OBJECTIVE: The aim of this study is to determine the interdependence between life expectancy and numerous social indicators, i.e., to determine the factors that encourage an increase or decrease in life expectancy.
METHODS: Pearson coefficients as well as linear and logarithmic trends and correlations between the dependent variable of life expectancy and numerous independent variables were calculated and analysed. The calculations were carried out for all countries in the world for which data is available. Based on the strength of the correlations between life expectancy and numerous indicators, we have tried to determine the reasons for the different values of life expectancy in the various countries.
RESULTS: Important factors for achieving high life expectancy values are economic development and healthcare spending but the spread of \"diseases of the modern era\", such as obesity or diabetes, have a significant negative impact on life expectancy. Other important limiting factors for life expectancy are large income inequalities, a higher share of private healthcare expenditure in total healthcare expenditure and lower total healthcare expenditure. Less developed societies can significantly increase their life expectancy by providing clean water and safe sanitation and by combating various infectious diseases (especially HIV).
CONCLUSIONS: Life expectancy is a meaningful indicator of the state of social development and accurately reflects the general state of a particular society. It has been shown that GDP per capita (PPP) is a key determinant of life expectancy, while other important factors play the role of a further modifier.

The healthcare sector faces several challenges, such as rising costs, rising demand, and the need for sustainability. A new area of healthcare has emerged due to these problems, focusing on long-term improvements in management, social policy, and health economics. This research explores the cutting edge of healthcare, concentrating on long-term advancements in management, social policy, and health economics. To better understand the problems affecting the healthcare sector and to pinpoint the areas where sustainable solutions are most required, a survey of 2000 healthcare professionals and policymakers was performed. The data were analyzed using structural equation modeling (SEM), and a thorough sustainable healthcare model was created. According to the survey\'s findings, the healthcare sector now faces three significant challenges: growing prices, increased demand, and the need for sustainability. According to the respondents, the three main areas where sustainable innovations are most required are management, social policy, and health economics. These conclusions were supported by the (SEM) analysis, which also showed that sustainable practices in these fields significantly impact the sustainability of the healthcare system. These findings lead this research to conclude that to guarantee the accessibility and affordability of healthcare for everyone, a move towards sustainable practices in health economics, social policy, and management is needed. Cooperation between healthcare providers, policymakers, and other stakeholders is required to create creative solutions that support sustainability in the healthcare sector. This study offers a thorough framework for sustainable healthcare that may act as a guide for further research and the formulation of new regulations.

The dramatic growth in the rate of diabetes prompts serious debates about awareness, early diagnosis, and care interventions. This Viewpoint aims to explore, from the perspectives of healthcare sector representatives, what challenges and difficulties they face in dealing with diabetes and how these can be overcome. We applied the World Café method for group discussions, which enabled us to bring together 50 stakeholders. They identified challenges at institutional and structural levels under the concepts of awareness, digitalisation, and new forms of care and shared their suggestions for feasible solutions. We learned there is a need for a diabetes map of Germany to identify risk groups and that hybrid solutions should be implemented for treatment, care, prevention, and early diagnosis, considering digital infrastructure. Also, the demand for digital innovation in the healthcare system raised concerns about information transparency and data management.

BACKGROUND: Within many advanced healthcare systems, patient advocacy associations are gaining a more relevant role in healthcare policy decisions. These associations provide help, representation, and voice to patients and citizens. However, although their role is important, a paucity of research exists analyzing their foundation dynamics, including their organizational decision, from a managerial perspective. To fill this knowledge gap, we formulated two research questions to investigate the motivations underlying the foundation of patient advocacy associations and the institutional pressures influencing the changes that have occurred in these associations throughout their evolution.
METHODS: Using a semi-structured questionnaire developed as part of a larger research project, we collected data about 31 patient advocacy associations operating within the Italian National Health Service. We employed qualitative analysis to examine the associations\' birth and evolution as well as the motivations and influences driving change within the sampled organizations.
RESULTS: Questionnaire responses provided information about the patient advocacy associations\' histories and highlighted their close links with the Italian National Health Service. Our results indicated the motivations for the associations\' establishment could be grouped into five categories: support at the system level, patient protection and support, actions to increase awareness, actions for improving patients\' health and quality of life, and dissemination of knowledge. We also identified the frequency and nature of the changes within the associations and explored the institutional pressures that influenced these organizational changes.
CONCLUSIONS: The results can be interpreted considering the organizational theories that focus on organizations\' establishment decisions and how external pressures impact organizations\' dynamics and evolution.

