JOURNAL OF ORIGINAL STUDIES

Evaluation of risk factors in financial management in healthcare enterprises with multi-criteria decision making analysis

Gülşah Kübra Kolbaşı, Erman Gedikli — Sun, 29 Dec 2024 00:00:00 +0300

The purpose of this study is to determine the main risk factors that are effective in the financial management of healthcare businesses and to evaluate the priority order of these factors using the Analytical Hierarchy Process (AHP). As a result of the literature review, the main risks were listed as market risk, exchange rate risk, liquidity risk, credit risk, inflation risk, competition risk, interest rate risk, legal risk and operational risks. The AHP survey prepared in accordance with the method was filled out by eight different unit managers working in a private hospital. The managers were determined according to the criteria of working in a private hospital, having at least 10 years of experience in the field and being the manager of an administrative department. As a result of the participants' opinions, the weighting order of the criteria was determined as; exchange rate risk (0.18), market risk (15%), liquidity risk (14%), inflation risk (13%), credit risk (12%), interest rate risk (9%), competition risk (8%), legal risk (8%) and operational risk (4%). Within the framework of the findings obtained, it was revealed that hospitals should be formulated in a way that will help them improve their financial management strategies and strengthen risk management. It may also be possible for decision makers to take precautions against risks in the market with integrated strategies that will primarily minimize exchange rate risk and increase liquidity opportunities in line with current conditions. In this way, healthcare businesses that manage financial risks well will be less affected by economic fluctuations in the market, gain more investor confidence, and can find funding more easily and adapt more quickly to changing economic conditions. Developments in this direction not only protect current situations, but also have critical importance for the long-term growth vision.

Scientific mapping of digital twin technology in health: A bibliometric analysis

Umutcan Altun, Tuba Aralan — Sun, 29 Dec 2024 00:00:00 +0300

This study aims to understand the current state and potential of digital twin technology in healthcare, and to provide an overview of scientific research in this area. Digital twin technology is an innovative approach that aims to create digital replicas of physical systems, providing real-time data and insights. In this study, 814 articles retrieved from the Web of Science database using pre-defined criteria were analysed using bibliometric analysis methods. The analyses show that the reviewed articles received a total of 17,122 citations, with an average of 21.03 citations per article. In addition, the H-index of the studies was determined to be 57. The articles were mainly published in high-impact journals such as IEEE Access (48 articles) and Sensors (28 articles). Beihang University (22 articles, 2,753 citations) and Nanyang Technological University (11 articles, 124 citations) were identified as the most influential institutions. Among countries, China and the United States emerged as leaders, with strong collaborations in particular with the United Kingdom, Singapore and Canada. The thematic analysis results indicate that digital twin technology in healthcare focuses on key areas such as 'system integration', 'modelling' and 'design'. In particular, concepts such as 'framework', 'health' and 'management' are frequently explored.

Analysis of personal health data breaches: prioritization with BWM approach

Emre Yılmaz — Sun, 29 Dec 2024 00:00:00 +0300

The aim of this study is to identify the factors that cause personal health data breaches, prioritize these factors with the BWM (Best Worst Method) approach, and propose solutions to improve health data security in line with the priorities obtained. As a result of the literature review, 8 criteria were identified for the evaluation of personal health data breaches: data leakage, human errors, malware, security level (encryption), cyber-attacks, unauthorized access, privilege abuse and inappropriate data destruction policies. The criteria were analyzed using the BMW method, a multi-criteria decision-making approach. The evaluation was conducted by 6 different experts with at least 7 years of academic or professional experience in the fields of health management and health law. According to the findings of the analysis; the most important (best) criterion causing personal health data breaches was determined as “Cyber Attacks” with a weight score of 16.95%. This is followed by “Data Leaks” (16.77%), “Privilege Abuse” (15.10%) and “Malicious Software” (15.07%). “Inappropriate Data Destruction Policies” was identified as the least important (worst) criterion with a weight of 5.01%. As a result, multifaceted strategies need to be developed for preventing health data breaches and effective data security management. Methods such as advanced security measures, regular security audits and network segmentation are recommended against cyber-attacks. Patient identity; privacy can be protected by using a number of methods such as anonymization, clustering of data sets or blurring technique instead of real patient identity. To mitigate the effects of privilege abuse, methods such as role-based access control, monitoring of user activities and regular access audits should be implemented.

Contribution of artificial intelligence based technologies to UN Sustainable Development Goals

Mehtap Polat — Sun, 29 Dec 2024 00:00:00 +0300

The rapid development of technologies in recent years has the potential to transform social and economic conditions by reshaping the world of innovation. However, while some of these technologies are commercialised and benefit society, others remain at the academic level. It is essential that new technologies are transformed into products that add value to the economy and deliver tangible benefits. The United Nations Sustainable Development Goals (SDGs) provide a framework that promotes social, environmental and global sustainability, as well as economic development.

Artificial intelligence stands out as an important technology that offers solutions to both social and economic problems, contributing to sustainable development. In particular, AI-based solutions to global problems such as hunger, poverty, inequality and violence offer opportunities for building a sustainable world. However, although a significant proportion of high technologies are developed in universities, they remain at the academic level. Patents, as one of the tangible outputs of this process, are a critical tool for measuring innovation and monitoring technological development. As a source of prestige for universities, patents also play an important role in the transformation of technology into societal benefits.

The study is a qualitative study, and the data obtained through content analysis will be categorised. This study aims to identify the relationship between the country's innovation ecosystem and the SDGs, by analysing the AI-based technological patent portfolios of universities in Turkey. The study will examine the areas in which innovative technologies are concentrated, and the SDGs to which these technologies contribute. The findings will contribute to the strategic planning of universities and Turkey's development policies, strengthening the link between technology and sustainability.

This study aims to identify the relationship between the country's innovation ecosystem and the SDGs, by analysing the AI-based technological patent portfolios of universities in Turkey. The study will examine the areas in which innovative technologies are concentrated, and the SDGs to which these technologies contribute. The findings will contribute to the strategic planning of universities and Turkey's development policies, strengthening the link between technology and sustainability. The study is a qualitative study, and the data obtained through content analysis will be categorised.