Abstract

Corruption and irregularity are situations that we may encounter in every field such as banking, insurance, security and health. Health expenditures are increasing every year all around the world. The amount of corruption and irregularity is parallel to this increase. Corruption and irregularities in the health sector both threaten human health and cause financial losses. With the help of methods for detecting corruption and irregularities, malpractices can be avoided and also financial losses can be prevented, thus contributing to the improvement of health service delivery. The aim of this study is to identify risky individuals who may be involved in drugs, which constitute an important part of health expenditures, and who may cause corruption and irregularities. Drugs with the Anatomical Therapeutic Chemical (ATC) code with the same active ingredient were examined. Anomaly detection, association analysis and rule-based data mining methods were used for the detection of corruption and irregularity. 24 physicians were identified as with high risk. Those who were found to be risky in the analysis were examined specifically and it was confirmed that all of them abused the drug with the relevant active ingredient, thus it means that the method used is 100% consistent and accurate.

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