HE380 Managed Healthcare Assignment 8 (Partial question)

O R I G I N A L P A P E R

What do physicians dislike about managed care? Evidence from a choice experiment

Maurus Rischatsch • Peter Zweifel

Received: 10 October 2011 / Accepted: 21 May 2012 / Published online: 21 June 2012

� Springer-Verlag 2012

Abstract Managed care (MC) imposes restrictions on

physician behavior, but also holds promises, especially in

terms of cost savings and improvements in treatment

quality. This contribution reports on private-practice phy-

sicians’ willingness to accept (WTA, compensation asked,

respectively) for several MC features. In 2011, 1,088 Swiss

ambulatory care physicians participated in a discrete choice

experiment, which permits putting WTA values on MC

attributes. With the exception of shared decision making

and up to six quality circle meetings per year, all attributes

are associated with non-zero WTA values. Thus, health

insurers must be able to achieve substantial savings in

order to create sufficient incentives for Swiss physicians to

participate voluntarily in MC plans.

Keywords Managed care � Physician preferences � Willingness-to-accept values � Discrete choice experiment

JEL Classification C93 � D61 � I11 � J22

Introduction

Many governments try to limit the rise in health care

expenditure by prescribing or encouraging managed care

(MC) programs. Promoting MC is one alternative to tackle

expenditure; the other usually is increased copayments

(Trottmann et al. [40] for a discussion of cost sharing in

deregulated social health insurance). The term MC

encompasses very different institutional arrangements, and

its complexity does not allow one single broadly accepted

definition (see Glied [11]). The present study uses the

expression MC to describe the nature of the contract

between ambulatory care physicians playing the role of

health-care providers and health insurers as payers of care.

In this case, MC contracts are defined by their specific

obligations included in the contract, e.g., mandatory par-

ticipation in quality circles (see ‘‘Study design’’ section). In

mixed systems permitting choice, consumer participation

in MC can be encouraged by lowered contributions to

health insurance (for evidence about the reduction required

to induce voluntary participation by consumers, see e.g.

Zweifel et al. [44]). However, health service providers

must also be won over to MC to avoid quality problems, in

particular due to a lack of participating physicians. For

instance, expansion of MC plans in the US has been

hampered by difficulties in recruiting service providers. In

Germany, the creation of so-called Integrated Care centers

has been slow for the same reason. These difficulties are

compounded in countries with a shortage notably of gen-

eral practitioners (GPs), who play a crucial role in MC as

gatekeepers. In the case of Switzerland, only about 10 % of

medical students intend to become GPs, while retiring GPs

have difficulties finding a successor for their practice [4].

Hence, health-care reforms designed to foster MC need to

address the issue of sufficient attractiveness of MC practice

particularly to general practitioners.

Incentives for providers to participate in MC programs

are mixed. On the one hand, they have to accept limitations

of their professional autonomy, and possibly increased

financial risk (especially if they participate in the financial

success of the scheme). On the other hand, they can benefit

from regular work hours, shared investment costs, and

easier exchange of information within a network. This

article purports to provide information about physicians’

M. Rischatsch (&) � P. Zweifel Department of Economics, University of Zurich,

Hottingerstrasse 10, 8032 Zurich, Switzerland

e-mail: [email protected]

123

Eur J Health Econ (2013) 14:601–613

DOI 10.1007/s10198-012-0405-8

preferences, expressed as their compensation asked (will-

ingness to accept, WTA) for departing from their con-

ventional job characteristics without MC obligations. The

evidence comes from a stated preference experiment of the

discrete-choice type (DCE), performed with 1,088 Swiss

private-practice physicians working in ambulatory care in

2011. The majority of respondents work in independent

private practice while participating voluntarily in some MC

schemes, which however account for a small share of their

patients (see ‘‘Data’’ section). While evidence based on

actual behavior would be preferable in principle, market

experiments can inform policy makers and health insurers

about the chances of success of planned changes, helping

them avoid costly failures.

This article is organized as follows. The ‘‘Literature

review’’ section contains an overview of the existing lit-

erature on physicians’ preferences, with special reference

to evidence from DCEs. The theoretical background to

understand DCEs and the methods to derive WTA values

are given in the ‘‘Methods’’ section. The ‘‘Study design’’

section outlines the study design and discusses the MC

attributes of interest. The ‘‘Data’’ section describes the

data. The estimation results are discussed in the ‘‘Estima-

tion results’’ section, and conclusions are drawn in the

‘‘Conclusions’’ section.

Literature review

The existing literature on physician behavior mainly

revolves around the impacts of different reimbursement

systems [18, 25, 27]. The precise nature of physician

preferences usually is not addressed because they do not

seem to affect predictions in a substantial way. Some

authors have nevertheless posited particular preferences by

including professional ethics, which in principle should

motivate physicians to hail MC treatment concepts such as

shared decision making (SDM) and critical incident

reporting (CIR) [7, 9, 43]. Attributes of professional

activity originally received little attention, except for the

rate of return associated with specialization [38]. More

recently, Gagne and Leger [10] have examined the choice

of specialty in Canada from 1976 to 1991 in response

to changes in fee-for-service rates. They find income

differences to be a significant factor. However, gender,

mother tongue, medical school attended, state laws, and

geographic conditions have a bearing on the choice of

specialty as well. With the spread of MC, research into the

determinants of choice of type of medical practice received

new impetus. Hypothesized attributes are reputation and

status [8, 29], properties of the medical practice [1], and

intellectual satisfaction [8, 9]. Kristiansen [15] has claimed

professional autonomy to be an additional attribute that

needs to be taken into consideration. However, the rele-

vance of these attributes, especially the non-pecuniary

ones, has been little investigated.

