CIze priemerna dlzka zivota od roku 2000 do roku 2015 v Portugalsku, vzrástla takmer o 4roky, pretoze v roku 2000 bola priemerna dlzka dozitia pred 77rokom a po roku 2015 az nad 81 rokov, bola dlzka priemerneho dozitia v Portugalsku. Cize priemerna dlzka dozitia sa zvysovala, co je pozittívny trend. Alkohol bol má veľký vplyv na dĺžku dožitia.Vyvoj spotreby alkoholu v Portugalsku vyzeral tak, že alkohol je predpokladaný negatívny faktor, ktorý vplýva na celkové zdravie a tým aj na dĺžku života. Zvyšuje krvný tlak, má negatívny vplyv na pružnosť ciev.P- value nám vyšla 0, ciže nižšia ako 0,1 a hodnota r-squared vyšla zhruba 0,88 - to znamemná, že v 88% prípadoch mala naozaj konzumácia alkoholu veľký vplyv na dĺžku dožitia.

The figure illustrates the relationship between duration and to_year over the observed time period. The plot shows a wide dispersion of duration values across years, with durations ranging from near zero to above 40 units. A general upward tendency can be observed, suggesting that higher duration values appear more frequently in the more recent years. However, the large number of overlapping lines creates a dense pattern, indicating substantial variability in duration across different observations. Overall, the figure highlights both the increasing tendency and the significant variability of durations over time.

Decision tree models are widely used in health economic evaluation to compare alternative healthcare interventions under uncertainty. These models are particularly useful for performing cost-effectiveness analysis (CEA) and cost-utility analysis (CUA) where outcomes are measured in quality-adjusted life years (QALYs). This tutorial demonstrates how to build a reproducible decision tree model in R using the rdecision package. The example illustrates a simplified pharmacoeconomic comparison between low molecular weight heparin (LMWH) and conventional treatment for patients undergoing hip replacement surgery. The tutorial walks through the process of defining decision nodes, chance nodes, and terminal nodes, assigning probabilities and costs to model pathways, and attaching health utilities to terminal outcomes. The model is evaluated to estimate expected costs and QALYs for each intervention and to calculate the incremental cost-effectiveness ratio (ICER). This example provides a step-by-step introduction to decision tree modelling in R, making it useful for students and researchers interested in Pharmacoeconomics, health technology assessment (HTA), and health data science. Keywords Decision tree modelling, cost-utility analysis, cost-effectiveness analysis, QALY, ICER, pharmacoeconomics, health technology assessment, R programming, health economic modelling, reproducible research.