ACİL SERVİSLER İÇİN BULANIK MANTIK TABANLI BİR KLİNİK KARAR DESTEK SİSTEMİ

Abstract

Acil servisler, her hastanede olan ve içerisinde özel birimlerin bulunduğu, birçok problemi olan en önemli birimlerinden biridir. Bu sorunların başında, acil servislerin kalabalık olması ve acil hasta bakım planlamasının zorluğu gelmektedir. Bu problemler için triyaj sistemi gibi uygulamalar kullanılmaktadır. Fakat bu gibi uygulamalarında problemlere tam olarak çözüm getiremediği bilinmektedir. Bu çalışmada acil servise gelen hastaların sınıflandırılmasına yönelik bulanık mantık tabanlı bir klinik karar destek sistemi (KKDS) gerçekleştirilmiştir. Çalışmada Muğla Sıtkı Koçman Üniversitesi Eğitim ve Araştırma Hastanesi'nde anonim olmayan 180 hastanın başvuru şikâyetleri ve medikal verileri kullanılmıştır. Hastaların 95'i kadın, 85'i erkek olup yaş ortalamaları 46’dır. Gerçekleştirilen sistemin performansını test etmek için uygulamanın sonuçları ve uzman hekimin kararları istatistiksel olarak değerlendirilerek (doğruluk, duyarlılık ve özgüllük) karşılaştırılmıştır. Sonuç olarak, gerçekleştirilen sistemin doğruluğu %83, duyarlılığı %87, özgüllüğü %76,6 bulunmuştur. En son kararın uzman hekime ait olması şartıyla bu tür KKDS’nin geliştirilmesi hastanelerin acil servislerinde özellikle yoğun olduğu dönemlerde ciddi zaman ve mekân açısından kazançlı olacağı düşünülmektedir.

Keywords

• Acil tıp,Karar destek sistemi,Bulanık mantık

A FUZZY LOGIC BASED CLINICAL DECISION SUPPORT SYSTEM FOR EMERGENCY SERVICES

Abstract

Emergency departments are one of the most important units in the hospital where there are special units and many problems. At the beginning of these problems, emergency services are crowded and urgent patient care planning is difficult. The applications such as triage system are used for these problems. However it is known that such applications do not fully solve these problems. In this study, a fuzzy logic based clinical decision support system (CDSS) was developed for the classification of emergency patients. In the study, application complaints and medical data of 180 non-anonymous patients in Muğla Sıtkı Koçman University Training and Research Hospital were used. The 95 of the patients are female, 85 are male and the average age is 46. In order to analysis the performance of the performed system, the results of the application and the decisions of the specialist doctor were compared statistically (accuracy, sensitivity and specificity). Consequently, the accuracy of the realized system 83%, sensitivity 87% and specificity 76.6% was found. Provided that the most recent decision belongs to the expert physician, the development of this kind of CDSS is thought to be beneficial in terms of serious time and space in the emergency departments of the hospitals, especially during intensive periods.

Keywords

• Emergency medicine,Decision support system,Fuzzy logic

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