Abstract:
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The study concentrates only on the low income care (LIC) or free medical care program. The data for this analysis are obtained from documents relevant to the program and the sampled survey in Mahasarakham in March, 1986. The head of a household, a spouse or a family member who could give sufficient information about the household, was randomly interviewed. Altogether, the 727 sampled households composed 2 groups, low income card holders and non low income card holders, according to the criteria of LIC provision of the Ministry of Public Health. The household which has an income of less than 2,000 baht per month is eligible to receive the LIC. For a better understanding of the LIC program, the study starts with the LIC program evaluation.
The main purpose of this study is to identify the target population who will be provided with free health care services by means of LIC. This was done by applying the basic minimum needs data. Specifically, the study is to (1) evaluate the LIC program, (2) examine the contribution of basic minimum needs factors to economic status of the sampled households, (3) propose useful information for the formulation of policies concerning the LIC program of MOPH. In addition, the socio-economic-demographic, and basic minimum needs characteristics of the households are also studied.
The principal methodologies applied in this study are Multiple Classification Analysis (MCA), Heirarchical Regression Analysis and Discriminant Analysis. The variables used in this study comprise four groups of factors : soci-economic, demographic, basic minimum needs, and development factors. The analysis is divided into two parts. The first is to evaluate the program, the other to propose models in order to identify target groups needing health care services.
The results show that the LIC program has been implemented for about 12 years, has met with a certain amount of success. Evidently, the program can cover many areas of the kingdom, levels of care and units of government. However, it is found that the total expenditure for this program has rapidly increased about 2.4 to 2.7 times more than the fiscal budgets in 1985 and 1986 respectively. The main causes of this high expenditure of free medical services stem from the LIC provision system. It is difficult to identify the poor people by using the criteria of a household income of less than 2,000 baht per month as poor and deserving to receive the card. So, the people who actually receive the card cannot be identified as being truly poor or not. On the other hand, those who are really poor have not received the LIC but, at the same time, have used free medical care services. The number of this type of patient is rather high compared to LIC holders. The number of times this type of patient visits the health center is also high and the unit cost per inpatient is somewhat more than other types of patients of the general hospitals. Factors determining who can be LIC holders are the various methods of announcement of the village LIC provision, informants of LIC information, criteria of providing LIC in the village and the submission of the household members' names for the right to have LIC. Also attitudes towards LIC, knowledge of LIC information and patterns of health service utilization are significant factors relating to LIC usage. Morover, in the analysis of validation of LIC provision with various socio-economic-demographic factors, the results show that these factors can neither significantly explain who are the actual LIC holders. It is interesting that income is not the most crucial factor relating to actual LIC holders.
For the proposed models, four are conducted to compare the results of the analysis. The model of income-in-cash plus in-kind can explain the living conditions of the target population significantly better than the model of income-in-cash alone. In the comparision of the poverty index using actual local minimum wage and official local minimum wage, the results show that there is not much difference in their ability to indicate the economic status of the households. One group of factors significantly predicts or classifies the target population in the four models is mainly the same. The cattle, the number of household members, the average years of education of working-age members, value of property, number of children aged 7-14, the housing condition and flushed latrine in the house, highly correlate with the average income. It could be said that these factors should better identify the target population than the single factor of income alone.
From the analysis of the proposed models, it is concluded that the INC model and the PIL model are efficient models in discriminating the correct group membership. While it shows only slight efficiency in predicting group membership for INCK and PI model, the related models yield significant results.
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