

Publishers

and Economics,

Wirtschaftsforschung

B.V. (Biomedical

Division)

Universitaire

der IJni-

274

Introduction An impartial observer of the ongoing international discussion on cost containment in health care would be struck by the onesidedness of the argument. Focus is invariably on cost-sharing as a sanction meted out to the user of services, both in research and in policy debates [l-3]. The alternative of creating incentives to non-users of medical care seems to be just about forgotten. However, private health insurers in West Germany have been offering rebates as well as experience-rated bonuses to their members for several years, and their experiences should be of interest internationally [4]. Therefore, a project was initiated by the Robert Bosch Foundation in 1981 with the objective of systematically investigating the properties of such contracts. In particular, this contribution is based on two working hypotheses: First, rebates and bonus options are deemed to be at least as attractive to the insured as conventional cost-sharing alternatives. Second, these new contracts are predicted to dampen utilization of services very much like traditional costsharing methods, with experience-rated bonus options having even more impact than fixed rebates for no claims. The plan of this paper is as follows. First, the rebate offer is compared to a costsharing contract from the point of view of the consumer. Rebate and bonus options are usually introduced into all policies written by a particular private insurer; thus, if an insured does not like them, he must turn to another company. In view of this mobility barrier, the mere .fact that nine out of ten leading private insurers in West Germany offer rebates or bonuses in 1985 whereas only one did so in 1980 is not sufficient to prove that these new options are in the interest of their members. For this reason, a microeconomic argument is developed showing that these new policies may be superior to conventional ones from the consumers’ point of view as well. The second part of the paper contains a description of policies written by three insurers: A, B, and C. A continues to offer plans with and without deductibles and coinsurance; B pays back a rebate amounting to three monthly premiums if the insured abstains from filing a claim during a year; C offers a bonus amounting to two monthly premiums (as of 1982) in the first year with no claims, three in the second year, and four starting from the third consecutive year with no claims. Using a simple microeconomic model, predictions are derived concerning the policies’ respective ability to induce an insured to forego ambulatory medical care given a minor impairment of his health. These predictions are subjected to empirical tests in the third part of the paper. Rebates and bonuses also create incentives for not submitting a claim although medical care was consumed. Particular care is taken to eliminate this submission effect because it amounts to a mere cost-shifting between the insured and the insurer. Social savings only accrue if the insured changes his behavior, i.e. if he reduces his utilization of medical care services. But by doing so, he might jeopardize his future health. Therefore, the empirical analysis is extended to cover two consecutive years in an attempt to detect traces of a toothsaw pattern in medical utilization. The concluding section of the paper contains a discussion and evaluation of the results, with particular reference to the ongoing debate about the reform of social health insurance.

The welfare

economics of health insurance policies

At first sight, a rebate offer might seem to be nothing but a gimmick on the part of the insurer for cashing in higher premiums earlier, with the insured foregoing interest income he could have if his money was not tied up with the insurance. This conception of a rebate or a bonus option overlooks the fact that there are really two risks, with the amount of correlation between them reduced by the bonus option. The first risk is the loss of health itself. This loss can be transformed into an equivalent loss of wealth, as in panel A of Fig. 1. Such a transformation B: Financial risk

A: Health risk, transformed into financial risk

U

*u(w)

4 A' =E(U) U-

1

I

wi

I

E(W)

WH’

..

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E(W)

L W‘

C: The two risks combined U

wi Fig. 1 Comparing

a rebate

option

W;=W-=E(W)

I

with a conventional

cost sharing

plan.

