Data format optimization for subsequent analyses of hospitalization data

Contemporary healthcare systems generate large amounts of data, related to patient health, diagnostics, medical procedures, and more. Processing and analyzing the available data make it possible to identify trends, correlations, and other interconnections that can serve as a basis for subsequent management decisions. Based on data and its correct interpretation the overall quality of public healthcare can be improved. The main objective of the present research is to examine medical data from hospitals in Bulgarian healthcare with a focus on subsequent data analysis. We use descriptive statistics to discover patient admission tendencies and use predictive analysis to forecast future admission trends. Our study presents hospitalization trend analyses, using descriptive statistics and predictive analysis. The obtained insights can be used to improve patient care by predicting hospitalization rates and optimizing patient planning procedures and resource allocation.