Background: We analyse the impact of the three following categories of Health Policies (HP) carried out by the Greek SYRIZA-ANEL governments on the efficiency of Greek public general hospitals. These governments have implemented policies intended to change the rate of contributions to publicly funded healthcare (PCnH), policies to affect the volume and quality of publicly funded health care (PVQH) and those intended to affect the costs of publicly funded healthcare (PCH). A literary review of the PCnH. PVQH and PCH policies of the Greek SYRIZA-ANEL governments was carried out and an efficiency window-DEA study was executed using data from the Ministry of Health (MoH) and the Greek Statistical Authority (ELSTAT). Methods: The study was designed to assess the impact of PCnH. PVQH and PCH policies by the Greek SYRIZA-ANEL governments on the efficiency of Greek general hospitals. The data was collected from HEAL-Link scientific journals. Information on HPs was extracted from the work collected. The values of inputs and outputs used for the efficiency study were obtained from ELSTAT and Greek MoH databases. Results: HPs of the Greek SYRIZA-ANEL governments extend to all three HP categories of the sample used. These policies have a dual effect on both the inputs and outputs used in efficiency. Efficiency values exhibit fluctuations with good and bad years. The SYRIZA-ANEL governments seek to ensure more equality in access to health services. Some of the policies reduce costs and have a positive impact on efficiency, while others have the opposite effect. The increase in outputs achieved as a result of health policies is counter balanced by an increase in inputs. Conclusions: The PCnH, PVQH and PCH policies of the SYRIZA-ANEL governance seem to have a dual orientation: some policies reduce the cost of a category and contain the total cost, thus positively contributing to an increase in efficiency. Certain policies are aimed more at fulfilling the criterion of equality in the provision of health services and thus the cost inevitably increases. From the window-DEA study, three relatively “good” years emerge (2015, 2016, 2018) and two “bad years” (2017, 2019). This analysis will be useful for further research on the effect of health policies on hospital efficiency in other countries and periods.

Background In recent years, parametric and non-parametric methods, especially the SFA, have been used at an increasing rate to measure efficiency in the health sector in the cases of political systems transition or with emphasis on the impact on the economic crisis or other types of crises.The purpose is the literature review of efficiency studies using the Stohastic Frontier Analysis (SFA) with emphasis on inputs and outputs, so that the resulting knowledge can be used for further efficiency study using the SFA method. Methods The data used in the study were derived from literature review of efficiency studies using the SFA method in Pubmed, Scopus, Heal-Link and Google scholar databases. The study was designed to review literature efficiency studies conducted using the SFA method and to perform meta-analysis of the findings of these studies. The data were extracted and then the stated methodology of the research was applied following the PICOS model protocol.The meta-analysis of the data obtained from the literature overview was analyzed using the KNIME software. Results Efficiency studies with SFA show great heterogeneity due to the different models used in them and the different areas in which they are performed. Most frequently found inputs and outputs in the reviewed studies were identified.Using KNIME software,the dominance of the classic SFA models in theefficiency assessment was shownand the overwhelming superiority of using SFA to measure Technical Efficiencywas shown also. Proposals for policy interventions are heterogeneous and can be classified into different levels of policy interventions. Conclusions The main inputs – outputs used in the efficiency studies with SFA were identified. Efficiency is basically high. The proposals for political interventions are classified at political, managerial and operational levels.

Introduction: Through data analysis of the literature we aim to answer the central question that fills a gap in the literature: Do the methods used to interpret political behaviour in Southern Europe lead to homogeneous results for the political attitudes? Methods: For this systematic review, we searched PubMed, Scopus, Heal-link, Register PROSPERO, and forward and backward citations for studies published between databases inceptions and May 30, 2024. We included studies reporting on political science and quantitative methods, without date or country restriction. We planned to extract results on studies' reporting on the impact of quantitative methods on political behavior. We used the open-source software KNIME. We ranked the studies according to their characteristics. Main findings: We classified the variables for voting behavior, quantitative analysis and we performed cluster analysis and sorted the variables for the different methods of quantitative analysis. We performed a cluster analysis and classified the studies into 3 categories. The studies using Quantitative Analysis in the interpretation of political behavior positively correlate the use of quantitative methods by using correlation with p-value (p = 0.985, < 0.015) and negative Methodology variables of quantitative analysis with the extent of using quantitative methods (p=-0.962,<0.038) and the reporting of political behaviour in the findings using quantitative method in which a p-value correlation is used (p=-0.908, < 0.092). The studies show that the application of quantitative research is usually done using correlation analysis, but the application this recedes in studies of general quantitative behaviour. Discussion: Clustering of the studies showed that studies were classified into three categories. The heterogeneity in the studies is due to the variation in their targeting. Future growth of studies in the region will lead to a reassessment of the situation. Conclusions: A heterogeneity in methodology was found among the included studies. Although the studies used the quantitative methods in a similar way, variations in the independent variables lead the studies to different conclusions. The survey question was answered in negatively: studies using quantitative analysis to explain political behaviour are not homogeneous. The social impact and the contribution of research to political decision-making is important.

