Quality of services and demand for health care in Nigeria: A multinomial probit estimation

This study attempts to empirically answer three important policy questions for a population sample from Ogun State, Nigeria: 1. 1. Would price (fee) increases for health care lead to large reductions of care usage or to shifts across types of care used?2. 2. Would price increases lead to net increases in revenues for the health system?3. 3. Would the price increases have larger impacts (in the form of reductions in health care usage) on lower income members of the population? Household data are combined with data on prices and quality of care, collected directly from facilities, to estimate the demand for outpatient health care. Many of the statistical problems of demand estimation with micro level data are avoided by an innovation--the first use of the multinomial probit estimation method for health demand. A separate but related problem, that the price data used in such studies are usually endogenous (in fact usually are expenditures, which are to a great degree determined by the actual care choice) is avoided by the collection of a specific exogenous price variable directly from the health providers. Because the health care 'good'--outpatient health care--can vary to such a degree across providers, quality of care must be controlled in order that the coefficients on prices and other variables will not be biased. A strong circumstantial case can be made that past estimation efforts probably underestimated the impact of prices of care on provider choices, because those providers charging higher prices also tend to provide higher quality care and those charging lower prices to provide care of lower quality. Because of this fear of bias on the extremely important price coefficient, effective control of the quality of the care available at the alternative accessible care providers is almost certainly at this time the most important marginal innovation to demand estimation. Most past researchers simply have not had available to them exogenous quality of care information collected via a facility (provider) survey. This study tried several health care provider quality variables and finally used three distinct variables which were statistically significant: (a) expenditure per person in population served; (b) percentage of times drug are available; and (c) interviewers evaluation of the physical condition of the facility. Price of a visit to the facility is also included, and also is an exogenous variable collected directly from the alternative available providers. For the variables of most interest for this study, price and quality of care, the results are quite reasonable and much as expected. It is seen that higher prices at either type of facility will tend to reduce usage of that type, and that usage will tend to increase for each type of care as the quality of the care is increased. The results also indicate no difference in the price responsiveness of different income groups.