In this paper, a statistical analysis is made of the health personnel in Romania in the public and private systems using data from the period 1990-2022, provided by the National Institute of Statistics. Using the least squares method, analytical functions are found that model the trend and forecasts are made for the years 2023 and 2024. The confidence intervals for the predictions are also found, at a significance threshold of 5%, and the correlations between certain indicators are analysed. It was found that in the public sector there was a downward trend, in general, for all categories of medical personnel in the period 1990-2017, followed by an increasing evolution after 2018, due to salary increases in the system. However, there is still a shortage of physicians in the public sector, even if their number has steadily increased in the last years. There is no correlation between the number of physicians and the number of beds in public hospitals, although this should be positive and high. On the other hand, in the private sector the trend is obviously increasing throughout the studied period, the correlations are very strong between the analysed indicators, a situation explained by the fact that in this system the goal is to minimize expenses and increase profit and less access of all citizens to health services.

Background/Objectives: Globally, healthcare systems face challenges in optimizing performance, particularly in the wake of the COVID-19 pandemic. This study focuses on the analysis and forecasting of key performance indicators (KPIs) for the County Emergency Clinical Hospital in Craiova, Romania. The study evaluates indicators such as average length of stay (ALoS), bed occupancy rate (BOR), number of cases (NC), case mix index (CMI), and average cost per hospitalization (ACH), providing insight into their dynamics and future trends. Methods: We performed statistical analyses on quarterly data from 2010 to 2023, employing descriptive statistics and stationarity tests (e.g., Dickey–Fuller), using ARIMA models to forecast each KPI, ensuring model validation through tests for autocorrelation, heteroscedasticity, and stationarity. The model selection prioritized Akaike and Schwarz criteria for robustness. Results: The findings reveal that ALoS and BOR demonstrate seasonality and are influenced by colder months, and it is expected that the ALoS will stabilize to around five days by 2025. Moreover, we predict that the BOR will range between 46 and 52%, reflecting these seasonal variations. The NC forecasts indicate a post-pandemic recovery but to below pre-pandemic levels, and we project the CMI to stabilize at around 1.54, suggesting a return to consistent case complexity. The ACH showed significant growth, particularly in the fourth quarter, driven by inflation and seasonal costs, and it is projected to reach more than RON 3000 by 2025. Conclusions: This study highlights the utility of ARIMA models in forecasting healthcare KPIs, enabling proactive resource planning and decision-making. The findings underscore the impact of seasonality and economic factors on hospital operations, offering valuable insights for improving efficiency and adapting to post-pandemic challenges.

In this paper, a statistical analysis of some financial indicators in Romania for the period 1991-2023 was made. Indicators from the agricultural field were studied, such as the export and import of animals and animal products, but also of vegetable products, as well as the total import and export. Using the ARIMA method (autoregressive integrated moving average), forecasts for the period 2024-2026 were presented for all the studied indicators.

In this paper, a statistical study on key performance indicators in health system is given and two regression models with the average cost of hospitalization as the dependent variable are found. Using linear regression, it was found that a decrease in the average cost per day of hospitalization can be achieved by increasing the bed utilization rate and increasing the number of cases treated in a calendar year. Also, the decrease in the case-mix index, which can be achieved by increasing the number of resolved cases, leads to a decrease in the average cost of hospitalization per day. The obtained results were interpreted and certain measures are proposed to improve health management.