Against the background of undersupply in rural areas of

Norway, Kristiansen [16] analyzed the determinants of the

decision where to locate. Place of birth, place of residency,

and spouse’s place of origin were found to be significant

factors. However, they are not of overriding importance,

causing the author to conclude that the problem of under-

provision could be solved through the use of financial

incentives. In addition, non-pecuniary motives might be

enhanced in order to relieve the public budget, e.g. by

favoring medical students with a rural background (who

are particularly likely to settle there). The same conclusion

is drawn by Benarroch and Hugh [2], who investigate the

migration of physicians in Canada. Urbanization has a

significantly positive effect on migration, whereas distance

between major cities of a province has a significantly

negative effect. While this research is valuable for

informing policy makers about what motivates physicians

to opt for existing alternatives, it is silent about their

choices with regard to alternatives that are being consid-

ered but not available yet. In this situation, surveys and

market experiments can fill the gap.

The effects of non-pecuniary job characteristics on

physicians’ labor supply decisions have mainly been sur-

veyed in the psychological and medical literature [36].

Buddeberg-Fischer and Klaghöfer [3] examine career paths

of 497 last-year medical students over a period of 8 years in

Switzerland. Respondents described versatility of the field

(96 %), intensive patient contact (87 %), positive experi-

ences during their studies (86 %), compatibility of work

with family (83 %), and possibilities of self-employment

(61 %) as determinants of their choice of specialty. In

addition, male students exhibit a preference for specialties

with a scientific orientation, whereas females, for settings

with intensive patient contacts. With regard specifically to

MC alternatives, Nordt [26] find that conflicts due to a

changed perception of the physician’s professional role put

more strain on practitioners in solo than in group practice.

Similarly, incompatibility of work and family may be more

of a problem in solo practice (2.8 out of a maximum of

5 points) than in group practice (2.3 points, difference not

statistically significant).

Market experiments of the discrete-choice type (see

‘‘Study design’’ section below) have been performed by

Scott [35] to investigate the preferences of practitioners in

the UK with regard to working hours, work load, time

spent on administration per week, out-of-hours appoint-

ments, and use of guidelines. Performing a DCE as well,

Ubach et al. [41] report WTA values for an extra working

hour per week and on being on call an extra day per month.

Wordsworth et al. [42] find differences between principal

602 M. Rischatsch, P. Zweifel

123

and so-called sessional GPs. 1

On the whole, the evidence is

in accordance with the theoretical predictions by Marinoso

and Jelovac [22], who compare the performance of gate-

keeping and traditional settings, emphasizing the impor-

tance of non-financial motives for the payment of GPs to

create favorable incentives.

While this research is valuable for pointing to job

attributes that may be particularly valued (or resisted) by

physicians, it fails to inform about their attitudes with

regard to non-marginal changes. However, the transition

from conventional independent private practices to con-

tractual obligations with insurers constitutes such a non-

marginal change. Policy makers considering increasing

the market share of MC through regulation as currently

discussed in Switzerland need to know how much it takes

to win physicians over.

Methods

Based on random utility theory [20, 21, 23, 24], discrete

choice experiments (DCEs) are designed to allow indi-

viduals to express their preferences for non-marketed

goods or goods that do not yet exist. The number of

applications of DCEs to the valuation of health-care pro-

grams has been increasing during the past few years

[13, 33, 34]. For a review of the literature on discrete

choice experiments in health economics, see [5]. In a DCE,

individuals are given a hypothetical choice between many

or just two (binary choice) commodities. From these

choices, the importance (more precisely, the expected

utility) of product characteristics can be inferred. Inclusion

of a cost or price attribute allows determining the valuation

of the remaining product attributes in terms of money. In

the present context, the price attribute is an extra payment

per insured and month. The fact that respondents have to

weigh several attributes simultaneously makes biases that

plague contingent valuation (where individuals are asked

about their willingness to pay directly, holding all other

attributes constant) less likely than in a DCE [32].

The first step of a DCE involves the definition of the

attributes of the commodity and the levels assigned to them

[19, 33]. Here, attributes of MC are chosen to describe the

physicians’ work situation (for more details, see ‘‘Study

design’’). When comparing hypothetical alternative MC

contracts, a rational subject will choose the alternative

with the higher level of utility. The decision-making pro-

cess in a DCE can be seen as a comparison of utilities

Uni ¼ Vni þ eni and Unj ¼ Vnj þ enj; where Vni represents

the deterministic indirect utility of individual n from

alternative i, and eni denotes the pertaining unobserved error term. Thus, individual n chooses alternative i (MC)

rather than alternative j (conventional practice) if (and

only if) Uni [ Unj, which implies Vni þ eni [ Vnj þ enj so that Pni ¼ Prðenj � eni\Vni � Vnj; 8j 6¼ iÞ. Therefore, the probability of choosing i rather than j implies that the error

term is dominated by the systematic difference in utility.

In this study, physicians’ preferences are estimated with

the aid of a random-coefficient logit model (RCM) esti-

mated by simulated maximum likelihood. The RCM has

three important advantages over the standard logit model. 2

First, it allows for random taste variation across physicians.

Second, the RCM model permits unrestricted substitution

patterns. 3

Third, it allows for correlation of unobserved

factors over time. The choice probabilities for the RCM are

given by

Pni ¼ Z YT

t¼1

eb 0 xnit

PJ j¼1 e

b0xnjt fðbjhÞdb; ð1Þ

where the logit probability is called the mixed function and

f(b|h) the mixing distribution with distribution parameters h (see Train [39], Chap. 6). Subscript n identifies the physi-

cian and i the MC alternative at choice situation t. Prefer-

ence heterogeneity is reflected by the mixing distribution

f(b|h), which is usually assumed to be normal or log-nor- mal. The log-normal distribution serves to model a strictly

positive or negative preference, e.g., for the price attribute.

