# 6 Discussion

Health policy in India is determined by different states (most of which are heavily rural), so any general discussion is limited by the urban nature of the study. There are a couple of clear hypotheses to pursue. First, the typical solution for low-quality service, more training, is unlikely to be effective, particularly given the cost of additional training. The difference in effort between non-MBBS and an MBBS doctor (a difference of up to $8,000 per student in training costs) while signi fi cant, is smaller than the difference between a fully trained MBBS doctor in a public primary health clinic and all other MBBS holders.<sup>27</sup> A difference in conscientious effort is a more likely explanation for the difference between low-quality public and private providers.

We need to look more carefully into the motivations, career path and expectations for doctors at elite public hospitals. The extra visible effort by providers in these institutions may well be associated with closer monitoring and the desire to be retained. However, because effort also increases with competence, a complementary hypothesis may be that doctors in public hospitals are looking for careers in the private sector and are developing reputations.

For the poor who visit low-quality public doctors and even somewhat lower-quality private practitioners, there are few easy solutions. Making public doctors in such areas more responsive to patient needs may be possible through compensation schemes other than fi xed salaries, although both capitation and fee-forservice programs could be corrupted without investments in administration and monitoring. Unfortunately low quality in the private sector cannot be addressed through incentives. The greater use of medications among the private providers suggests that doctors (like most professionals) are sensitive to their patient desires; perhaps overly so. Ways to in fl uence patient expectations regarding drug treatments is a difficult but urgent topic for further research. It could be as simple as public service announcements cautioning against the use of too many drugs or it might be as complicated as improving patients’ abilities to search for reliable and trustworthy care.

More data, a larger sample or a modi fi ed sampling strategy could have addressed the lack of information on patient attributes (matched to practitioner effort) and selection into the public sector. We explored using “standardized patients” (fake patients), who would mitigate the matching problem but discarded this possibility for ethical reasons. Because the doctor would need to be informed prior to sending such patients, it was unlikely that permission to carry on would have been approved. A second option, conducting exit surveys of patients on the day of the observation, turned out to be operationally difficult given the urban scenario and the crowded clinics. Concurrent work in Paraguay implements the matching exit survey (Das and Sohnesen 2005). The preliminary results are very much in line with what we fi nd here–practice patterns vary considerably across doctors, but very little across patients for the same doctor.

The differences between the public and private sector are the joint effects of selection and moral hazard. (altruistic doctors are in the public sector versus lazy doctors are in the public sector). A number of

> 27 MBBS degrees are offered mostly by public institutes where the budget is not itemized. Our fi gure of $8,000 is based on the fee for the MBBS degree in a private institute (Manipal Academy of Higher Education). This overestimates the true cost if governments operate as non-pro fi ts. It underestimates the true cost if (a) efficiency is lower in the government sector and/or (b) the quality of training is higher in the private sector.

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