ABSTRACT
Healthcare systems worldwide are confronted with numerous challenges such as an aging population, an increasing number of chronically ill patients, innovations as cost drivers and growing cost pressure. The COVID-19 pandemic causes additional burden for healthcare systems. In order to overcome these challenges, digital technologies are increasingly used. Especially the past decade witnessed a tremendous boom of artificial intelligence (AI) within the healthcare sector. AI has the potential to revolutionize healthcare and to mitigate the challenges healthcare systems are confronted with. The existing literature has frequently examined specific benefits of AI within the healthcare sector. However, there are still research gaps according to different application areas in healthcare. For this reason, an empirical study design has been conducted to investigate the potentials of AI in healthcare and to consequently identify its role. Based on a Systematic Literature Review (SLR), the following application areas for key determinants in healthcare have been identified: management tasks, medical diagnostics, medical treatment and drug discovery. By means of structural equation modeling (SEM), the study confirmed medical diagnostics and drug discovery as positive and significant influencing factors on the potential benefits of AI in healthcare. The other determinants didn't prove a significant influence. Based on the findings of the study, various recommendations have been derived to further exploit the potentials of AI in healthcare. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Demographic change, shortage of qualified employees and increasing cost pressure—the healthcare sector has to deal with various challenges. Coping with the current COVID-19 pandemic is an additional issue. All these barriers contribute to the fact that digitalization in the healthcare sector is moving forward more and more. Without the application of advanced technologies, healthcare organizations would reach their limits. In this context, the use of AI is becoming increasingly important. The potentials are wide-ranging and include applications in diagnostics and therapy, as well as the development of pharmaceuticals. But what challenges are associated with the use of AI in healthcare? Within the framework of a qualitative empirical study according to Mayring, this question has been investigated. Based on a systematic literature review, the following barriers of AI in healthcare have been identified and examined: Disagreement in data protection, lack of compatibility with ethical aspects, quality of training data, knowledge, and trust of physicians in AI-supported systems. The next step in the research design have been expert interviews among medical staff as well as AI developers with focus on AI in the healthcare sector mainly in Germany. According to these interviews, the data are analyzed and evaluated. Based on the results of the study, potential activities have been derived in order to be able to successfully overcome the barriers of AI in the healthcare sector in the future. Finally, the opinions of physicians and developers on the identified barriers are compared and discussed. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Demographic change, shortage of qualified employees and increasing cost pressure—the healthcare sector has to deal with various challenges. Coping with the current COVID-19 pandemic is an additional issue. All these barriers contribute to the fact that digitalization in the healthcare sector is moving forward more and more. Without the application of advanced technologies, healthcare organizations would reach their limits. In this context, the use of AI is becoming increasingly important. The potentials are wide-ranging and include applications in diagnostics and therapy, as well as the development of pharmaceuticals. But what challenges are associated with the use of AI in healthcare? Within the framework of a qualitative empirical study according to Mayring, this question has been investigated. Based on a systematic literature review, the following barriers of AI in healthcare have been identified and examined: Disagreement in data protection, lack of compatibility with ethical aspects, quality of training data, knowledge, and trust of physicians in AI-supported systems. The next step in the research design have been expert interviews among medical staff as well as AI developers with focus on AI in the healthcare sector mainly in Germany. According to these interviews, the data are analyzed and evaluated. Based on the results of the study, potential activities have been derived in order to be able to successfully overcome the barriers of AI in the healthcare sector in the future. Finally, the opinions of physicians and developers on the identified barriers are compared and discussed. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Healthcare systems worldwide are confronted with numerous challenges such as an aging population, an increasing number of chronically ill patients, innovations as cost drivers and growing cost pressure. The COVID-19 pandemic causes additional burden for healthcare systems. In order to overcome these challenges, digital technologies are increasingly used. Especially the past decade witnessed a tremendous boom of artificial intelligence (AI) within the healthcare sector. AI has the potential to revolutionize healthcare and to mitigate the challenges healthcare systems are confronted with. The existing literature has frequently examined specific benefits of AI within the healthcare sector. However, there are still research gaps according to different application areas in healthcare. For this reason, an empirical study design has been conducted to investigate the potentials of AI in healthcare and to consequently identify its role. Based on a Systematic Literature Review (SLR), the following application areas for key determinants in healthcare have been identified: management tasks, medical diagnostics, medical treatment and drug discovery. By means of structural equation modeling (SEM), the study confirmed medical diagnostics and drug discovery as positive and significant influencing factors on the potential benefits of AI in healthcare. The other determinants didn’t prove a significant influence. Based on the findings of the study, various recommendations have been derived to further exploit the potentials of AI in healthcare. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
The COVID-19 crisis affected society and economy worldwide and has an increasing influence on all industry sectors. That opens up completely new digital business models and does not stop at people’s payment behavior. New payment options such as Apple Pay, Amazon Pay, and others enable people to pay without cash. The aim of this research project is to identify what effects the COVID-19 crisis has on people’s behavior with regard to contactless payment. It will be investigated whether the participants are increasingly using contactless payment options due to the COVID-19 crisis and what advantages and disadvantages are associated with the options. Since there are hardly any studies on this topic at the current time, this paper strives to fill this research gap. For this purpose, the authors have conducted a quantitative study. The hypothesis framework is derived from literature research. The resulting study was conducted with 528 participants. Study analysis show that the vast majority of hypotheses have a significant impact on the potential of contactless payment systems. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.