However, in practice the log-normal distribution may cause

problems for different reasons (see ‘‘Estimation results’’).

Therefore, applied researchers often keep the price attribute

fixed. The choice of adequate mixing distributions is

important and discussed in the ‘‘Estimation results’’ section.

The mixing distributions reflect unconditioned or pop-

ulation preferences. If no choices were observed, one

would only know that the coefficients follow f(b|h). In contrast, observed choices allow conditioning the distri-

butions of b on the choices (y), permitting the derivation of conditional or physician-specific distributions h(b|yn, xn, h) of b (see Train [39], Chap. 11). By the Bayes theorem,

hðbjyn; xn; hÞ¼ Pðynjb; xnÞ � fðbjhÞR Pðynjb; xnÞ � fðbjhÞdb

/ Pðynjb; xnÞ � fðbjhÞ; ð2Þ

where the denominator is the normalizing constant.

P(yn|b, xn) is the probability of physician’s observed choice

1 Principal GPs have ownerships in their practice, whereas sessional

GPs are freelancers (mainly young females with childcare responsi-

bilities) and employees of NHS boards (Scotland).

2 The RCM (or mixed logit) model is a generalization of the standard

logit model. The RCM reduces to the standard model if density

f(b) = 1 for b = b and 0 for b = b. Further, the random-intercept logit model (RIM, also called random-effects model) treats the

constant as normally distributed with all other coefficients kept fixed. 3

This is irrelevant to this study, which is of the binary choice type.

What do physicians dislike about managed care? 603

123

sequence yn given b and the attribute levels of the chosen alternatives xn. Hence, all quantities are known to derive

h(b|yn, xn, h) and to calculate moments of physician- specific coefficients. Means can be simulated as

weighted averages �b ¼ P

r w rbr; with wr = P(yn|b

r , xn)/P

r P(yn|b r , xn) where b

r is a draw from f(b|h).

Study design

In this section, we present attributes related to physicians’

professional activity that distinguish MC from conven-

tional practice. Specifically, we analyze preferences for

different forms of treatment concepts, critical incident

reporting, quality circles, preferred provider lists, and

generic drug lists.

The attribute ‘treatment concepts’ has two levels. First,

shared decision making (SDM) requires that patients are

more strongly involved in the decision-making process

concerning the choice of treatment. SDM is widely applied

in practice (especially encouraged by MC networks) in

Switzerland, at least compared to other countries [6]. It is

recommended in the medical literature as a way to make

the physician a more perfect agent of the patient. An

additional benefit of SDM from the point of view of a risk-

averse physician is to shift the burden of proof in a

malpractice suit to the (now informed) patient; however,

liability suits against physicians are extremely rare in

Switzerland. The downside of SDM is a certain curtailment

of professional autonomy. Therefore, the valuation of SDM

can go either way (see Table 1). The second level is

adherence to treatment guidelines (GL), to be developed by

physicians and accepted by insurers. They define how to

proceed in the case of certain medical interventions.

Guidelines are typical of MC; they are little known in

Switzerland. They entail a strong limitation of professional

autonomy combined with extra administrative work. They

do shift the burden of proof in a malpractice suit to the

insurer or agency (health administration) issuing them.

In view of the very low likelihood of this event, GL is

expected to have a positive WTA (compensation required).

Critical incident reporting (CIR) obliges physicians to

anonymously report critical incidents that happened in their

practice. On the one hand, CIR calls for extra time and

effort, and may give rise to fears of being interpreted as a

confession of malpractice. On the other hand, CIR holds

the promise of quality improvement in the treatment pro-

vided. Hence, the valuation of CIR can go either way (see

Table 1).

The third attribute is the obligation to attend so-called

quality circles (QC), another feature of MC. In QC, phy-

sicians meet on a regular basis to discuss new treatments

and interventions as well as experiences made. This benefit

to participating physicians has to be balanced against the

sacrifice of time. Interviews with physician networks

indicated that many of their members like to participate

in QC provided they take place during lunches and are

accompanied by presentations by fellow members or spe-

cialists. On the whole, no clear prediction about the

expected sign of WTA can be made.

The fourth attribute is the preferred provider list (PPL),

which restricts referrals to specialists and hospitals to

providers selected by the MC organization. This restriction

is expected to be undesired by most physicians. However,

some of them may support PPL because they believe in the

ability of the MC organization to identify providers offer-

ing high quality and/or high cost-efficiency.

Fifth, mandatory prescription of generic drugs if avail-

able (GEN) is imposed by most MC organizations in

Switzerland. Physicians may perceive GEN as a good

instrument for tackling rising drug expenditures; on the

other hand, it does restrict their choice of pharmaceutical

treatment. Therefore, preferences could go either way.

The sixth attribute represents the price attribute in the

DCE. It is measured as a payment (PAY) over and above

current income per MC-insured person per month (IPM).

To be in line with microeconomic theory, all physicians

should positively value PAY.

Table 1 Attributes and attribute levels in the DCE

Attribute Attribute levels

No contractual obligation to adhere to any item below versus

Treatment concepts Shared decision making: yes/no (SDM, ±), guidelines: yes/no (GL, ±)

Critical incident reporting Mandatory anonymous reporting: yes/no (CIR, ±)

Quality circles a

Mandatory meetings per year: 0/3/6/12 (QC, ±)

Preferred provider list Referrals only to listed providers: yes/no (PPL, ±)

Generic drug list Restricted to prescribe generics if available: yes/no (GEN, ±)

Payment Payment of CHF 0.00/0.50/1.00/1.50/2.00 per insured and month (PAY, ?)

a Quality circles are defined to the last 1.5 h per meeting. The signs after the abbreviations in parentheses indicate our expectations about

physician preferences

604 M. Rischatsch, P. Zweifel

123

An example of a choice scenario is shown Table 2.