W

276

is based on the notion that a given level of wealth yields less utility to an individual when ill than when healthy. But as long as utility increases with wealth, a health loss can be neutralized by a (possibly large) increment of wealth [5]. In panel A of Fig. 1, this increment amounts to the difference between WA (good health) and W, (bad health). Assuming a 50 per cent chance of falling ill, the depicted variation in the state of health results in an expected equivalent wealth level of E(W). If health could be stabilized at this average level, the individual’s utility would be at point A; since he is assumed risk averse, his expected utility from this ‘health lottery’ amounts to point A’ only. The fact that A is higher up on the utility scale than A’ makes clear that such an individual would like to insure health itself if this were possible. What can be insured are the financial consequences of an illness episode. For simplicity, the concomitant variation in wealth is assumed to be equal to the one shown in panel A. Panel B of Fig. 1 depicts an individual with health insurance. If the policy is of the deductible type, his wealth is W+ if healthy and W- if ill, the difference mirroring the size of the deductible. If it is of the rebate type. the same wealth levels obtain because the insured stays put at W- if ill instead of cashing in the rebate and moving up to W+ if healthy. Thus, the two policies are financially equivalent in Fig. 1. Despite this financial equivalence, the two alternatives are not equivalent as soon as the possible correlation between the health risk and the financial risk is taken into account. Under a deductible policy, the financial loss shown in panel B of Fig. 1 may well coincide with the health loss of panel A in the course of a year. Under a rebate option, this loss is pre-paid in the guise of a somewhat higher monthly premium, which serves to break the positive correlation between the two losses. For ease of exposition, extreme assumptions are used in panel C of Fig. 1, which combines the financial risk and the health risk, expressed in equivalent wealth. At the one extreme, let the two risks be perfectly correlated under the deductible plan. Thus, a healthy month will be characterized by a utility as high as U&. But with 50% chance, ill health strikes and the deductible is due, resulting in a utility as low as U;. Hence, expected utility under the deductible plan is given by point D in Fig. 1. At the other extreme, let the two risks be independent under the rebate plan. In a given month, the insured thus still faces the health risk, but no extra financial risk will be associated with it. Variation between utility levels Uw and Uw solely mirrors the insured’s uncertainty as to whether he will be able to obtain his rebate at the end of the year. As derived in panel B of Fig. 1. this lottery yields expected utility according to point B’. The independent health lottery, on the other hand, yields expected utility as indicated by point A’. Mixtures of these two lotteries are evaluated according to the straight line connecting A’ and B’. In particular, a rebate option that is financially equivalent to the deductible plan (both implying expected wealth equal to E(W) in panel C) yields expected utility as given by point E. But point E is higher up on the utility scale than point D. This means that the rebate option dominates a financially equivalent deductible plan. It should be emphasized that this argument does not prove that traditional contracts (as well as self-insurance) are always inferior to rebate offers or comparable

277

bonus options. At least in theory, a conventional contract could be complemented by another policy covering the net cost of medical care. If indeed available, such a combination might well be preferred to a rebate offer. Additionally, self-insurance could be a viable alternative if interest to be earned on cash not tied up in insurance premiums is high enough. This argument can be summed up in Conclusion 1: To the extent that the risk of having to pay the net cost of medical care is correlated with the risk of health loss under a deductible plan while the two risks are dissociated under a rebate option, the rebate option will tend to dominate both a financially equivalent policy with cost sharing as well as self-insurance. This proposition cannot be tested empirically on the basis of available data, for the records do not contain information concerning choice among private insurers nor the reasons for this choice.

Three health insurance policies compared Given that individuals are insured by the same company, they are exposed to much the same financial incentives. Therefore. generating predictions concerning one type of policy only is not sufficient. Rather, differential predictions among the three insurers must be derived, e.g. comparing insurer B (offering a fixed rebate of three monthly premiums) to insurer C (offering an experience-rated bonus of two to four monthly premiums). In order to be able to deal with insurer C in the sequel, the planning horizon is two years throughout. In Fig. 2, a simple two goods model is shown with hours of medical service (M) on the horizontal and all other goods (X) on the vertical axis. In an attempt to mirror limited consumer sovereignty in health care, choice is restricted between 0 and Mi physician hours (which are assumed to cost 150 DM or 50 U.S. dollars). The straight line AA’ depicts the budget constraint of a member of insurance A with full coverage. It runs close to the origin because such a plan has a high price. By way of contrast, BB’ mirrors the lower premium of the rebate policy written by insurer B. If a member of B accepts the treatment offer comprising M1 hours of care, he attains utility level I; at point B-. If he saves his rebate by foregoing ambulatory care, his new budget constraint originates from point B+ on the X axis. However, he would have to face the full price for every physician minute, making him move along the steep budget constraint towards point R. The two budget constraints intersect at point R in Fig. 2, indicating a submission threshold: for an annual bill falling short of R (about 4 hours work of ambulatory care), it is better to pay it out of one’s own pocket. Beyond point R, the insured fares better submitting his medical bill. Given the indifference curves shown in Fig. 2, point B- (M, hours of medical care) yields slightly higher utility than alternative B+ (no medical care and rebate saved). In this case, the rebate option fails to induce the insured to go without medical care. A fortiori, the same individual would also take advantage of the