BACKGROUND: The healthcare sector has an environmental impact of around 4.6% of global CO2 emissions, contributing to aggravating the climate crisis. However, the impact of the health sector\'s emissions on human health is not regularly assessed. We aim to estimate the health burden and associated costs of the health sector\'s carbon footprint within the European Union (EU).
METHODS: We calculated disability-adjusted life years (DALYs) and associated costs based on human health damage factors (DALYs/kg-CO2e) by considering four scenarios. Three scenarios for shared socioeconomic pathways (S1 - high growth, S2 - baseline, and S3 - low growth) represented variations of global society, demographics, and economics until 2100. A fourth scenario (S4) considered the current EU\'s 55% reduction goal of greenhouse gas emissions. The healthcare sector\'s emissions per capita (in CO2-equivalent) in 2019 were extracted from the Lancet Countdown, and population data were retrieved from Eurostat for the same year.
RESULTS: In the EU, 365,047 DALYs (95%CI: 194,692-535,403) are expected to be caused by the health sector\'s emissions at baseline (S2). In an S1 scenario, the burden would slightly decrease to 316,374 DALYs (95%CI: 170,355-462,393), whereas a S3 scenario would increase 486,730 DALYs (95%CI: 243,365-681,422). If EU\'s carbon goals are met, the burden could be substantially reduced to 164,271 DALYs (95%CI: 87,611-240,931). Costs can amount to 25.6 billion euros, when considering DALYs monetisation.
CONCLUSIONS: CO2 emissions from the health sector are expected to significantly impact human health. Therefore, it is important to ensure that EU climate policies for public buildings are in line with the Paris Agreement, increase funding for climate mitigation programs within the healthcare sector, and review clinical practices at the local level.

The purpose of this study is to investigate the effect of medical tourism revenues on the growth of healthcare sector across 49 emerging and developed economies from 2008 to 2022. Using panel GMM and PMG/ARDL estimation methods, the results show that higher levels of medical tourism revenues promote growth in the healthcare sector. This finding remains robust across different sample periods, alternative measure of healthcare sector performance, and model specifications.

The growing and ubiquitous digitalization trends embodied in eHealth initiatives have led to the widespread adoption of digital solutions in the healthcare sector. These initiatives have been heralded as a potent transformative force aiming to improve healthcare delivery, enhance patient outcomes and increase the efficiency of healthcare systems. However, despite the significant potential and possibilities offered by eHealth initiatives, the article highlights the importance of critically examining their implications and cautions against the misconception that technology alone can solve complex public health concerns and healthcare challenges. It emphasizes the need to critically consider the sociocultural context, education and training, organizational and institutional aspects, regulatory frameworks, user involvement and other important factors when implementing eHealth initiatives. Disregarding these crucial elements can render eHealth initiatives inefficient or even counterproductive. In view of that, the article identifies failures and fallacies that can hinder the success of eHealth initiatives and highlights areas where they often fall short of meeting rising and unjustified expectations. To address these challenges, the article recommends a more realistic and evidence-based approach to planning and implementing eHealth initiatives. It calls for consistent research agendas, appropriate evaluation methodologies and strategic orientations within eHealth initiatives. By adopting this approach, eHealth initiatives can contribute to the achievement of societal goals and the realization of the key health priorities and development imperatives of healthcare systems on a global scale.