‘Independent without obligations’ defines the status quo of

conventional practice, an option available to all Swiss

physicians. In fact, only 13 % of respondents report to be

in MC practice (see ‘‘Data’’).

In Eq. (3) below, the attribute levels for treatment

concepts (SDM, GL), critical incident reporting (CIR),

preferred provider list (PPL), and generic drug list (GEN)

are coded as dummy variables. Because SDM and GL are

levels of one attribute, they never appear together in an

alternative. Quality circles (QC) have levels of 0, 3, 6, and

12 (meetings per year). Coding them as three categorical

variables (QC3, QC6, and QC12) has the advantage of not

imposing a specific functional form such as the linear or

quadratic. Finally, PAY denotes the payment a physician

receives in return for accepting MC-type obligations,

ranging from zero to CHF 2.00 per insured and month

(IPM). With an enrolment of 600 (say), this maximum

corresponds to about 8 % of the median monthly income

[17]. Therefore, the deterministic part of the random utility

can be written as

b0x ¼ b1SDM þ b2GL þ b3CIR þ b4QC3 þ b5QC6 þ b6QC12 þ b7PPL þ b8GEN þ b9PAY þ b10CONST; ð3Þ

where the bs are the taste parameters of interest to be estimated.

The total of six attributes and their levels combine to

form 480 possible combinations of alternative MC con-

tracts. Using JMP to optimize the experimental design, this

number was reduced to 40 D-optimal choice scenarios and

randomly split into four groups, resulting in 10 choice

situations per respondent. Each of the ten hypothetical MC

contracts had to be evaluated against the reference case

with no obligations imposed.

Data

The Swiss Medical Association (FMH) supported carrying

out the discrete choice experiment (DCE) by including a

link to the web-survey in a newsletter addressed to all

members in private practice. In July 2011, a pretest

involved a randomly selected sample of 1,000 FMH

members. Respondents had the opportunity to write com-

ments, which indicated a good understanding of the survey.

Respondents were randomly selected considering eco-

nomic and demographic characteristics to represent the

ambulatory care physician community in Switzerland. The

main survey was fielded in August 2011 with a return rate

of 11 % , resulting in 10,461 observed choices by 1,088

physicians. This rate of response coincided with our

expectations and previous experience with surveys

addressed to physicians. A high share of 87 % completed

all ten choice scenarios, with 9.6 the average number of

choices made per respondent. The share of respondents

always choosing no obligations was 29 %, while 1 % of

physicians agreed to sign up to all MC alternatives pre-

sented. In addition to the DCE, the survey included ques-

tions about general attitudes concerning experience with

MC, education, and other demographic variables.

The statistics compiled in Table 3 indicate that average

age is a high 54 years (the same as the national figure, see

Kraft [14]). With 26 years of experience, participants are

somewhat past their halftime in independent practice on

average. Accounting for 19 % of the sample, women are

underrepresented in the sample compared to their overall

share of 32 % in the medical profession [14]. The fact that

relatively fewer female physicians participated in the study

again coincides with previous survey experience by the

Swiss Medical Association, regardless of topic. About

77 % of sampled physicians are married (5 % are single, 9

divorced) and have on average 1.65 children under

18 years. Some 52 % have their practice in an urban

environment, while 25 % are located in suburban and 23 %

in rural areas, respectively. The majority of respondents are

from the German-speaking northern and eastern parts of

Switzerland (73 %), while 24 % are from the French-

speaking western and the remaining 3 % from the Italian-

speaking southern parts.

Approximately 45 % of sampled physicians are general

practitioners (including gynecologists and pediatricians),

while 13 % are specialists without surgical and 13 % with

surgical activity. Psychiatrists constitute 16 % of the

sample, while the remainder declared themselves to belong

Table 2 Example of choice scenario

Attribute Obligation

You are to base treatment decisions on shared

decision making

Yes

You obligate yourself to anonymously report

critical incidents

Yes

Number of quality circles you agree to attend per

year

6 (1.5 h each)

You accept a preferred provider list for referrals Yes

You prescribe exclusively generics if available No

You receive payment of CHF 1.50/IPM a

I am willing to sign the MC contract with these

obligations

h

I would like to remain independent without

obligations

h

a Payment is in CHF per insured per month (IPM). 1 CHF &

1.1 USD at 2011 exchange rates

What do physicians dislike about managed care? 605

123

to other groups or failed to state their specialty. Most

physicians work in single practice on their own account

(51 %), which means that their income or profit depends on

their own services. Approximately a third (30 %, not

shown in Table 3) work in shared or group practices but

bill their services individually. This is in contrast to shared

practices with a common account, which bill regardless of

who in the practice actually provided the services. These

shared practices with so-called common accounting are

rare (5 %). The MC setting is predominantly characterized

by networks where members continue to work on their own

account (12 % of respondents); common-account networks

are the exception (1 %). Among physicians in shared

practice, 61 % work in a team of two, 24 % in a team of

three, and 8 % in a team of four physicians. Maximum

team size reported is a low nine physicians.

In the attitudinal part of the survey, participants were

asked about their experiences with MC. This information is

used in the ‘‘Effects of prior experience’’ section to explore

experience-related differences in WTA values with respect

to MC attributes. Concerning treatment concepts, 57 %

have experience with shared decision making and 51 %

with treatment guidelines. About 27 % of sampled physi-

cians collected experience with critical incident reporting.

