An Analysis of Primary Healthcare Antibiotic Prescription Rates Within Castile and Leon (Spain): 2013–2023

<b>Background/Objectives</b>: According to the World Health Organization, more than one million deaths each year are attributable to bacterial resistance, making it one of today's main public health threats that could cause up to 10 million deaths by 2050. In this study, antibiotic prescription rates at primary healthcare centers) within Castile and Leon are analyzed over the period 2013-2023, and some of the sociodemographic variables that might influence the prescription of antibiotics are determined. <b>Methods</b>: A descriptive, observational, ecological study was conducted based on data gathered by Concylia (pharmaceutical information system-Castile and Leon Health Service). Comparable variables (time of prescription and type of health center) and variables of results (Defined Daily Doses per 1000 health center card-holders per day and qualitative antibiotic selection variables) were analyzed. <b>Results</b>: During the first years under analysis, prescription rates increased, followed by a reduction at the start of 2015 that continued up until 2021. Another rise was then recorded, and prescriptions once again reached values in 2023 that were comparable to those observed in 2019 (17.62 and 17.45 Defined Daily Doses per 1000 health center card-holders per day). Throughout Castile and Leon as a whole, there were more prescriptions within urban areas; but when analyzed by provinces, prescriptions were mainly higher in rural areas within most provinces. The percentage of macrolides was higher in urban areas, whereas the percentage of fluoroquinolones was higher in rural areas. <b>Conclusions:</b> The variation was repeated throughout the period under study in a similar way in all the provinces of Castile and Leon and at a national level. Different prescription rates were observed by province within the autonomous region. Moreover, higher prescription rates were observed in the rural areas of most provinces. The data source did not allow linking prescriptions to diagnoses, limiting interpretation.