UNASSIGNED: Evidence shows that routine occupational safety and health (OSH) training is critical for maintaining good safety culture at healthcare facilities. However, our understanding of how healthcare facility type and routine OSH training interactively influence the number of reported organizational safety culture perceptions is limited.
UNASSIGNED: This study assesses the interactive effect of healthcare facility type and OSH training on the number of reported organizational safety culture perceptions of healthcare workers in Ghana, secondly it evaluates how the relationship was attenuated when theoretically relevant factors (compositional and contextual) were considered, and lastly examines the magnitude and order of association between the predictors and the number of reported organizational safety culture perceptions.
UNASSIGNED: Cross-sectional interview study.
UNASSIGNED: The researchers interviewed 500 healthcare workers in seventeen healthcare facilities in the Central region of Ghana.
UNASSIGNED: Negative binomial regression models were fitted to cross-sectional survey data on 500 healthcare workers in Ghana.
UNASSIGNED: Healthcare workers who work in healthcare centers (24%, P<0.05) and hospitals (23%, P<0.05) where routine OSH training was conducted were more likely to report good organizational safety culture perceptions compared with their counterparts who work at healthcare centers where no routine OSH training was conducted. Individuals who were above 39 years (23%, P<0.05) were more likely to report good organizational safety culture perceptions compared with their counterparts in the 20-29-year category. Female healthcare workers (11%, P<0.05) were more likely to report good organizational safety culture perceptions compared with their male counterparts.
UNASSIGNED: These findings provide valuable information for policymakers and stakeholders in the healthcare sector to develop interventions necessary for improving safety culture at healthcare facilities.

Artificial intelligence has led to significant developments in the healthcare sector, as in other sectors and fields. In light of its significance, the present study delves into exploring deep learning, a branch of artificial intelligence.
In the study, deep learning networks ResNet101, AlexNet, GoogLeNet, and Xception were considered, and it was aimed to determine the success of these networks in disease diagnosis. For this purpose, a dataset of 1,680 chest X-ray images was utilized, consisting of cases of COVID-19, viral pneumonia, and individuals without these diseases. These images were obtained by employing a rotation method to generate replicated data, wherein a split of 70 and 30% was adopted for training and validation, respectively.
The analysis findings revealed that the deep learning networks were successful in classifying COVID-19, Viral Pneumonia, and Normal (disease-free) images. Moreover, an examination of the success levels revealed that the ResNet101 deep learning network was more successful than the others with a 96.32% success rate.
In the study, it was seen that deep learning can be used in disease diagnosis and can help experts in the relevant field, ultimately contributing to healthcare organizations and the practices of country managers.

OBJECTIVE: In many countries, outpatient and inpatient care are separated. During hospitalization, therefore, switching the outpatient medication to medication of the hospital formulary is required.
METHODS: We newly designed a switching algorithm in six switching steps (S0-S5) and conducted a study at Bundeswehr Hospital Hamburg (300 beds, 80% civilians). We performed (i) a medication reconciliation to obtain information on outpatient medications and (ii) a medication review to solve drug-related-problems, e.g., drug-drug interactions. We applied (iii) the algorithm to switch medications to the hospital formulary.
RESULTS: (i) We identified 475 outpatient medications (median per patient: 4; Q25/Q75 2/7) in 100 patients consecutively admitted to hospital (median age: 71; Q25/Q75: 64/80 years). Of 475 medications, the switching algorithm could not be used since product names were missing in 23.9% and strength in 1.7%. In 3.2%, switching was not required since medication was not prescribed during the hospital stay. (ii) Drug-drug interactions were identified in 31 of 79 patients with more than one medication. (iii) Of 475 medications, 18.5% were on the hospital formulary and therefore did not need to be  switched (S0), 0.2% were on a substitution-exclusion list not allowing switching (S1), 42.0% were switched to a generic medication of the hospital formulary (S2), 1.7% to a therapeutically equivalent medication (S3), 0.4% were patient-individually switched (S4), and for 8.2% a standardized/patient-individual switching was not possible (S5).
CONCLUSIONS: Despite comprehensive medication reconciliation, patient- and medication-related information for switching medications to the hospital formulary was often missing. Once all the necessary information was available, standardized switching could be easily carried out according to a newly developed switching algorithm.