Quality circles are the most prominent MC feature, with 60

physicians having attended meetings at least once. As to

the most restrictive MC features, only 14 % stated expe-

rience with preferred provider lists and 27 % with generic

drug lists.

Estimation results

Table 4 shows the estimated distribution parameters for

two different model specifications. Both are estimated by

simulated maximum likelihood using 500 Halton draws

[12]. The left panel of Table 4 pertains to the random-

intercept model (RIM) specification, where all coefficients

are kept fixed with the exception of the constant, for which

a normal distribution is assumed. The constant captures

unobserved physician-specific effects. The right panel

displays the parameters pertaining to the random-coeffi-

cient model (RCM), where all coefficients are assumed to

be normally distributed (reflecting the theoretical expec-

tations listed in Table 1), with the exception of a fixed

coefficient for PAY. Revelt and Train [28] give three

reasons for keeping the price attribute fixed. First, it

facilitates the calculation of population WTA values.

Second, RCM estimates tend to be unstable when all

coefficients are random [31]. Third, the appropriate choice

of mixing distribution for the price attribute is not

straightforward. The most frequently applied log-normal

distribution does often not converge in practice. Further, it

renders estimates of the price coefficient that are very close

to zero, causing implausibly high WTA values [37].

Therefore, the WTA values (see Fig. 1 of the ‘‘Willingness

to accept MC-type obligations’’ section) capture only

preference heterogeneity from the MC attributes but no

heterogeneity with respect to PAY, and hence marginal

utility of income (which may be substantial in view of the

dispersion of medical income documented by Künzi et al.

[17]).

The simulated log-likelihood (SLL) values at conver-

gence are -4,549.7 (RIM) and -4,261.0 (RCM), while the

AICs are 9,121.3 (RIM) and 8,559.9 (RCM), respectively.

Therefore, goodness of fit speaks in favor of RCM esti-

mates, which are emphasized in the discussion below.

Table 4 shows estimated mean and standard deviation

parameters along with their standard errors (SE). The mean

parameters are insignificant for CIR (RIM) and six meet-

ings per year for both specifications. All remaining

parameters are highly significant with a p value below 0.01.

Table 3 Respondent descriptives, Swiss ambulatory

care physicians (2011)

General practitioners include

gynecologists and pediatricians.

Statistics are mean (MN),

standard deviation (SD), and

median (MD)

Variable MN SD

Percentiles

5th MD 95th

Age of physician 53.73 8.25 40.00 54.00 66.00

Job experience (in years) 26.00 9.74 11.00 27.00 39.00

Male respondents 0.81 – – – –

Married 0.77 – – – –

Number of children under 18 1.65 1.70 0.00 2.00 4.00

Urban practices 0.52 – – – –

Suburban practices 0.24 – – – –

Rural practices 0.23 – – – –

General practitioners 0.45 – – – –

Specialists without surgery 0.13 – – – –

Specialists with surgery 0.13 – – – –

Psychiatrists 0.16 – – – –

606 M. Rischatsch, P. Zweifel

123

Share of physicians who dislike MC

The estimated parameters for the population distributions

can be used to calculate population shares of physicians

with negative preferences for MC. For attribute k, this

share is given by Pðbk\0Þ¼ Uð�MNk=SDkÞ; where U is the cumulative normal distribution, and MNk and SDk are

the estimated mean and standard deviation, as given in

Table 4. An alternative approach is to calculate the share of

negative physician-specific coefficients using Eq. (2),

which has the advantage of conditioning on individual

choices observed. Therefore, the conditioned shares are

discussed below, while the unconditioned shares are shown

in parentheses.

Regarding MC-type treatment concepts, only 9 (31) %

of physicians have a distaste for shared decision making,

while no less than 86 (73) % dislike guidelines. Similarly,

the share of physicians opposing critical incident reporting

attains 93 (70) %. Almost all physicians (1 % rejecting)

like to attend three quality circles per year. However,

acceptance already decreases for six meetings per year,

with 38 (45) % against. Finally, a full 92 (79) % dislike to

be obliged to participate in 12 meetings per year. In sum,

about one-half of sampled physicians are willing to

participate in up to six quality circles without being com-

pensated. The MC attribute with the highest share of

opposing physicians is the preferred provider list with 94

(88) %. Restricting drug prescriptions to generics if

available is still refused by 88 (79) %. These findings

suggest that with the exception of shared decision making

and up to six quality circle meetings per year, all MC-type

attributes have to be compensated if a majority of Swiss

physicians are to be won over to MC.

Willingness to accept MC-type obligations

Next, we focus on the physician-specific willingness-to-

accept (WTA) values for MC attributes, shown in Table 5.

The discussion concentrates on the median values from the

RCM because they are more robust to outliers than the

mean values.

The negative WTA value for SDM indicates that the

median Swiss physician need not to be compensated for

involving patients in the decision making about choice of

treatment. In contrast, following guidelines has to be

compensated with about 3.57 CHF per MC-insured per

month (CHF/IPM). Critical incident reporting was shown

to have a small, insignificant effect on the choice prob-

abilities (Table 4). This is reflected by a WTA value of

only 0.34 CHF/IPM; this low value likely reflects physi-

cians’ belief that CIR contributes to an increase in treat-

ment quality. Quality circles are positively valued up to

six meetings per year by the median respondent. Hence,

including up to six quality circles in a MC contract allows

Table 4 Preferences for managed care attributes—

regression results

a Number of physicians: 1,088;

number of choices observed:

10,461. Coefficients for RCM

are all assumed to be normally

distributed, with the exception

of a fixed coefficient for PAY

Attribute Parameter

Random- intercept model

(RIM)

Random-coefficient model

(RCM)

Value SE Value S.E.