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hours,

at 50 S)

Fig. 2 Incentives

contained

in rebate option (insurer 8). 2 years horizon

treatment offer if covered by A’s plan because any point along AA’ ranks higher than point A on the X axis. Now let the situation repeat itself in the following year. with the physician fixing intensity of care at MI hours and the health problem being of the same severity as in the year before. Over the 2-year period, the choice is between 0 and M, hours of care if the insured did not see the physician in the first year and between M,

279

and 2Mi hours of care if the insured went to see the doctor in the first year. But under the assumptions made, the individual should decide exactly the same way in the second year as in the first. If he saw the physician during the first year (as in Fig. 2), he should turn to him again. His second year budget constraint originates either at point B-+ (saving his rebate) or B- (consuming care). According to indifference curve J;, obtaining M, (= 6 hours) of care is again superior to having none. The same holds true if the individual were covered by the no cost-sharing policy of A. On the other hand, if the enrollee of B went without medical care during the first year, he should continue to do so, too. This argument may be summed up by Conclrlsion 2: Other things being equal, a member of insurance A will be more inclined to demand medical care for the treatment of a minor health problem than a similar member of insurance B. Fig. 3 depicts the decision problem facing an enrollee of insurer C. While indifference curves are exactly the same as in Fig. 2, budget constraints differ due to the experience-rated bonuses offered by C. In view of the fact that next year’s bonus depends on this year’s utilization of medical services, dynamic optimization methods are called for in principle [6,7]. However, in a very simple special case (no discounting of future receipts and outlays, identical utility functions in only two consecutive periods of equal length), a graphical analysis is possible. The limiting case of indifference serves as the point of departure in the first period, allowing the optimal decision in the first period to be determined in the light of the optimal decision made in the second period. Moreover, the bonus to be reaped in the first year is assumed to amount to three months premiums, the same as the fixed rebate offered by insurer B (see Fig. 2 above). This implies that the insured did not submit a claim in the previous year. Thus, the insured has a choice between two budget constraints in the first year: if he falls back on insurance, the relevant boundary is CC’C”, reflecting the fact that insurer C’s plans have a deductible of 2.50 DM (1.67 physician hours) throughout. If he saves his bonus, the constraint is given by the straight line starting from point C,+. Should he decide to see the physician in the first period, he ends up at point C,, which is by assumption on the same level of utility as C3+. Budget constraints in the second year depend on the decision made in the first year. If the individual took advantage of the physician’s treatment offer after all, his point of departure in the second year is C, in Fig. 3. Should he fall back on insurance once more, the boundary defined by points C,-, C3-‘, and C3-” applies. On the other hand, he could earn a bonus amounting to two monthly premiums if he managed to refrain from consuming medical care in the second period. But this incentive will not suffice to make him go without care because the same individual under the same conditions was just indifferent when the bonus at stake was as high as three monthly payments. Thus, consuming Mi hours of medical care will rank higher than the prospect of saving the bonus in the second year, given that ambulatory care was preferred to the bonus in the first year. Alternatively, the individual might have saved his bonus in the first year. In that

280

case, the attainable bonus in the second year will amount to four monthly premiums, corresponding to the point of departure C4+ on the X axis of Fig. 3. This is to be compared to consuming M, of care in the second year, symbolized by point C,_ in Fig. 3. Since the individual previously was indifferent between medical care and the bonus of three monthly premiums, he will certainly save his bonus of four monthly premiums in the second year. Thus, the optimal decision in the second

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Fig. 3 Incentives

contained

in an experience-rated

bonus

option

(insurer

C). 2 years horizon.

