A Risk Management Framework Using Digital Transformation for the Healthcare Sector during the Covid-19 Pandemic

Despite the many changes in the orientation of the world economy and the spotlight positioning, the healthcare sector remains one of the most important and critical sectors for its contribution in every aspect of human life. Improvements in the healthcare sector are seen and evident on a daily basis to cope with the technological and digital advancements in the world, and the recent COVID-19 pandemic has put these improvements into a faster pace. Several challenges in the health sector have risen to surface since the beginning of the pandemic; some of these challenges have been properly addressed and tackled, while others have shown the flaws in the healthcare sector in several countries around the world. These challenges have come with risks that can be projected on the sector as a whole, and thus this has given researchers a golden chance to dig further deep into more improvements in the sector, to have these risks identified, assessed, and eliminated or monitored in the future. Digital transformation has recently become one of the most robust tools to improve the processes and operations of organizations as whole and paramount ones in particular. Digital transformation brings however its own risks and thus a lot of research has been previously addressed the risks of digital transformation, whereas no research has yet been done on digital transformation by itself being used as a risk management and mitigation tool despite its effective use as an improvement tool and for other organizational goals. Our research comes to address the main risks in the healthcare sector and to match these risks with monitoring actions that use digital transformation as a tool. One of the main challenges the healthcare sector has faced during the COVID-19 pandemic, was the ability to maintain ordinary operations while handling COVID-19 cases and controlling the spread of the virus in the healthcare facility. This situation has called for segregation of COVID-19 patients from other patients whether it was in the same facility or by adapting them into different facilities. The segregation of patients has been done using two digital solutions; embedment of automatic thermometers, and the development of an efficient scheduling strategy for COVID-19 symptomatic patients. Furthermore, other challenges have risen due to the pandemic and caused major risks that called for monitoring actions and solutions, whether digital or non-digital ones. To investigate these challenges, a literature review was conducted in this research to highlight the 11 most common challenges that can be included in a survey to be distributed to different healthcare organizations for the purpose of prioritization and ranking of these challenges and ultimately conclude the associated risks based on the results of the survey. In this research, a survey was conducted with over 100 hospitals inside and outside the UAE to identify the main challenges in the healthcare sector faced during the pandemic. The survey addressed the challenges that were found in the literature review to be the most impactful on the healthcare sector during the COVID-19 pandemic. These challenges acted as an inspiring source for the associated risks to be identified accordingly based on their impact result from the survey. Furthermore, an assessment of these risks was conducted to evaluate the likelihood of each risk and ultimately the risk rank and priority. The final step in the risk management strategy entailed the recommendation of monitoring actions based on digital transformation tools and techniques. Basing the monitoring actions on digital transformation will pose the trademark of this research and will highlight its originality. Moreover, the survey has also addressed three factors by questions that were answered by the respondents. These factors included the country, the size of the healthcare organization, and its technological readiness. The correlation of these factors with the collected responses of healthcare organizations is investigated using statistical tools to study the effect of these factors on the impact level of COVID-19 on the healthcare organization. This risk management framework will act as a guideline for any healthcare organization Finally, a risk management framework is drawn from these findings involving a risk response strategy and a risk control plan as part of risk registers. The main and ultimate goal of this research is to outline a recommended management approach to the healthcare sector risks caused by an event of a pandemic in general and COVID-19 in specific. This risk management framework designed in this report will act as a guideline for any healthcare organization of any size, with any level of technological readiness, and at any level outbreak severity in the country

Modified masses and parallaxes of close binary system: HD39438

We present the detailed fundamental stellar parameters of the close visual binary system; HD39438 for the first time. We used Al-Wardat's method for analyzing binary and multiple stellar systems (BMSSs). The method implements Kurucz's plane parallel model atmospheres to construct synthetic spectral energy distributions for both components of the system. It then combines the results of the spectroscopic analysis with the photometric analysis and then compares them with the observed ones to construct the best synthetic spectral energy distributions for the combined system. The analysis gives the precise fundamental parameters of the individual components of the system. Based on the positions of the components of HD39438 on the H-R diagram, and evolutionary and isochrones tracks, we found that the system belongs to the main sequence stars with masses of 1.24 and 0.98 solar masses for the components A and B, respectively, and age of 1.995 Gyr for both components. The main result of HD39438 is new dynamical parallax, which is estimated to be 16.689+- 0.03 mas

home page, Evolution of Accreting Binary Systems on the Spin-up Line

The measured characteristics of binary pulsars provide valuable insights into the evolution of these systems. We study the aspects of binary evolution particularly relevant to binary Millisecond Pulsars (MSPs), and the formation of close binaries involving degenerate stars through a spin-evolution diagram (spin-up line). For this task, we use a wide variety of binaries, including those with compact components that observed in different energy bands, which we analyze them according to the spin-up line. Their formation and evolution over timescales of binary evolution models are investigated in order to grab any constraint on their evolution, and to estimate the masses of neutron stars with different mass-transfer histories