Shared decision making (SDM) Mean 0.38 (0.07) 0.48 (0.09)

SD 0.95 (0.16)

Guidelines (GL) Mean -0.66 (0.09) -1.49 (0.19)

SD 2.43 (0.26)

Critical incident reporting (CIR) Mean -0.06 (0.06) -0.16 (0.09)

SD 0.31 (0.16)

Three quality circles (QC3) Mean 0.33 (0.09) 0.30 (0.11)

SD 0.10 (0.22)

Six quality circles (QC6) Mean 0.04 (0.09) 0.10 (0.11)

SD 0.79 (0.18)

Twelve quality circles (QC12) Mean -0.91 (0.10) -1.66 (0.18)

SD 2.09 (0.20)

Preferred provider list (PPL) Mean -1.42 (0.07) -2.28 (0.13)

SD 1.95 (0.14)

Generic drug list (GEN) Mean -0.89 (0.07) -1.66 (0.12)

SD 2.09 (0.15)

Payment (PAY) a

Mean 0.37 (0.05) 0.49 (0.06)

SD

Constant (CONST) Mean -0.73 (0.13) -0.64 (0.16)

SD 1.79 (0.07) 1.86 (0.11)

What do physicians dislike about managed care? 607

123

reducing the overall compensation required. Nevertheless,

this reduction is too low to play a crucial role in attracting

physicians to participate in MC. In addition, 12 meetings

already have to be compensated at the tune of 3.71 CHF/

IPM. Restricting referrals to providers listed by insurers

is strongly opposed and requires the highest compensa-

tion of all MC-type attributes. Its median WTA is 5.27

CHF/IPM. The next-highest WTA value pertains to the

restriction to prescribe only generics if available (GEN),

with 4.06 CHF/IPM. A likely reason for this high figure is

the fact that about one-half of Swiss physicians live in

jurisdictions permitting them to dispense drugs on their

own account [30]. Therefore, the GEN attribute entails the

loss of an option to generate extra income for many

respondents.

In view of the entries of Table 5, the question arises of

whether current extra payments by insurers suffice to win

physicians over to MC. A typical value is 1.50 CHF/IPM

for participating in a health maintenance organization

(HMO), the most restrictive MC variant (preferred provider

organizations and gatekeeping networks also exist in

Switzerland). Clearly, this extra payment falls far short of

what it takes to make the median Swiss physician join an

HMO. To the extent that it reflects achievable cost savings

due to MC, these savings could easily be insufficient for

MC to increase its current market share.

Because the coefficient of PAY is kept fixed, the WTA

values have the same distributions as the random coeffi-

cients for the MC attributes. The histograms of Fig. 1 point

to substantial heterogeneity of preferences, especially with

0 .2

.4 .6

.8

−4 −3 −2 −1 0 1

SDM

0 .1

.2 .3

.4

−5 0 5 10

GL

0 1

2 3

−.5 0 .5 1

CIR 0

.2 .4

.6 .8

−2 −1 0 1 2

QC=6

0 .1

.2 .3

−5 0 5 10

PPL

0 .0

5 .1

.1 5

.2

−5 0 5 10

GEN

Fig. 1 Histograms of physician-specific WTA values

Table 5 Willingness to accept MC-type obligations

WTA values (mean denoted by

MN and median by MD) are

shown in CHF per insured and

month (CHF/IPM) using

physician-specific coefficients;

1 CHF & 1.1 USD at 2011 exchange rates

Attribute Abbrev. RIM RCM

MN MD Percentiles

MN 5th 95th

Shared decision making SDM -1.03 -1.00 -0.86 -2.56 0.31

Guidelines GL 1.80 3.05 3.57 -2.31 6.53

Critical incident reporting CIR 0.17 0.33 0.34 -0.10 0.66

Three quality circles QC3 -0.89 -0.61 -0.61 -0.73 -0.50

Six quality circles QC6 -0.11 -0.21 -0.17 -1.53 0.90

Twelve quality circles QC12 2.46 3.46 3.71 -0.83 6.67

Preferred provider list PPL 3.87 4.70 5.27 -0.18 8.15

Generic drug list GEN 2.43 3.53 4.06 -1.54 7.40

608 M. Rischatsch, P. Zweifel

123

regard to GL, PPL, and GEN. Opinions appear to be

strongly divided concerning GL and GEN in particular,

where bi-modality is evident. In the case of GEN, this

likely reflects the divide between physicians who dispense

drugs on their own account and those who do not.

Effects of prior experience

The preference patterns and WTA values found in the

previous section do not distinguish between different

groups of physicians. This section is devoted to the ques-

tion of whether prior experience with a MC setting makes a

difference; differences between general practitioners and

specialists are discussed in the next section.

To test for differences between physicians with and

without MC experience, all attributes are interacted with a

dummy indicating whether respondents declared have

made experience with this specific MC attribute. Table 8 of

the ‘‘Appendix’’ (left-hand side) shows the estimated dis-

tribution parameters for the RCM containing this type of

interaction. The physician-specific WTA values estimated

for physicians with and without experience with the per-

tinent MC attribute are displayed in Table 6. In general,

physicians with experience have lower WTA values,

indicating less resistance against or even a preference for

the MC feature. There are two reasons for this effect. First,

physicians may like MC because of their favorable expe-

rience. Second, however, self-selection may be at work.

