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The model based on pharmaceutical expenditure per capita is a more balanced model containing both need and enabling factor variables.
For such an allocation, the model based on pharmaceutical expenditure per capita would be ideal since it contains more factors as identified by the modified Andersen's model.
The log-linear model based on total pharmaceutical expenditure works acceptably well and can be considered useful for predicting future total pharmaceutical expenditure following observed trends.
One variable which does not appear in the log –linear prediction model based on the total pharmaceutical expenditure, but appears in the allocation model that is based on primary health care pharmaceutical expenditure per capita is the variable related to whether a district is considered by MOH to be a hard to reach district or not (DISTACCESS).
The model based on primary health care pharmaceutical expenditure per capita (Model 5) explained about 50%% of the observed variation in per capita primary health care pharmaceutical expenditure among the study districts (Adjusted R = 0.513).
Model 8; the log-linear model based on primary health care pharmaceutical expenditure per OPD visit explained about 56%% of the observed variation in the logarithm of primary health care expenditure per OPD visit in the study districts (Adjusted R = 0.562).
The log-linear model based on total primary health care pharmaceutical expenditure may however not be ideal for allocating the set national primary health pharmaceutical budget among the various districts based on the needs of the population.
The log-linear model based on total primary health care pharmaceutical expenditure would for example be used to predict future total district primary health care pharmaceutical expenditure based on any plans the government may have for the district (e.g. increasing the number of health facilities, upgrading facilities etc).
The pharmaceutical market's demand function is thus often distorted, and a model based on price elasticity of demand might not present a real world situation of the complexity of the pharmaceutical market.
The design of optimal model based experiments is finding increasing use in various fields including chemical, pharmaceutical, biological engineering, and biomedicine.
The developed model based on CRGs can be of great use in managing the pharmaceutical spending in integrated health services such as the National Health Service (NHS).
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