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The definition of a healthcare system evolves continuously, becoming broader and more complex with each rendering. Healthcare systems can consist of many different elements, including but not limited to: access to comprehensive medical care, health promotion, disease prevention, institutional framework, financing schemes, government responsibility over health, etc. In light of its broad classification of healthcare, this book focuses on a wide spectrum of health-related issues ranging from risk factors for disease to medical treatment and possible frameworks for healthcare systems. Aging populations, increasing costs of healthcare, advancing technology, and challenges created by the COVID-19 pandemic require an innovative conceptual and methodological framework. By combining the experience and effort of researchers from a variety of fields including mathematics, medicine and economics, this book offers an interdisciplinary approach to studying health-related issues. It contributes to the existing literature by integrating the perspective of treatment with the economic determinants of health care outcomes, such as population density, access to financial resources and institutional frameworks. It also provides new evidence regarding the pharmaceutical industry including innovation, international trade and company performance.

Contributors are: Sayansk Da Silva, Joe Feinglass, Scott W. Hegerty, Joseph E. Hibdon, Jr, Arkadiusz Michał Kowalski, Małgorzata Stefania Lewandowska, Dawid Majcherek, Ewelina Nojszewska, Izabela Pruchnicka-Grabias, Agata Sielska and Julian Smółka.

Abstract

Because limited financial access has been shown to be associated with adverse public health outcomes in the United States, modeling this access and identifying geographic areas where it is deficient is essential. Recent research on the locations of bank branches has identified thresholds below which a given area can be considered to be a “banking desert.” Thus far, most analyses of the country as a whole have tended to focus on minimum distances from geographic areas to the nearest bank, while a recent density-based analysis focused only on the city of Chicago. As such, there is not yet a nationwide study of bank densities for the entire United States. This study calculates banks per square mile for US Census tracts over ten different ranges of population density. One main finding is that bank density is sensitive to the measurement radius used (for example, density in urban areas can be calculated as the number of banks within two miles, while some rural areas require a 20-mile radius). This study then compiles a set of lower 5- and 10-percent thresholds that might be used to identify “banking deserts” in various urban, suburban, and rural areas; these largely conform to the findings of previous analyses. Finally, adjusting for population density using regression residuals, this chapter examines whether an index of economic deprivation is significantly higher in the five percent of “desert” tracts than in the remaining 95 percent. The differences are largest – and highly significant – in the densest tracts in large urban areas.

Open Access
In: Economics and Mathematical Modeling in Health-Related Research
In: Economics and Mathematical Modeling in Health-Related Research

Abstract

The aim of this chapter is to identify a pattern of international trade in medical products in the context of tackling the COVID-19 pandemic. Medical products are grouped according to classifications of the World Trade Organization into four categories: pharmaceuticals, medical equipment, medical consumables, and personal protective products. This study focuses on the international trade of pharmaceuticals, which represents over a half of the total value of medical product trade. The United States, Germany, and Switzerland are key players regarding exports of medical products; however, the leaders differ in exports of the four medical product groups. Switzerland holds a predominant position in exports of pharmaceuticals, the US leads in exports of both medical equipment and medical consumables, while China is the world’s top exporter of personal protective products, occupying the 7th place in total exports of medical products. The analysis of Revealed Comparative Advantage (RCA) indices showed that high trade values do not necessarily translate into specialization in trade. Switzerland and Ireland are the world’s leaders in terms of relative trade specialization in medical products, in particular they enjoy high comparative advantages in trade of pharmaceuticals. The US and China, although both have relative specialization in overall medical exports, do not reveal comparative advantages in trade of pharmaceuticals.

Open Access
In: Economics and Mathematical Modeling in Health-Related Research

Abstract

The chapter focuses on the development of healthcare and pharmaceutical industry analyzed from the perspective of the innovation divide in the world economy, as there are traditionally countries with developed national innovation systems, playing the role of technology leaders, and those with developing innovation systems, acting as innovation followers. However, together with significant structural changes taking place in the world economy, we observe a gradual shift of high-technology industries, such as the pharmaceutical industry, to emerging economies, among which China is making a considerable progress in innovation performance. The objective of this research is to measure the development of healthcare and pharmaceutical industry in economies traditionally playing the role of technological followers, that is, China and Poland, and economies positioned as innovation leaders, that is, the EU and the USA. According to the results, the development of the healthcare sector in emerging economies, in particular China, is positively associated with economic growth, and innovations in the pharmaceutical industry are critical to the present and future advances in healthcare.