Physicians with a preference for MC are likely to have

selected this setting, causing them to have prior MC

experience. As will be argued below, disentangling the two

directions of causality is not worthwhile in the present

policy context.

The discussion is limited to the most salient differences.

They concern SDM, PPL, and GEN. First, physicians

stating that they have never had experience with SDM

dislike involving patients in the decision-making process.

They ask for a median compensation of 0.72 CHF/IPM for

SDM. In contrast, physicians with experience in SDM have

a positive preference for it and do not have to be com-

pensated. Second, physicians who have worked with a

preferred provider list (PPL) exhibit a median WTA value

of 2.98 CHF/IPM, less than one-half of that characterizing

their colleagues without that experience (6.30 CHF/IPM).

Third, restricting drug prescription to generics has a med-

ian WTA of 3.72 CHF/IPM among physicians who have

applied such a list, compared to 5.52 CHF/IPM for those

who have not.

While it would be of scientific interest to distinguish the

effect of prior experience from a possible self-selection

effect, for policy makers attempting to increase the market

share of MC, this is a moot point. They need to win over

physicians without prior MC experience. This means that

the achievable cost savings must suffice to finance the

higher compensations requested by this group—letting

alone the compensation asked by Swiss consumers as

estimated by another DCE [44].

Differences between GPs and specialists

In the survey, physicians were asked to state if they are

general practitioners (GPs, including gynecologists and

pediatricians), specialists with and without surgical activ-

ities, or psychiatrists. Because GPs play a crucial role in

MC as gatekeepers for their patients, this section compares

their preferences with those of their specialized colleagues

who are grouped together as ‘specialists.’ The same RCM

is estimated as in the ‘‘Estimation results’’ section, but this

time with MC attributes that interacted with a dummy

variable, indicating whether the respondent is a specialist

Table 6 Willingness-to-accept values by experience

Attribute Physicians without experience Physicians with experience

MN MD Percentiles MN MD Percentiles

5th 95th 5th 95th

Shared decision making 0.52 0.72 -1.40 2.25 -2.28 -2.09 -4.44 -0.40

Guidelines 3.80 3.85 1.46 5.55 0.89 1.22 -2.55 3.19

Critical incident reporting 0.72 0.75 0.13 1.20 -0.35 -0.34 -1.54 0.90

Three quality circles 0.37 0.37 0.30 0.44 -1.32 -1.32 -1.59 -1.04

Six quality circles 1.59 1.59 1.54 1.62 -1.39 -1.39 -1.44 -1.33

Twelve quality circles 5.08 5.18 1.95 7.45 2.95 3.05 -1.41 6.57

Preferred provider list 5.61 6.30 -0.37 9.38 2.78 2.98 -2.94 7.46

Generic drug list 4.64 5.52 -2.18 9.15 3.48 3.72 -2.24 8.69

WTA values are shown in CHF per insured per month, IPM using physician-specific WTA values from RCM, containing interactions.

‘Experience’ refers to the particular MC attributes listed

What do physicians dislike about managed care? 609

123

or not. In analogy to the previous section, estimated dis-

tribution parameters are relegated to Table 8 of the

‘‘Appendix’’ (right-hand side). Table 7 displays the calcu-

lated physician-specific WTA values.

With regard to most MC-type attributes, WTA values do

not markedly differ between GPs and specialists. There are

two exceptions. One is the preferred provider list (PPL), for

which the median GP would have to be compensated at the

tune of 3.64 CHF/IPM, compared to 6.53 CHF/IPM for the

median specialist, the overall maximum found in this

study. This discrepancy is intuitive for three reasons. First,

a specialist who joins a MC network depends on referrals

from GPs (potentially governed by a PPL) in an even more

decisive way than in conventional practice, whereas

referrals play a minor role in either setting for a GP. Sec-

ond, many specialists serve more than one MC network, in

which case a PPL imposed by one of the networks can hurt

them. By way of contrast, GPs typically work for a single

MC organization; there is no need for them to rely on

demand emanating from other MC organizations. Finally,

specialized physicians may feel that they know better than

GPs which providers to choose for their patients or net-

works. The second discrepancy concerns the generic drug

list (GEN), where GPs have to be compensated with a

median of 3.06 CHF/IPM, but specialists with 4.44 CHF/

IPM. A likely explanation is that specialists are more likely

than GPs to treat rare diseases that might call for a brand-

name drug, which is not listed.

On the whole, general practitioners are found to be

less strongly opposed to attributes of MC. Thus, winning

them over to MC is less costly than estimated in ‘‘Esti-

mation results’’ section based on the whole sample. Still,

a payment of 1.50 CHF/IPM remains insufficient for

attracting a majority of GPs to an MC organization that

imposes guidelines requiring more than six quality circle

meetings per year, a preferred provider list, or a generic

drug list.

Conclusions

Policy makers try to limit increasing health care expendi-

ture by mandating or encouraging Managed Care (MC).

However, attempts to increase the market share of MC

often fail because of a lack of participating physicians. As

long as conventional practice remains an alternative, health

service providers must be won over to MC because they

have to accept limitations of their professional autonomy.

The objective of this contribution is to investigate physi-

cians’ preferences for MC attributes measured as willing-

ness-to-accept (WTA) values. The data come from a

sample of 1,088 Swiss private-practice physicians working

in ambulatory care participating in a discrete choice

experiment (DCE) in 2011.

The MC attributes studied are shared decision-making

and guidelines; reflecting treatment concepts; critical

incident reporting; attending 0, 3, 6, or 12 quality circle

meetings per year, accepting a preferred provider list, and

having drug prescription restricted to generics if available.

To determine the money valuation of MC attributes

expressed as WTA values, a price attribute is included,

defined as a payment per MC-insured per month (IPM) to

compensate the physician for additional cost and effort.