281

year is to refrain from consuming medical care, implying that the total bonus at stake in the first year is not three but as much as seven monthly premiums. Under these circumstances, the individual insured by C will refrain from calling on the physician in both years. This argument leads up to Conclusion 3: The prospect of saving an even higher bonus in the subsequent year may induce members of insurance C to refrain from consuming ambulatory care in the current as well as in the subsequent year whereas a member of insurance B would have demanded medical care in both periods. It is important to see that the statement holds true only in the case of minor illness. Should the physician deem the health problem severe enough as to warrant 2M, hours of care in the first period, then even an enrollee of insurer B would want to take advantage of this offer. In Fig. 3, the newly attainable point is in the neighbourhood of C 3+” (at M = 12), which certainly ranks higher than point C4+ on the X axis, according to indifference curve Jr. Alternatively, the insured himself might rate his health problem as serious, which would be reflected by indifference curves sloping down more steeply than in Fig. 3. In that event, an attainable point like C, (corresponding to M, hours of care) is preferred to point C4+ (reflecting receipt of the rebate).

Empirical results This section is devoted to empirical tests of the theoretical predictions derived above. The sample used comprises segments of populations enrolled by the three insurers, with full coverage policies selected from A and B. As to insurer C, a mandatory deductible of 250 DM (8.5 U.S. Dollars at 198.5 exchange rates) applies throughout. Eliminating effects of submission: As a rule, the insured will submit their medical bills only if their total exceeds the value of the rebate (plus a deductible Table 1 Dependent

variable and auxiliary variables used for their construction,

Variable

Definition

D82

= 1: Costs of ambulatory THRESHOLD

1982

Mean

S.D.

care in excess of 0.29

LIMITA LIMITB LIMITC

Limit above which insured submit their medical bills. defined for subsamples A. B and C

0 771 1534

0 223 347

THRESHOLD

max (LIMITA. LIMITB, LIMITC), equivalently defined for all insured of given age and sex

1379

339

-

282

if applicable), cf. intersection ponts R and U in Figs. 2 and 3. Beyond this threshold, the billings distribution should be complete. Since conclusions 2 and 3 do not refer to the filing decision but to impacts on actual demand for ambulatory care. analysis of the billings distribution must focus on values at or above this submission threshold. Submission thresholds are determined for a 2-year horizon since only billings for the years 1981 and 1982 are jointly available for all three insurers. This threshold is highest for enrollees of insurer C: in 1981, the bonus at stake could be as high as seven monthly premiums (undiscounted). For these insured, the threshold amounts to ‘seven monthly premiums plus deductible 2.50 DM’. This is a conservative estimate because members who had not attained maximum bonus in 1982 or did not count on saving their bonus in subsequent years would have submitted smaller billings to their insurance as well. Members of insurances A and B must be assigned virtual submission thresholds that would be in effect if they were enrolled by C. First, in each age-sex-cell of insurer C’s population, the maximum value of the submission threshold is determined. Second, these values are assigned to members of insurers A and B in the same age-sex-cell. For empirical estimation, a binary dependent variable D82 is defined as follows: If the billing for ambulatory medical care exceeds the submission threshold, it takes on the value of 1, otherwise it is 0. Table 1 below documents the construction of this dependent variable, along with some distributional information. Table 2 contains analogous information concerning explanatory variables. Among other things, it shows that the three insurers have a different age structure in that the share of members aged 45 to 54 varies between 12% with A and 27% with C. Table 3 below contains estimation results of logit regression [8], using D82 as the dependent variable. On the left hand side of the table, regressors refer to the current year 1982 only; later on, the list of explanatory variables will be expanded to include utilization during the previous year. Age gradients and sex differentials very much conform to expectations. Here, discussion will focus on the crucial variables INSB and INSC, indicating membership of insurer B and insurer C, respectively (enrollees of A constitute the left-out category). Both coefficients are negative and highly significant at a confidence level of 0.001. Relative to members of insurance A, members of B are 9.4 percentage points less likely to have ambulatory care costs in excess of the joint threshold value defined above. This finding confirms conclusion 2. A similar result holds true for the insured of C, with the estimated impact amounting to 11.5 percentage points. This differential in favor of the experience-rated bonus offer is very much in accordance with the prediction of conclusion 3. An analogous estimation using data for 1981 (not shown) produces quite similar results, admitting of Short run impact of rebates and bonuses:

Conclusion 4: The predictions formulated in conclusions 2 and 3 concerning the incentives of the three policies examined are confirmed without ex-