Open Access
In: Economics and Mathematical Modeling in Health-Related Research
Author:

Abstract

The aim of this chapter is to search for common institutional traits that improve the efficiency of healthcare systems in developed countries. The study joins the broad discussion on the topic of limiting costs and accelerating effects of healthcare systems. An extensive review of the literature and statistical sources is used to create the institutional framework for healthcare systems in the United States, the United Kingdom, Germany, Sweden, Singapore, and Poland – developed countries selected for differences in socio-economic conditions of health care as well as diverse models of capitalism. Based on the characteristics specified during research, a comparative analysis of institutional traits was performed. This allowed the identification of similarities that improve the efficiency of healthcare systems in developed countries (as measured by the provision of satisfactory services at acceptable levels of cost). The institutional traits and patient navigation within the healthcare systems of Singapore and Sweden appear to be most effective in increasing system efficiency. Other selected features from the remaining countries were also brought up. Wide implementation of the presented institutional traits may help reduce the burden of health care costs while maintaining high quality services.

Open Access
In: Economics and Mathematical Modeling in Health-Related Research
In: Economics and Mathematical Modeling in Health-Related Research

Abstract

In Horizon 2020, the biggest European Union research and innovation funding program with of budget of nearly €80 billion for the period 2014–2020, one of challenges is Health, Demographic Change and Wellbeing which “aims to keep older people active and independent for longer and support the development of new, safer and more effective interventions. [It] also contributes to the sustainability of health and care systems” (EuroAccess, 2022). The aim of this chapter is to investigate how effective the European Union investments are, taking into account the measurable outcomes in accordance with the expected targets. The analysis is based on the input financial data obtained from EU Contact Points covering 314 Health projects completed by December 2020. The output data are divided into four groups: economic (patents, prototypes); academic (publications, PhD dissertations), health (new drugs, new healthcare solutions, final reports, conferences), and media (press releases). Data are collected in the Cordis project database and matched with financial data. The results show that such an assessment has multiple drawbacks and does not provide a rich picture of the program outcomes, leading to the conclusion that more advanced and holistic techniques have to be implemented, especially those based on big data analysis.

Open Access
In: Economics and Mathematical Modeling in Health-Related Research

Abstract

The aim of the study is to analyze pharmaceutical companies quoted on the Warsaw Stock Exchange as part of the investment portfolio in order to check whether their stocks can be used as a diversification tool for investors. Traditional and alternative performance measures are calculated to conclude that results are different for different time periods; however, in each of them it was possible to choose some companies which performed better than the benchmark WIG20TR index according to all applied performance measures. This suggests that pharmaceutical companies can be good diversifying assets for other equity investments. The study is original and unique because the literature usually offers research based on fundamental factors, such as different financial ratios calculated for pharmaceutical companies when performance is analyzed. Authors do not consider their performance on stock exchanges. However, analyzing stock market fluctuations is important because performance is not only based on financial ratios but also on investor sentiment and behavior of market speculators who often make market prices deviate from their fundamental values based on the traditional financial analysis. The considered study period starts in January 2017 and ends in June 2021. It was the maximum time span available for the analysis because some companies are quite young. The study is based on weekly data to avoid daily market fluctuations because the main assumption is that the investment period is either medium or long. The analysis may help investors and capital diversification seekers to optimize their investment decisions.

Open Access
In: Economics and Mathematical Modeling in Health-Related Research
Author:

Abstract

This chapter presents findings from two health equity studies of the social epidemiology of cancer in the United States. Both these studies were designed to provide a framework for further ecosocial research on racial, ethnic, and socioeconomic disparities in health in the United States. Findings from these studies have provided a framework for a new generation of health equity research underway at the NIH-funded Chicago Cancer Health Equity Collaborative, a collaborative of three Chicago area universities focused on cancer research. The chapter describes two specific modeling approaches to the social epidemiology of lung and breast cancer. Our breast cancer study analyzed all cause survival data from 1630 hospitals and almost 600,000 breast cancer patients from the National Cancer Database (NCDB), maintained by the American College of Surgeons and the American Cancer Society. Patients diagnosed between 1998 and 2006 were followed up to 14 years through 2011. Our research sought to determine the magnitude of socioeconomic effects on all-cause mortality, adjusting for clinical risk factors, like cancer stage at diagnosis. Was there a ‘gradient’ of mortality across our synthetic measure of socioeconomic status? Lung cancer accounts for one quarter of all US cancer-related deaths, more than breast, prostate, colorectal, and brain cancer combined. Our lung cancer study used publicly available data form the state of Illinois to investigate racial and ethnic disparities in the epidemiology of lung cancer incidence, mortality, stage at diagnosis, surgical treatment and screening.

Open Access
In: Economics and Mathematical Modeling in Health-Related Research