measures can be used to evaluate the quality of care. For instance, Davies and Ware (1988) conclude that “ _consumers can provide a valid assessment of quality and that bias from personal characteristics is not strong enough to invalidate consumers’ ratings_ ”, a finding that contrasts with those of Eriksen (1987) and Chang et al. (2006), which do not find support for a strong relationship between the quality of care and patient satisfaction.

We differ from previous studies in our methodological approach. Quantitative studies of patient satisfaction often examine correlations between reported satisfaction and particular aspects of the doctor-patient interaction, with and without the inclusion of patient and doctor characteristics as additional covariates. As is well known from the empirical economics literature, these associations have limited importance as policy-tools if unobserved patient and doctor characteristics correlated both with effort and satisfaction could bias the results. For instance, if more courteous doctors also exert greater effort, and patients report higher satisfaction when they are treated courteously, a positive correlation between effort and satisfaction would reflect, in part, the positive association between courtesy and satisfaction rather than the impact of effort.<sup>2</sup> Policy based on such associations could lead to results very different from those intended—for instance, bonuses for doctors based on reported satisfaction may lead to more courteous behavior without any impact on the quality of medical advice.

To address this problem we collected doctor effort and patient satisfaction measures for multiple patients for every doctor in the sample. By comparing patient satisfaction for the _same_ doctor when s/he exerts greater/less effort in the interaction, unobserved variables at the level of the doctor can be accounted for. This technique, known as the “fixed-effect” or “within” specification, has been used extensively in the economics literature and, as discussed below, using this methodology significantly alters the estimated impact of effort on satisfaction. Indeed, the results argue for a “sorting” interpretation whereby patients more likely to report high levels of satisfaction are also more likely to visit doctors who exert greater effort; effort in and of itself has no impact on reported satisfaction.

The remainder of the paper is as follows. Section II introduces the data and the empirical framework. Section III presents the results and Section IV discusses the conclusions and caveats.

# **Section II: Country Context, Data and Empirical Framework**

# _The Country Context_

Paraguay is a land-locked country in the center of South America with a fast-growing population (2.48 percent) of 6.3 million people, of which 52 percent are located in urban areas. Geographically, the country is divided into 18 “departments” that also serve as organizing units for health facilities.

Three main institutions provide health services in the country. These are the public sector under the Ministry of Health (MoH), the semi-public sector under the Institute of Social Provision (IPS), funded through employees and employer contributions, and the fully private sector. The Ministry of Health covers 63 percent of the population; the IPS 17 percent and the private sector a further 10 percent (the remainder is covered by a variety of providers including the police, the army and the Paraguayan Red Cross). In contrast to MoH facilities, which can be visited by any individual, both the private sector (through higher prices) and the IPS (by treating only those with formal employment) are restricted in access.

> 2 Chang et al (2006) report a significant association between communication and satisfaction with no relationship between quality and satisfaction. One problem with this study is the sample, which consists almost entirely of older patients who may be less able to differentiate the quality of care from interpersonal interactions (Cleary et al, 1997).

3