283 Table 2 Explanatory

variables

Means Variable definition Al924 A3544 A4554 A5564 A6599 A1924F A2534F A3544F A4554F AS564F A6599F PRIVl

=l: =l: =l: =l: =l: =l: =l: 1: =l: =l: =l: = 1:

PRIV3

= 1:

INSB

= 1:

INSC

= 1:

D81A

=l:

D81B

=l:

D81C

=l:

Age between

19 and 24 years 35 44 45 54 55 64 Age above 65 years Females with A1924=1 A2534 -. A3544 A4554 A5564 A6599 hospital insurance: private room hospital insurance: common ward insured by B Rebate: 3 monthly premiums incl. ambulatory, hospital, dental care insured by C Bonus: 2,3, or 4 monthly pre miums (ambulatory care only) depending on damage experience insured by A and D81=1 (lagged dependent variable) insured by B and D81=1 (iagged dependent variable) insured by C and D81=1 (lagged dependent variable)

Subsample A B

c

*

0.04 0.33 0.12 0.06 0.05 0.02 0.13 0.09 0.04 0.02 0.03

0.03 0.40 0.19 0.08 0.02 0.01 0.07 0.09 0.06 0.03 0.01

0.03 0.27 0.27 0.18 0.15 0.01 0.03 0.09 0.09 0.07 0.10

0.03 0.33 0.20 0.11 0.08 0.01 0.07 0.09 0.06 0.04 0.05

0.31

0.18

0.31

0.27

0.20

0

0.04

0.08

0

0

0.31

0

1

0.38 0.11 0.09 0.10

* Total sample, used in the estimate shown on the left hand side of Table 3.

ception. Thus, the fixed rebate of insurer B and to an even greater degree the experience-rated bonus offer of insurer C reduce demand for ambulatory medical care at billing levels that lie above a conservatively determined submission threshold. This conclusion can be criticized on three major grounds. (1) It may be argued that members of insurance C have a planning horizon of less than two years. This would imply that the impact of the bonus is still intermingled with that of the deductible. However, in research using data of insurer B only, the effect of the deductible was found to fade out rather quickly with increasing values of the annual medical bill: a deductible of 300 DM (100 U.S. Dollars at 1985 exchange rates) does not appear to have any recognizable effect on

284 Table 3 Probability

for ambulatory

care costs to exceed the THRESHOLDS

defined in Table 1, 1982

Variable

Coefficient

r-Value

Coefficient

t-Value

Al924 A3544 A4554 A5564 A6599 A1924F A2534F A3544F A4554F A5564F A6599F PRIVl PRIV3 VERSB VERSC D81A D81B D81C

-0.171** 0.056** 0.078** 0.180*** 0.278*** 0.239** 0.163+** 0.115*** 0.073* 0.008 -0.029 0.066*** -0.074** -0.094*** -0.115*** _ _

-2.62 2.74 3.21 6.38 7.20 2.79 6.12 4.99 2.53 0.22 -0.70 4.81 -2.83 -5.71 -7.10 _ _ _

-0.074 0.034 0.029 0.082* 0.167*** 0.017 0.096** 0.069* 0.036 -0.020 -0.020 0.022 -0.098* -0.054* -0.097*** 0.380*** 0.396*** 0.458*** Chi2=966/df=18 N=4655/CONC=0.742

-0.86 1.39

Chi’=255/df= 15 N=5784/CONC=0.605

1.oo 2.41 3.41 0.14 2.80 2.49 1.03 -0.47 -0.36 1.36 -2.33 -2.06 -3.78 14.28 14.63 17.93

Intercepts not shown. Coefficients are estimated partial impacts on probability, derived from ing the parameters of a logit regression by p (1 -p). with p = average probability (=0.29. see and Ref. 9, pp. 166-178). *(**,*** ) denote 0.05 (0.01, 0.001) levels of statistical significance; to be interpreted asymptotically. df: degrees of freedom. N: number of observations. CONC: concordant pairs between predicted and actual probabilities.

