Towards European Modern Societies with Health Systems That Are Able to Add More Years to Life, But Also to Add More Life to Years

The political context in Europe is changing including health. Among the priorities in seeking to influence the future of healthcare is a renewed attachment to health for all, health in all policies and a better coordination between social and health policy. Health issues are by definition international, and Europe has a duty to extend solidarity to the wider world population, in strategy and in delivery. Ensuring equitable access to high-quality healthcare constitutes a key challenge for health systems throughout Europe. The chapter will emphasise the importance of European public health policies. The chapter will offer a real opportunity to address public health areas and values such as right to access to healthcare into the detailed mechanisms of European policy. The chapter will form a tool for health leaders, to enrich their knowledge in the public health spectrum from a European perspective, to support, promote and improve healthcare access at a national level.

Hospital Units Merging Reasons for Conflicts in the Human Resources

The necessity for the control of expenses of health and the reduction of cost, led the Ministry of Health and the government of Greece to the decision-making for fusions of hospitals units of health following the new tendency of health's policy that prevails also in other countries. The research purpose was to appoint the positive and negative results from the fusions of hospitals. Any changes in the health care system aim at the reduction of expenses, however, they constitute the most frequent causes of conflicts among employees. The Hospital is characterized as a natural space for the growth of conflicts. Despite the oppositions that are recorded as for the positive and negative results, it appears finally that through the fusions, resources have been saved, management systems have been improved but in the same time, conflicts in the labour place between the individuals and the teams recruiting hospitals have been aggravated.

Surgery Operations Modeling and Scheduling in Healthcare Systems

Surgery operations scheduling is a complex task due to operation duration uncertainties and resource sharing and availabilities in healthcare processes. In current health care systems it is important to minimize staff idle time and maintain a high utilization rate for surgery facilities. In the present study a nonlinear mathematical model for surgery scheduling is described, and an approximated linear model is deduced based on a set of assumptions. The linear model is solved using heuristic approach. The objective is to maximize the utilization of operating rooms and the surgery staff. Computational results show that our model improved the surgery schedule and the resources utilization. Our model also showed the potential of adding cases to the schedule due to minimizing the completion time of the schedule.

Examining the Influence of Information Technology on Modern Health Care

Health care costs continue to rise at a level that far exceeds the rate of inflation. IT will be necessary in the computation and organization of complex algorithms presented in bundled payments and other initiatives. Currently in health care, a patient's medical history is not easily accessible by physicians and other medical personnel. IT can play the pivotal role in rectifying this problem in tracking the record in a universally designed environment. Advanced databases are needed to integrate facilities within health care systems. This chapter is to explore the current framework of Information Technology in the U.S. health care industry and to examine the topic covering the following areas: (a) IT's influence on the Affordable Care Act, (b) the emergence of the Electronic Health Record (EHR), also known as the Electronic Medical Record (EMR), and (c) the integration of databases across health care organizations through advanced systems like Epic.

Modelling Spatial Medical Data

Models are sometimes incomplete, especially in scaling data where other information of large regions needs to be predicted by smaller ones. Uncertainty analysis is the process of assessing uncertainty in modelling or scaling to identify major uncertainty sources, quantify their degree and relative importance, examine their effects on model output under different scenarios, and determine prediction accuracy. Especially for large dimensional data where spatial process in regional investigation are difficult to applied due to incompleteness leading us to spatial heterogeneity and non-linearity of our data. Modelling the uncertainty particular in scaling data starts with a general structure (linear most of the time) that explains as accurate as it is the real data and the model is built through adding variables, which are significant or which aid in prediction (hierarchical modelling). Parameter estimation is an important issue for the evaluation of these proposed models. Statistical techniques based on the spatial modelling could be proposed to overcome the problem of dimensionality and the spatial homogeneity between different grains levels based on the neighbourhood structure of the regions with similar characteristics. Investigation of the neighbourhood structure analysis could be applied using kriging or variogram techniques. In this work, we introduce and analyse methodologies for scaling data under uncertainty where incomplete data can be explained by spatial modelling at different scales. Incomplete data of uncertainties in regions involve spatial homogeneity upon neighbourhood structure between regions. The last could be illustrated by using spatial modelling techniques (like spatial autocorrelation, partition functions, and multilevel models). Parameter estimation of these models could be achieved by using stochastic (spatial hierarchical models, kriging, auto-correlation) methods. Comparison between different models could be achieved by considering statistical measures like log-likelihood ratio test. The best model is the one, which explains better the real data.

