How enabling factors determine unmet healthcare needs? A panel data approach for countries.

Health service need refers to the essential care required to achieve optimal health outcomes within resource constraints. When necessary services to address identified health issues are not received, unmet needs arise. This research focuses on the determinants of unmet healthcare needs across the 34 countries within the European region from 2011 to 2019, focusing on Andersen's Behavioral Model's enabling factors. We employed a static and robust panel regression model using Stata 14.0 software. Key determinants analyzed include GDP per capita, urbanization rate, and physicians per capita. Findings reveal that lower GDP per capita and lower urbanization rates are significantly correlated with higher levels of unmet healthcare needs, highlighting income level and geographical accessibility as critical factors. Additionally, a higher number of physicians per capita is associated with reduced unmet healthcare needs, indicating the importance of healthcare resources in addressing healthcare access gaps. These findings underscore the importance of targeted healthcare policies that address income level, improve healthcare accessibility, and enhance healthcare resource allocation to reduce unmet healthcare needs effectively. These findings equip policymakers and administrators with empirically grounded insights to comprehend the factors contributing to unmet healthcare needs and to develop policies aimed at addressing this challenge.

Patient Safety Culture: Effects on Errors, Incident Reporting, and Patient Safety Grade.

OBJECTIVES: This study mainly examines the effects of patient safety culture dimensions on 4 outcomes (self-reported errors, witnessing errors, incident reporting, and patient safety grade). METHODS: The data were collected using the Turkish version of the Safety Attitudes Questionnaire, which consists of 6 dimensions (teamwork climate, safety climate, job satisfaction, stress recognition, perceptions of management, and working conditions). Of 1679 personnel working in 6 hospitals in Ankara, 860 were randomly selected. The data were analyzed using descriptive statistics, the Spearman correlation coefficient, and binary logistic regression analyses. RESULTS: The response rate was 62.7%. When the overall patient safety culture score increased by 1 point; the probability of witnessing an error was 2 times lower (P < 0.001), the probability of incident reporting was 4.22 times higher (P < 0.001), and the probability of assessing the patient safety grade as excellent was 29.86 times higher (P < 0.001). The teamwork climate was negatively related to making errors and witnessing errors (P < 0.001). The safety climate and working conditions were positively related to incident reporting and patient safety grade (P < 0.001). Job satisfaction was negatively related to incident reporting (P < 0.001). Perceptions of management were positively related to making errors and patient safety grade (P < 0.001). CONCLUSIONS: The patient safety culture scores were positively correlated with incident reporting and patient safety grade but negatively correlated with the occurrence of errors. Each dimension of the patient safety culture, except stress recognition, affected different outcomes. Therefore, managers should focus on different dimensions of patient safety culture to improve different outcomes.