Change management: a framework for adaptation of the change management model

Digital health change management projects have a high rate of failure which limits the realization of their potential benefits. While there are many change management models, there is limited evidence of one model being effective in all circumstances. We propose a framework for building on an organizations preferred change management model and adapting it based on the change desired and the organization. We use three change management scenarios (small, large, and rapid) from radiology to explore the application of the framework. Radiology was chosen to illustrate the framework because it has been digital longer than many medical specialties. Given the high number of upgrades and new digital platforms in Radiology, it could also serve as a testing ground for such a framework. © 2023 "IISE”.

Potential Benefits of Artificial Intelligence in Healthcare

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.

Towards Reliable Remote Health Monitoring in Fog Computing Networks

As the World is still facing the COVID-19 pandemic, several researchers and industry players have proposed technological solutions to help fight the pandemic and pave the way for post-pandemic era precautions. In this matter, the potential benefits of remote health monitoring have been brought back to the spotlight. Indeed, with current advances in wireless communications, core network virtualization, and computing architectures as enablers, consistently guaranteeing the stringent quality-of-service (QoS) requirements of remote health monitoring, e.g., ultra-low latency, may be achievable. Notably, the fog computing (FC) paradigm has been advocated as a potential solution for remote health monitoring. However, the unreliability of fog nodes in FC networks is a critical aspect often overlooked despite its significant impact on vital latency requirements. This paper proposes a reliable fog-based remote health monitoring framework operating under uncertain fog computing conditions. Specifically, we formulate the problem of assigning tasks of remote sensors attached to patients to their adequate applications deployed in fog nodes aiming to maximize the number of satisfied tasks with respect to the fog nodes’availability and communication latency constraints. Due to the problem’s NP-hardness, we leverage a differential evolution-based algorithm enhanced by reinforcement learning to deploy applications in fog nodes. Numerical results demonstrate the superior reliability performance of our proposed solution, in terms of the average success ratio of tasks, compared to benchmarks. Specifically, our simulations show up to 60 % performance improvement compared to benchmarks in specific scenarios. Moreover, by investigating the impact of several key parameters, we identify a design trade-off between the number of fog nodes and the latter’s intrinsic failure rates. IEEE

Digitalization of the supply chain: transformation factors

Purpose There is an increasing interest in the supply chain's digitalization, yet the topic is still in the preliminary stages of academic research. The academic literature has no consensus and is still limited to research assessing the supply chain's digitalization of organizations. This study aims to explore the supply chain digitalization drivers to understand the emerging phenomena. More specifically, the authors devised from the literature the most common factors in assessing the readiness in scaling supply chain digitalization. Design/methodology/approach This study followed a five-phased systematic literature review (SLR) methodology in this research: designing, analyzing, conducting, writing and assessing the quality of the review. The SLR is beneficial for justifying future research regardless of the complex process that requires dealing with high-level databases, information filtering and relevancies of the content. Through analysis of 347 titles and s and 40 full papers, the authors showed and discussed the supply chain digitalization: transformation factors. Findings The results generated three main themes: technology, people and processes. The study also generated ten subthemes/primary drivers for assessing the readiness for supply chain digitalization in organizations: IT infrastructure, cybersecurity systems, digitalization reskilling and upskilling, digitalization culture, top management support, digitalization and innovation strategy, integrated supply chain, digital innovation management, big data management and data analytics and government regulations. The importance of each factor was discussed, and future research agenda was presented. Research limitations/implications While the key drivers of the supply chain digitalization were identified, there is still a need to study the statistical correlation to confirm the interrelationships among factors. This study is also limited by the articles available in the databases and content extraction. Practical implications This study supports decision-makers in understanding the critical drivers in digitalizing the supply chain. Once these factors are studied and comprehended, managers and decision-makers could better anticipate and allocate the proper resources to embark on the digitalization journey and make informed decisions. Originality/value The digitalization of the supply chain is more critical nowadays due to the global disruptions caused by the Coronavirus (COVID-19) pandemic and the surge of organizations moving toward the digital economy. There is a gap between the digital transformation pilot studies and implementation. The themes and factors unearthed in this study will serve as a foundation and guidelines for further theoretical research and practical implications.

Deceased donor kidney transplant in a 70-year-old Jehovah's Witness patient: to transplant or not to transplant-a case report.

While Jehovah's Witness (JW) patients refuse transfusions of blood or blood products, they are willing to accept renal allograft transplantation. We describe here a case of what we believe is the oldest (a 70-year-old) JW candidate to undergo a deceased donor kidney transplant reported in the literature. Prior to transplantation, discussions ensued amongst the multidisciplinary transplant team, weighing the potential benefits vs. risks of performing a kidney transplant on this patient due to her refusal (due to religion) to accept any blood transfusions or blood products combined with her advanced age and having longstanding insulin-dependent, type 2 diabetes mellitus with extensive peripheral vascular disease. Preoperatively, we believed that the odds were in favor of performing the kidney transplant safely without the need for any blood product usage. However, her post-operative course was complicated by severe anemia, which developed by post-transplant day 4. The anemia incapacitated the patient's physical and psychological state, creating medical, social and financial burdens on the patient, family, medical team and hospital. Both family and patient grew concerned about her overall condition. Blood transfusion was offered in order to improve her weakness and shortness of breath that developed due to the severe anemia, but the patient (along with her family) refused such treatment. During the 17 days of hospitalization, it was a continuous struggle between the transplant team, patient, and family for her to continue with the recovery process; at times we had even considered that performing the transplant had been a mistake. While organ transplantation can be performed safely in Jehovah's Witnesses, there are multiple factors seen in this particular case that warrant analyzing: (I) the potential use of stricter transplant exclusionary criteria, given the recipient's advanced age and preexisting co-morbidities, which likely increased her risk of developing severe anemia post-operatively, and (II) the recipient's emotional/psychological post-operative state of high anxiety, which developed while she was experiencing the severe anemia; in hindsight, her anxiety level may have been reduced if we had offered daily post-operative psychological counseling sessions. While the patient's allograft is currently doing well, we probably did not have strict enough criteria for proper selection of a JW candidate for kidney transplantation.