Analysis of parameters that affect the lenght of stay of pacients in the Emergency department Maribor

Prezasedenost v urgentnih centrih in preobremenjenost osebja je problem, ki se trenutno pojavlja marsikje po svetu. Prezasedenost urgentnih centrov ima posreden negativen vpliv tako na paciente kot na zaposlene. Z ozkimi grli nastajajo zamude pri zdravljenju, poviša se lahko stopnja smrtnosti pacientov, podaljšuje se čas obravnave in pacient je bolj dovzeten za ponovno hospitalizacijo. Da bi zmanjšali preobremenjenost urgentnih centrov, smo v diplomskem delu poskusili napovedati čas trajanja obravnave pacientov glede na izbrane parametre in s tem poskusili predvidevati, kako dolgo traja obravnava pacienta na urgenci glede na značilnosti pacienta in obravnave. V prvem delu smo naredili pregled strokovnih člankov, kjer so avtorji raziskovali podobne primere našemu. Predstavili smo tudi trenutno metodologijo organizacije slovenskih urgentnih centrov. Nadaljevali smo z raziskovalnim delom, kjer smo iskali linearni regresijski model, ki bi najbolje opisal izbrane podatke. Rezultate smo interpretirali in identificirali kritične parametre. V zaključku diplomskega dela smo podali rešitve tako za izboljšavo modela kot rešitve za razbremenitev urgentnih centrov.Emergency department overcrowding and staff overload are currently significant issues in many parts of the world. The overcrowding in emergency departments indirectly negatively affects patients and employees. Bottlenecks lead to treatment delays, increasing patient mortality rates, prolonging treatment times, and raising the risk of re-hospitalization. To address the issue of overloading in emergency departments, our thesis aimed to predict the length of stay for patients based on selected parameters. By doing so, we sought to estimate the duration of a patient\u27s treatment in the emergency department based on their characteristics and treatment specifics. In the initial phase, we conducted a comprehensive review of scientific articles where authors explored similar cases. We also presented the current methodology used in Slovenian emergency departments for organizing patient care. Subsequently, we carried out our research to find the most suitable linear regression model that could accurately describe the selected data. We interpreted the results and identified critical parameters affecting the length of stay. Finally, we provided solutions to enhance the model and alleviate the overload in emergency departments