Health Services Quality and Patient Satisfaction

Quality of care from the patient's perspective and patient satisfaction are two major multidimensional concepts that are used several times interchangeably. Patient satisfaction is a topic that is important both to medical (health) providers, the patients (consumers) and other third-party stakeholders in the medical care industry; it is, therefore, a dominant concept in quality assurance and quality improvement programmes. Patient satisfaction is an important measure of healthcare quality because it offers information on the provider's success at meeting the expectations of most relevance to the client. The importance of quality in the health care sector has been recognized recently, but it has been accelerated over the past years through the development of quality assurance, quality improvement programmes and patients' agendas. Patients are the ones situated at the front lines of care; therefore their opinion may provide useful insights into the quality of healthcare in different European systems, nevertheless the methodological limitations that should be taken into consideration.

Geographic Information System Applications in Public Health

Geographic information systems or geographic information science is a combination of computer-mapping capabilities with additional database management/data analysis tools. GIS is widely used in various sectors such as environmental science, urban planning, agricultural applications etc. Public health is another focus area, where GIS has been used for research and practice areas such as epidemic surveillance and monitoring, among others. The journey of use of GIS in public health spans more than a century and GIS application in public health has evolved from the simple maps to the higher level geostatistical analysis and interactive WebGIS in recent times. GIS is an analytical tool which differs from conventional computer-assisted mapping and any statistical analysis programs in its ability to analyze complex data and visual presentation of spatial data. Specialized GIS techniques such as network analysis, location-allocation models, site selection, transportation models, and geostatistical analysis are well established and used in many developed and developing nations. Unfortunately owing to the high cost of licensed software and specialized skills for advanced data analysis, use of these techniques is limited mainly for the research and by few experts. GIS is proved to be useful for various public health practices and research purposes including epidemiological surveys/investigation, implementation research, program/policy decision making and dissemination of information. The advantage of using GIS is that maps provide an added dimension to data analysis, which helps in visualizing the complex patterns and relationships of public health issues, thus many unanswered questions in public health, can be understood well through use of GIS techniques. Use of GIS in public health is an application area still in its infancy. Wider use of GIS for public health practice such as program planning, implementation and monitoring in addition to building evidence base for the policy making will help reduce inequities in health and provide universal healthcare. Overall, GIS is a helpful and efficient tool especially for public health professionals working in low resource settings. In the future with inclusion of advanced GIS technology like WebGIS can help reach the goal of optimal health care services globally.

High-Performance Work Practices in Healthcare Sector

High-performance work practices are described as human resource management practices that augment organizational performance through enhancing employees' competencies, motivation, commitment and productivity. Last decades have seen an increase in both research and practice on high-performance work practices. Yet, they have only recently received attention in healthcare settings. Nascent empirical studies have shown that high-performance work practices may play a vital role in fostering positive employee, patient and organizational outcomes. Given the problematic and limited environment of healthcare organizations, high-performance work practices are purported to be an effective “medicine” for organizational functioning. Thus, the purpose of this chapter is to delineate human resource management policies and their core high-performance work practices and also highlight their key role in ameliorating healthcare organizations' performance. By doing so, we provide some useful insights from healthcare literature in relation to the underlying mechanisms that account for this relationship.

Strategies for Expanding Access and Improving the Quality of Pharmaceutical Services

Pharmaceutical services are among the most accessible healthcare assistance systems worldwide, being provided generally in enterprises like Drugstores and Compounding Pharmacies. Pharmacists are highly accessible healthcare professionals considering also the availability, geographic distribution and location of pharmaceutical enterprises. However, there are several challenges for providing these services for patients with limitations such as low education, difficulties on reaching the Pharmacist, and the need for individualized monitoring (due to the complexity of therapy). Reports of low quality services are growing worldwide, and in order to expand access and improve the quality of pharmaceutical services, Pharmacists must move from being medication dispensers with focus in administrative management to a clinically-oriented practice with a humanistic view. The aim of this chapter is to make an approach on the implementation of effective strategies and ways to improve the quality of Pharmacists' work as specialized healthcare providers.

Organizational Integration of Decision Analytic Methods in Healthcare Settings

Healthcare organizations face a range of external and internal factors that both enable and hinder the organization's ability to provide safe, quality, timely and reliable healthcare services. The accessibility of data coupled with effectively integrated analytic methods can provide healthcare organizations with essential components of a solid framework for improving performance across the full spectrum of organizational contexts. However, data, methods, and a robust information infrastructure are only part of the solution. Healthcare organizations must consider characteristics of the organization and its strategy in order to effectively integrate analytic methods. Conceptual ideas from organizational theory, economics and strategic management can provide structure to the integration process.