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The objective of this study is to analyse the factors that influence the utilisation of healthcare services in the Dalarna. The dataset for this study is generated from patient visit records in Dalarna and the dataset consist of over eight million rows and 17 columns covering diverse demographics and healthcare details. The dataset's analytica capacity for this study was enhanced by refining the data to 453,380 rows and 56 columns, with dummy encoding performed on some categorical variables. The ZTNB model is selected to effectively handle overdispersion and datasets that do not include zero counts of healthcare visits, resulting in precise outputs. The analysis uncovers notable discrepancies in healthcare utilisation depending on age, gender, and geographic region. Women have much higher rates of healthcare service utilisation, with 7,152,440 visits (56.40%) as opposed to men, who recorded 5,528,553 visits (43.60%). Furthermore, there are notable regional discrepancies in Dalarna like Falun and Borlänge utilising healthcare services more frequently than other parts of Dalarna. The findings of this study emphasise the significance of enacting customised healthcare policies that target the distinct requirements of various demographic cohorts and geographical regions. To achieve fair and just healthcare outcomes, it is critical to efficiently handle chronic illnesses, increase healthcare availability in remote regions, and offer services tailored to specific genders. This study emphasizes the importance of understanding regional disparities to improve healthcare service utilisation and deliver better outcomes in the Dalarna region. Although this study takes a broad approach, it has certain drawbacks. The study examined healthcare utilisation from 2021 to 2023, but its findings may not accurately represent long-term patterns. The dataset was deficient in precise socioeconomic characteristics and cultural elements, which restricted the scope of the investigation. The scope of this study does not cover predictive modelling. Future research should include more socioeconomic and cultural information and extend the analysis period for a better understanding of long-term trends.