InterCriteria Analysis of Public Health Data in Bulgaria

Abstract

The assessment of the system of public health has been receiving significant importance over the past years, because it reflects the trend in optimizing the effectiveness of the health services. The article uses a recently defined intelligent decision-making method based on an extension of fuzzy logic called InterCriteria Analysis (ICA). Object of the study of (the) ICA are real data in the field of public health connected with in-patient, out-patient health care establishments and their regional distribution in Bulgaria for the years 2010–2018. Using the ICA approach, we can identify the relationships between and among indicators of health care facilities and nursing staff, statistical regions and districts, the doctors in the healthcare facility by medical specialties, and more. The metrics that have the greatest dependencies and the contrary indicators that are often independent of one another. This way we can monitor their demeanor over time.