Introduction: Maritime safety has evolved from reactive measures to proactive risk management. Despite the implementation of frameworks like the Formal Safety Assessment (FSA), maritime accidents continue to pose significant risks to occupational health and the environment. Recent global empirical studies, spanning from the South China Sea to North Atlantic shipping lanes, corroborate that these risks are not regionally isolated but represent a systemic challenge in modern seafaring. Unlike standard institutional reports (e.g., EMSA, ELSTAT) which primarily provide descriptive statistics, this study introduces an integrative analytical framework that correlates vessel age with specific human-machine interaction failures. Methods: By identifying a distinct 'risk threshold' at 20 years and proposing the 'reliability paradox' in automated systems, this research offers a methodological breakthrough in understanding how structural decay and technological dependency converge to influence maritime risk. The research employed a mixed-methods approach to correlate accident categories—such as collisions and hull failures—with vessel age and human-related causal factors. Results: The findings indicate that while incident frequency has risen, severity in terms of total ship losses has significantly decreased. The "human element" remains the primary catalyst, involved in approximately 75% of global incidents and 59.1% of the refined national study sample. A critical structural risk threshold was identified at 20 years of vessel age, beyond which the probability of hull failure and serious casualties indicates a sharp upward trend. Furthermore, a significant divergence in safety trends was observed, as the vast majority of recorded maritime fatalities occurred in coastal areas and were non-occupational, whereas occupational fatalities on commercial cargo ships and tankers remained remarkably low. The study proposes the emergence of a 'reliability paradox in mid-aged vessels (5–25 years), where increased reliance on advanced bridge automation is linked to higher collision risks due to diminished situational awareness. Conclusion: Enhancing maritime occupational safety requires a transition toward predictive analytics and AI-driven monitoring. Policy interventions should address the safety disparity between the commercial and fishing sectors and prioritize the optimization of human-machine interaction. This study underscores the need for targeted training to mitigate cognitive load and ensure the safety of the maritime profession in the digital age.

Background/Objectives: Although the Robin Hood Index (RHI) is increasingly used to quantify geographic health inequality and guide resource redistribution, empirical evidence on whether higher physician density reduces RHI-measured inequality remains limited. This study systematically reviews and meta-analyzes RHI-based research to assess the association between physician distribution and health inequalities. Methods: We conducted a systematic review and meta-analysis of studies using the RHI to evaluate health inequalities, without restrictions on country or publication date. Following PRISMA 2020 guidelines and registered in PROSPERO (CRD42024496486), we searched PubMed, Scopus, and OpenGrey literature, extracted data on physician density and RHI outcomes, and conducted a meta-analysis. Odds ratios (ORs), ln(OR), and 95% confidence intervals (CIs) were calculated, and risk of bias was assessed using the Robvis tool. Results: Seventeen studies covering 720 regions and 1.07 billion individuals were included. Three clusters emerged: physician redistribution (10 studies), poverty–mortality associations (six studies), and systematic reviews (one study). Physician redistribution was strongly associated with increased inequality and policy attention (r = 0.73; p = 0.0038). Meta-analysis of eight redistribution studies yielded a pooled OR of 1.24 (95% CI: 0.54–2.86), consistent in sensitivity analysis (OR = 1.26; 95% CI: 0.56–2.89). Poverty–mortality studies also showed a correlation with the number of variables considered (r = 0.59; p = 0.022). Conclusions: A greater physician supply is associated with increased health inequalities, with statistical support but limited certainty. Methodological heterogeneity in RHI-based studies constrains comparability. Standardized methodologies and broader analytic models are needed to inform research and guide health policy.

Introduction: Bronchoalveolar lavage (BAL) is a fundamental diagnostic procedure for evaluating diffuse parenchymal lung diseases (DPLDs). However, its diagnostic precision is critically dependent on the integration of a detailed occupational history. Occupational exposures are frequently overlooked in clinical practice, leading to potential misdiagnosis. Methods: We conducted a retrospective analysis of 210 BAL samples from 207 patients over one calendar year at a tertiary referral hospital in Attica, Greece. Data regarding demographics, smoking status, and occupational history (classified via ISCO-08) were correlated with BAL cytology using descriptive statistics, χ² tests, t-tests, and one-way ANOVA with post-hoc comparisons. Missing data were supplemented through extensive record review and patient interviews. Results: Occupational history was absent in 79.5% of initial clinician referrals. Upon data completion, 23.3% of patients were identified as active workers. Workers in the agricultural and forestry sector (ISCO-08 Group 6) showed significantly higher total BAL cell counts (P = 0.025) and specific cytological patterns, including increased macrophages and mast cells. While smoking significantly altered differential counts, it did not influence the total cell count. Conclusion: Specific BAL profiles are associated with certain occupational groups, yet a significant gap in history-taking persists. Systematic occupational assessment is mandatory to improve the diagnostic utility of BAL in respiratory medicine. These findings suggest that BAL can serve as a valuable 'sentinel tool' for occupational surveillance in respiratory medicine.