Mining Medication Behavior of the Completion Leprosy's Multi-Drug Therapy in Indonesia
- 1 September 2018
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 271-274
Abstract
Leprosy is one of the listed neglected tropical diseases which is continuing as a major health problem in Indonesia. Low adherence to Multi-Drug Therapy (MDT) against leprosy is still a significant obstacle in disease control, as the defaulters with incomplete cure remain as potential sources of infection, lead to patients' irreversible complications and multidrug resistance. This paper aims to describe the behavior of leprosy patients during the long-term medication of MDT drugs through mining association rule between the on-time of taking MDT to healthcare facilities using apriori algorithm. Data has been collected from manual leprosy registry cohort of 27 Primary Health Care (PHC) at Pekalongan District start from June, 1 st 2012 to June, 30 th 2014. This study converted the range date between the MDT collection attendances to the new label, which is called on-time attendance (OTA), and on time completion (OTC). Both of MB and PB patients shows the association between MDT 2, MDT 3 have a strong relation to the late of the completion treatment behavior of leprosy patients.Keywords
This publication has 8 references indexed in Scilit:
- Leprosy Drug Resistance Surveillance in Colombia: The Experience of a Sentinel CountryPLOS Neglected Tropical Diseases, 2016
- The application of Apriori-BSO algorithms in medical records data mining2016
- Magnitude of Neglected Tropical Diseases in Indonesia at Postmillennium Development Goals EraJournal of Tropical Medicine, 2016
- Factors associated with the worsening of the disability grade during leprosy treatment in BrazilLeprosy Review, 2015
- Assessing and improving adherence with multidrug therapyLeprosy Review, 2012
- Mining multi-item drug adverse effect associations in spontaneous reporting systemsBMC Bioinformatics, 2010
- Data Mining and Knowledge Discovery Handbook2005
- Application of Data Mining Techniques to Healthcare DataInfection Control & Hospital Epidemiology, 2004