multiplyTable 1, t-values share of

billings beyond a threshold of 1000 DM (330 U.S. Dollars). Among members of insurer A, a deductible of 250 DM (85 U.S. Dollars) was found to lose its impact beyond a threshold of as low as 350 DM (120 U.S. Dollars). These low threshold values should be compared with the submission threshold of no less than 1379 DM (460 U.S. Dollars) used here, cf. Table 1. Thus, at billings of 1000 DM and more, a deductible of 250 DM is very unlikely to have an impact of its own that would bias the estimate of the bonus effect. (2) Attempting to save one’s bonus or rebate might well jeopardize health in subsequent years. Recent research based on the Rand Health Insurance Study [lo] suggests an absence of such negative side effects. Moreover, the present study deals with ambulatory medical care only. As soon as hospitalization is envisaged, saving one’s rebate or bonus is out of the question as a rule. Nevertheless, some additional empirical evidence will be presented below concerning the occurrence of a tooth-saw pattern that would be consistent with too little ambulatory care in the first year, causing deterioration of health status and higher ambulatory care outlays in the second year. (3) Since privately insured can choose their insurer, good risks may conceivably select the insurance offering the largest bonus for a sequence of years with no claims. Conclusion 4 would then reflect not the impact of incentives contained in

285

different policies but merely the effects of self-selection. However, changing from one insurer to another entails a great deal of transaction costs, slowing down the process of self-selection. The plans analyzed in this paper were launched no more than five years prior to the observation period. Additionally, insurers offering plans that are strongly exposed to moral hazard protect themselves by requiring physical exams at entry. Nevertheless, the issue of self-selection is important enough to merit some further empirical investigation. Intermediate run aspects: Testing the validity of criticisms 2 and 3 in a comprehensive manner would require a period of observation of five years at least. Effects that are deferred by more than five years do not count much from an economic point of view because of discounting to present value. Unfortunately, only data for the years 1981 and 1982 are jointly available from the three participating insurers. The results presented in the sequel thus are no more than preliminary indications of effects expected to hold in the intermediate to long run. In a multi-period context, demand for medical care in the current year probably will contribute greatly to explaining medical care consumed in the following year and possibly in several following years. The reason for this correlation over time lies with important determinants of demand for medical services that do not enter insurance records. But the expected amount of correlation over time depends on the maintained hypothesis. In particular, if criticism No. 2 obtains, then members of insurance A should be least characterized by tooth-saw pattern outlays for medical care. Given full protection, they have no reason for spending too little on medical care today, causing higher expenditures tomorrow. In other words, correlation over time in outlays should be very marked among members of insurance A but less so in the case of insurers B and C, whose enrollees might be characterized by some degree of toothsaw pattern of utilization. This line of thought results in Conclusion

5: Intertemporal

stability of ambulatory medical care consumption should be highest among members of insurance A under the hypothesis that financial incentives cause negative side effects on health in the intermediate to long run.

Turning to the self-selection hypothesis advanced in criticism No. 3, there are two likely effects. Good risks would generally have ambulatory care outlays in excess of the high threshold defined in Table 1 only ‘by accident’. Such random events leave little traces in consecutive years. To the extent that good risks are attracted by an insurer offering large rebates and bonuses for no claims, great intertemporal stability should be observed for insurer A. On the other hand, rebates and bonuses may turn marginally bad risks into good ones, with bonuses creating the incentive of keeping them in that category (see Conclusion 4). In this case, individuals with ambulatory costs above the submission threshold should be rather bad risks. Hence, the preceding argument is reversed and the ordering of intertemporal stability is contrary to both the ordering under the self-selection hypothesis and the one stated in conclusion 5. These arguments can be summed up in

286

Conclusion 6: If self-selection

of risks is an important factor, then intertemporal stability must be greatest among members of insurance A, followed by insurers B and C. However, intertemporal stability should be highest for C if financial incentives transform marginally bad risks into permanently good ones.