Estimated distribution parameters for the random-coef-

ficient model show that the median Swiss physician likes

shared decision making, three quality circles, and payment;

is indifferent with regard to six quality circles per year; and

dislikes all other MC attributes. The highest share of

opposing physicians is found for the preferred provider list.

All respondents like three quality circles per year. With

respect to strength of opposition, estimated WTA values

reveal that preferred provider and generic drug lists have to

be compensated most, with median WTA ranging from

3.60 CHF/IPM to 5.30 CHF/IPM (1 CHF & 1.1 USD in 2011). These figures exceed the current level of 1.50 CHF/

IPM, which already amounts to 8 % of median physician

Table 7 Willingness-to-accept values, general practitioners vs. specialists

Attribute General practitioners Specialists

MN MD Percentiles

MN MD

Percentiles

5th 95th 5th 95th

Shared decision making -0.58 -0.55 -1.62 0.46 -1.03 -0.70 -4.37 1.07

Guidelines 3.38 4.26 -3.34 7.63 3.47 4.15 -3.15 7.15

Critical incident report. 0.23 0.24 -0.16 0.59 0.68 0.78 -0.59 1.46

Three quality circles -0.90 -0.90 -0.96 -0.85 -0.13 -0.12 -0.56 0.27

Six quality circles -0.98 -0.98 -1.32 -0.64 0.60 0.60 0.20 0.96

Twelve quality circles 2.50 2.49 -0.12 4.92 3.61 3.72 0.93 5.83

Preferred provider list 3.64 3.64 -0.11 6.91 5.94 6.53 -1.30 11.30

Generic drug list 2.93 3.06 -1.70 6.80 4.15 4.44 -0.84 7.55

WTA values are shown in CHF per insured per month, IPM using physician-specific WTA values from interacted RCM

610 M. Rischatsch, P. Zweifel

123

income. Shared decision making and up to six quality

circles are accepted without compensation.

Clear signs of preference heterogeneity motivate dis-

tinctions between physician groups. For an expansion of

MC, physicians without prior experience with MC-type

attributes need to be attracted. However, some of their WTA

values turn out to be twice as high as those of physicians with

prior experience. Another distinction of importance is

between general practitioners and specialists since some MC

organizations have difficulty offering the full range of spe-

cialties. Indeed, specialists are found to exhibit higher WTA

values than GPs almost without exception; their resistance

against a preferred provider list would have to be overcome

by a payment of 6.53 CHF/IPM, the overall maximum found

in this study. Considering that a current rate for participating

in an HMO is 1.50 CHF/IPM, these findings lead to the

prediction that MC plans designed to achieve cost savings

are unlikely to enlist the majority of Swiss physicians as long

as they retain the option of conventional practice with full

professional autonomy. Realistically, the implementation of

shared decision making, critical incident reporting, and up to

six quality circle meetings per year can be expected. It is

doubtful that future cost savings achievable through treat-

ment guidelines, a preferred provider list, and generic drug

lists are of a magnitude that would permit the current 1.50

CHF/IPM to be doubled or even tripled, reaching compen-

sation amounts that would render MC attractive to the

median physician. Prospects for a voluntary, market-driven

expansion of MC in Switzerland look rather bleak indeed;

quality circles as the one positively valued attribute do not

modify this conclusion.

Acknowledgements The authors would like to express their thanks to Dr. med. Jacques de Haller and Dr. med. Ignazio Cassis from the

Swiss Medical Association (FMH) for making the experiment for the

present analysis possible. Support by Martina Hersperger and Esther

Kraft is also gratefully acknowledged. Special thanks go to Dr. Maria

Trottmann and Dr. Harry Telser for their very helpful comments.

Appendix

See Table 8.

Table 8 Preferences for managed care attributes (model

with interactions)

Attribute Parameter Experience Profession

Value SE Value SE

Shared decision making Mean -0.24 (0.14) 0.28 (0.11)

SD 1.14 (0.16) 0.71 (0.16)

SDM interacted Mean 1.32 (0.17) 0.18 (0.18)

SD 0.35 (0.96) 1.30 (0.27)

Guidelines Mean -1.71 (0.22) -1.55 (0.24)

SD 1.30 (0.32) 2.65 (0.26)

GL interacted Mean 1.25 (0.26) -0.07 (0.31)

SD 0.91 (0.38) 0.79 (0.34)

Critical incident reporting Mean -0.34 (0.10) -0.11 (0.11)

SD 0.37 (0.17) 0.34 (0.24)

CIR interacted Mean 0.54 (0.18) -0.22 (0.17)

SD 0.72 (0.28) 0.61 (0.26)

Preferred provider list Mean -2.50 (0.14) -1.62 (0.13)

SD 2.22 (0.18) 1.49 (0.20)

PPL interacted Mean 1.07 (0.31) -0.95 (0.21)

SD 0.36 (0.43) 2.09 (0.22)

Generic drug list Mean -2.10 (0.19) -1.31 (0.14)

SD 2.48 (0.24) 1.71 (0.14)

GEN interacted Mean 0.41 (0.23) -0.56 (0.20)

SD 0.41 (0.29) 0.65 (0.17)

Three quality circles Mean -0.17 (0.16) 0.42 (0.13)

SD 0.04 (0.29) 0.04 (0.20)

QC3 interacted Mean 0.78 (0.18) -0.37 (0.17)

SD 0.15 (0.19) 0.31 (0.29)

Six quality circles Mean -0.73 (0.17) 0.46 (0.14)

SD 0.03 (0.23) 0.23 (0.27)

What do physicians dislike about managed care? 611

123

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