PENGEMBANGAN PROTOTIPE SISTEM PENDUKUNG KEPUTUSAN KLINIS UNTUK DIAGNOSIS DAN PENATALAKSANAAN DEMAM BERDARAH DENGUE

Background Dengue hemorrhagic fever (DHF) is a health problem in many parts of the world, especially in Indonesia. Outbreaks happens in 12 provinces with a total of 12,224 cases and 218 deaths. Diagnostic and management of DHF are required exactly and accuracy to avoid the severity of illness or death. However clinicians still make misdiagnosis because DHF has similarities with the symptoms of some diseases such as malaria, typhoid fever, leptospirosis, and other diseases. Number discrepancy diagnosis by WHO (Word Health Organization) criteria approximately 31.1% of due to the lack of clinician�s ability in diagnosing. It is a need to develop a prototype of clinical decision support system in diagnosing and management DHF because CDSS (Clinical decision support systems) has been widely shown to increase the exactly, precision, accuracy, efficiency and effectiveness in health care. Aim of the study Developing a prototype of clinical decision support system for DHF diagnosing and managing that have good validity and reliability or good performance system. Methodology This study use action research approach. Development of system with prototyping methods and use rule-based system with the format of \"IF THEN \" in support of decision making. Results Clinical decision support systems have been developed and tested by comparing the output of clinician and the output system based on 2 kinds of guidelines (WHO 1997 and WHO 2009). The first test 46 quessionnary data from clinician, the correct result 22 (47,87%), X 2 =0,087, p=0,768 based on WHO 1997 Guideline and 26 (56,52%), X 2 =0,783, p=0,376 based on WHO 2009 Guideline, the output system both guideline are 100%. The second test, 108 cases, the correct result 77.78% (X2 = 2.5, p = 0.114) based on WHO 1997 Guideline and 78.79% (X2 = 0.831, p = 0.362) based on WHO 2009 Guideline. The output system and diagnosis from clinician are not significant difference and the system has higher performance than clinicians. The system has good validity and reliability to support clinical decision making in diagnosis and management of DHF