Hydrological and Hydrodynamic Modeling for Flash Flood and Embankment Dam Break Scenario: Hazard Mapping of Extreme Storm Events

Simulation of dam breach scenarios can help in the preparation of emergency action plans for real dam breaks or flash flooding events. The purpose of this study was to identify flood-prone areas in the Al Wala Valley in the governorate of Madaba in Jordan through analysis of the Al Wala Dam. Modelling of dam breaches was conducted under two scenarios: a Clear Day scenario and a Probable Maximum Flood (PMF) scenario. The former scenario does not address the various dam failure modes; rather, it addresses the formation and development of a breach as a result of structural failures like the sliding of dam blocks in the case of a concrete dam or piping failures in the case of embankment dams. The PMF scenarios, however, simulate unsteady flow in pipes and overtopping failure via consideration of runoff hydrography. In the PMF scenario, flood-prone areas can be identified by in-depth analysis of data from previous extreme rainfall events. The related hydrologic and hydraulic data can then be modelled using intensity-duration-frequency curves applied to an hour-by-hour simulation to discover the areas most at risk of flooding in the future. In the present study, data were collected from inlet of flow to Al Wala Valley on 10 January 2013. The collected data, which included rainfall and discharge data, were fed to the HEC-HMS software in order to calibrate the hydrological parameters of the watershed of the Al Wala Dam. Additionally, the HEC-RAS tool was employed to determine the breach outflow hydrography and hydraulic conditions across various critical downstream locations, which were determined by use of dynamic flood wave-routing models. The simulations revealed that, in the case of the Clear Day scenario, downstream inundation would cover an area of 5.262 km2 in the event of a pipe failure. However, in the event of a six-hour storm, a twelve-hour storm, and a twenty-four-hour storm, the flooded area would rise to 6.837 km2, 8.518 km2, and 9.390 km2, respectively. In the event of an overtopping failure, 13.171 km2 would be inundated, according to the Clear Day scenario. On the other hand, in the event of a six-hour storm, a twelve-hour storm, and a twenty four-hour storm, the flooded area would rise to 13.302 km2, 14.249 km2, and 14.594 km2, respectively

Hydrological and Hydrodynamic Modeling for Flash Flood and Embankment Dam Break Scenario: Hazard Mapping of Extreme Storm Events

Simulation of dam breach scenarios can help in the preparation of emergency action plans for real dam breaks or flash flooding events. The purpose of this study was to identify flood-prone areas in the Al Wala Valley in the governorate of Madaba in Jordan through analysis of the Al Wala Dam. Modelling of dam breaches was conducted under two scenarios: a Clear Day scenario and a Probable Maximum Flood (PMF) scenario. The former scenario does not address the various dam failure modes; rather, it addresses the formation and development of a breach as a result of structural failures like the sliding of dam blocks in the case of a concrete dam or piping failures in the case of embankment dams. The PMF scenarios, however, simulate unsteady flow in pipes and overtopping failure via consideration of runoff hydrography. In the PMF scenario, flood-prone areas can be identified by in-depth analysis of data from previous extreme rainfall events. The related hydrologic and hydraulic data can then be modelled using intensity-duration-frequency curves applied to an hour-by-hour simulation to discover the areas most at risk of flooding in the future. In the present study, data were collected from inlet of flow to Al Wala Valley on 10 January 2013. The collected data, which included rainfall and discharge data, were fed to the HEC-HMS software in order to calibrate the hydrological parameters of the watershed of the Al Wala Dam. Additionally, the HEC-RAS tool was employed to determine the breach outflow hydrography and hydraulic conditions across various critical downstream locations, which were determined by use of dynamic flood wave-routing models. The simulations revealed that, in the case of the Clear Day scenario, downstream inundation would cover an area of 5.262 km2 in the event of a pipe failure. However, in the event of a six-hour storm, a twelve-hour storm, and a twenty-four-hour storm, the flooded area would rise to 6.837 km2, 8.518 km2, and 9.390 km2, respectively. In the event of an overtopping failure, 13.171 km2 would be inundated, according to the Clear Day scenario. On the other hand, in the event of a six-hour storm, a twelve-hour storm, and a twenty four-hour storm, the flooded area would rise to 13.302 km2, 14.249 km2, and 14.594 km2, respectively