Developing a data monitoring system for methadone flexi dispensing (MFLEX) service using mahalanobis-taguchi system - Siti Khadijah, Mat Saad (2022)
Methadone flexi dispensing (MFlex) program is one of the components of harm reduction to address HIV/AIDS issues among injecting drug users and at the same time address the issue of opiate addiction, especially heroin. According to the existing system through laboratory report of blood test and methadone trend chart as shown by the clinic, it does not have generic indicator for classifying the healthy and unhealthy patient. From that, patient under MFlex program is required to do 4 types of blood tests and 4 types of methadone dosages trends to observe their healthiness performance. Subsequently, to confirm that the patient has liver problems, a doctor will refer to the Alk Phosphatase, ALT (SGPT), and AST (SGOT) parameters in the blood test to make a decision. Although those parameters have been clinically proven, there is a need to enhance the system by determining the degree of contribution for each parameter through a new method. A similar problem also happened to the methadone dosages trends. Since the existing system need further enhancement towards classification and optimization, the results in the validation through unknown data which is new methadone patients would be less accurate. The clinic also takes a longer time to determine the patient’s healthiness performance and the government has to bear some additional expenses. The objective of this research work is to apply Mahalanobis-Taguchi system (MTS) in the MFlex program. The data is collected at Bandar Pekan clinic with 34 parameters in the blood tests and 16 parameters in the methadone dosages. Two types of MTS methods are used such as RT-Method and T-Method for classification and optimization respectively. As a result, the RT-Method is able to classify between healthy and unhealthy samples, while the T-Method is able to evaluate the significant parameters in terms of degree of contribution for the blood tests and methadone dosages. In validation of unknown data, 60 unknown samples in blood tests and 24 unknown samples in methadone dosages have been validated using MTS. All of them have different number of positive and negative degree of contribution to achieve lower MD. There are 6 types of modification to prove the proposed solution and type 6 modification has been selected as the best solution. In conclusion, a pharmacist from Bandar Pekan clinic has confirmed that MTS is able to solve a problem in classification and optimization in the MFlex program. Therefore, it might be interesting if MTS is applied more in the healthcare sector such as it can be applied to the pandemic that hit Malaysia nowadays which is the cases of Coronavirus (Covid-19) where it can be classifying the severe patients of Covid-19, the deaths in a month, and the infection stage.