The statements contained in conclusions 5 and 6 can be subjected to a preliminary empirical test by including an explanatory variable that indicates whether or not the medical bill of the previous year has exceeded the pertinent threshold value. These are the variables DSlA, D81B and D81C appearing in Table 3. The results are shown on the right hand side of Table 3. As could be expected, the three new regressors D81A, D81B and D81C are highly significant. But the coefficient pertaining to insurer A (DSlA) has a value of 0.380 only which is less than the one of D81C, amounting to 0.458. This clearly is incompatible with the prediction of conclusion 5 that a tooth-saw pattern holds among enrollees of insurers B and in particular C. Interestingly enough, the coefficient of D81B (0.396) is statistically indistinguishable from the coefficient of D81A (0.380), whereas the coefficient of D81C is highest (0.458). This is exactly what one would have predicted if bonuses have the power to transform marginally bad risks into permanently good ones. Summing up, there is justification for Conclusion

7: conclusion 5 fails to be confirmed empirically;

Concluding

at least in the intermediate run, neither insurers B nor C seem to be characterized by a tooth-saw pattern. Moreover, there is evidence in favor of an ‘educational impact’ of the dynamic bonus offer of insurer C, as stated in conclusion 6.

remarks

The starting point of this contribution is the fact that there is an alternative to the negative sanctions contained in conventional health insurance policies. This alternative takes the form of rebate options and experience-rated bonuses as offered by German private health insurers. From the consumer’s point of view, these new options may well be preferable to plans featuring deductibles and coinsurance (conclusion 1). At the same time, rebates and in particular bonuses are predicted to have a dampening impact on demand for ambulatory medical care (conclusion 2). Moreover, the experience-rated bonus is predicted to continually reduce demand even more than a roughly comparable rebate offer (conclusion 3). These predictions are subjected to empirical tests using insurance files from three German private health insurers for the years 1981 and 1982. Great care is taken to eliminate effects on accounted billings that merely reflect the insured’s decision not to submit a bill. Rather, estimated effects on the billings distribution should reflect modifications of behavior, as studied in the theoretical model. Those insured exposed to a rebate offer are found to exceed a threshold value of almost 1400 DM (465 U.S. Dollars) for ambulatory medical care with a lower likelihood than the

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insured having a conventional policy, with age, sex, and supplementary hospital insurance held constant. This dampening effect is even more pronounced among members of an insurance that offers an experience-rated bonus (conclusion 4). While seeking to save their rebate or bonus, insured might jeopardize their future health. Statistically, such behavior would give rise to a tooth-saw pattern in medical care cost (conclusion 5). On the other hand, these estimated impacts could be due to a mere self-selection of risks. Under this premise, insured having either a rebate or a bonus option should have a less stable pattern of utilization over time. Alternatively, a bonus might educate insured to become permanently good risks, resulting in very high intertemporal stability (conclusion 6). An analysis of billings over two consecutive years leads to rejection of the tooth-saw pattern and self-selection hypotheses while yielding some evidence in favor of an ‘educational effect’ of bonuses (conclusion 7). Thus these insurance options with their positive rather than negative economic incentives can be commended for their dampening impact on health care cost. In view of the notorious financing problems of almost all Western social health insurance schemes, experiences made by private insurers with their innovative plans may well be of relevance to social health insurance in countries such as Austria, Belgium, France, Germany, and the Netherlands. Since self-selection always plays a certain role in insurance markets where consumers have a choice, a conclusive comparison of plans in terms of their impact on medical care costs would require an experiment of the type of the health insurance study initiated by the Rand Corporation [ 111. Ever since Beck’s [12] study of the effects of cost-sharing on the poor, the notion that copayment may restrain demand for medical care much more at lower than at higher income levels has been a major concern to policy makers. Although this study is based on a high income segment of the population, the stability of estimated relationships was investigated by dividing the samples of insurers A and B into three broad socio-economic groups [13]. Coinsurance rates, deductibles, and rebates all turned out to have minimum effect on utilization among enrollees of the uppermost group and maximum effect in the lowest group, which is still very much middle class, of course. However, rebates and bonuses are defined relative to an insurance premium, and to the extent that lower income groups buy less insurance, financial incentives for refraining from medical care consumption are scaled down along with income, which is not true of deductibles and coinsurance rates. Moreover, these effects are small compared to primary determinants of demand for medical care such as age and sex. In conclusion, these innovations in health insurance merit serious attention in the debate about future reforms of social health insurance.

Acknowledgments The author would like to thank Friedrich Breyer (Heidelberg) and Wienand van de Ven (Rotterdam) for helpful criticism and Otto Waser (Zurich) for the key suggestion for overcoming it, as well as expert computational assistance.

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