Artificial intelligence (AI) applications have transformed healthcare. This study is based on a general literature review uncovering the role of AI in healthcare and focuses on the following key aspects: (i) medical imaging and diagnostics, (ii) virtual patient care, (iii) medical research and drug discovery, (iv) patient engagement and compliance, (v) rehabilitation, and (vi) other administrative applications. The impact of AI is observed in detecting clinical conditions in medical imaging and diagnostic services, controlling the outbreak of coronavirus disease 2019 (COVID-19) with early diagnosis, providing virtual patient care using AI-powered tools, managing electronic health records, augmenting patient engagement and compliance with the treatment plan, reducing the administrative workload of healthcare professionals (HCPs), discovering new drugs and vaccines, spotting medical prescription errors, extensive data storage and analysis, and technology-assisted rehabilitation. Nevertheless, this science pitch meets several technical, ethical, and social challenges, including privacy, safety, the right to decide and try, costs, information and consent, access, and efficacy, while integrating AI into healthcare. The governance of AI applications is crucial for patient safety and accountability and for raising HCPs’ belief in enhancing acceptance and boosting significant health consequences. Effective governance is a prerequisite to precisely address regulatory, ethical, and trust issues while advancing the acceptance and implementation of AI. Since COVID-19 hit the global health system, the concept of AI has created a revolution in healthcare, and such an uprising could be another step forward to meet future healthcare needs.

Higher education institutions (HEIs) shifted from in-person attendance to blended and online learning due to the COVID-19 lockdowns. This study investigated the students' perception of satisfaction, convenience, engagement, and learning towards blended and online courses conducted before, during, and after the COVID-19 lockdowns. A longitudinal study design was adopted to examine the students' perception of online and blended learning courses before, during, and after the COVID-19 lockdowns. The subjects consist of Health science students (N = 130) belonging to two different colleges of a public university and the study period includes three academic years (i.e., six semesters) (2018–2021). A survey tool was developed to collect data from students studying the computer fundamentals course through blended and online learning modes from 2018 to 2021. Over 95% of students have been satisfied with the course offered through various blended learning formats since 2018. The blended 0.50-course format is the most preferred one for the students; however, the Blended 0.75-course format is highly rated by the students regarding their satisfaction and engagement than other learning formats during the COVID-19 lockdowns. Following adaption after COVID-19, the students reported a high perception of learning towards the course when delivered through 100% online learning mode. Students' achievement is significantly associated with the learning modes, exam modes, and various student batches. The blended 0.75-course format group shows a higher achievement than the other three-course format groups. Likewise, those students who appeared in their exams online showed higher achievement than those who appeared physically. Further, the students felt equally convenient with Blended 0.75 and 100% online learning course formats. These findings would also help HEIs choose appropriate learning and examination modes while designing courses.

Information Technology (IT) professionals working with computers gradually develop forward head posture and, as a result, these professionals are susceptible to several neck disorders. This study intended to reveal the relationships between pain intensity, disability, head posture and deep cervical flexor (DCF) muscle performance in patients with postural neck pain. A cross-sectional study was conducted on 84 IT professionals who were diagnosed with postural neck pain. The participants were recruited with a random sampling approach. A Visual Analogue Scale (VAS), the Northwick Park Neck Pain Questionnaire (NPQ), the Modified Head Posture Spinal Curvature Instrument (MHPSCI), and the Stabilizer Pressure Biofeedback Unit were used to measure neck pain intensity, neck disability, head posture, and DCF muscle performance, respectively. The Pearson correlation coefficient revealed a significantly strong positive relationship between the VAS and the NPQ (r = 0.734). The cranio-vertebral (CV) angle was found to have a significantly negative correlation with the VAS (r = -0.536) and a weak negative correlation with the NPQ (r = -0.389). This study concluded that a smaller CV angle corresponded to greater neck pain intensity and disability. Furthermore, there is no significant relationship between CV angle and DCF muscle performance, indicating that head posture re-education through postural correction exercises would not completely correct the motor control deficits in DCF muscles. In addition, a suitable exercise regimen that exclusively targets the deep cervical flexor muscle to improve its endurance is warranted.

Background: Hospital-acquired infection (HAI) is one of the most common complications occurring in a hospital setting. Although previous studies have demonstrated the application of data-driven Six Sigma DMAIC (Define, Measure, Analyze, Improve and Control) methodology in various health-care settings, no such studies have been conducted on HAI in the Saudi Arabian context. Objective: The purpose of this research was to study the effect of the Six Sigma DMAIC approach in reducing the HAI rate at King Fahd Hospital of the University, Al-Khobar, Saudi Arabia. Methods: Historical data on HAI reported at inpatient units of the hospital between January and December 2013 were collected, and the overall HAI rate for the year 2013 was determined. The Six Sigma DMAIC approach was then prospectively implemented between January and December 2014, and its effect in reducing the HAI rate was evaluated through five phases. The incidence of HAI in 2013 was used as the problem and a 30% reduction from 4.18 by the end of 2014 was set as the project goal. Potential causes contributing to HAI were identified by root cause analysis, following which appropriate improvement strategies were implemented and then the pre- and postintervention HAI rates were compared. Results: The overall HAI rate was observed as 4.18. After implementing improvement strategies, the HAI rate significantly reduced from 3.92 during the preintervention phase ( first quarter of 2014) to 2.73 during the postintervention phase (third quarter of 2014) (P < 0.05). A control plan was also executed to sustain this improvement. Conclusion: The results show that the Six Sigma “DMAIC” approach is effective in reducing the HAI rate.

Background: Performance evaluation in the allied healthcare education sector is complex, making it essential for policymakers and managers to approach it comprehensively and thoughtfully to understand their performance. Hence, the development and monitoring of Key Performance Indicators (KPIs) in this domain must be considered one of the key priorities for the policymakers in AHIs. Aim: This study aims to develop a framework for the AHIs to extract and profile the indicators, measure, and report the results appropriately. Methods: The authors adopted a general review of the literature approach to study the primary goals of the institutional KPI framework, emphasizing the need for benchmarking while implementing KPIs and how to track performance using a KPI dashboard. Results: The study provides the scope, relevant KPI categories, and a list of KPIs for evaluating the effectiveness of allied healthcare programs. The study findings also emphasized the need for benchmarking the KPIs and establishing a KPI dashboard while measuring and monitoring performance. Conclusion: KPIs are considered an invaluable tool that contributes immensely to the performance monitoring process of AHIs, irrespective of the specialties. This helps to identify and guide AHIs for developing KPIs and the associated minimum data set to measure organizational performance and monitor the quality of teaching and learning. In addition, the KPI framework reported in this study is a tool to assist performance monitoring that can subsequently contribute to the overall quality of AHIs.

Students’ Evaluating Teaching Effectiveness is one of the most widely accepted methods of measuring the Quality of Higher Education worldwide. The University of Dammam is currently performing several evaluations by students as required for academic accreditation by the National Commission for Academic Accreditation and Assessment. Of these, two of them deal with program evaluation i.e. Students Experience Survey (SES), and Programme Evaluation Survey (PES). SES denotes the experience of students halfway through in a given academic program and PES denotes the students overall experience at the end. This study was conducted among the students of Medical and Nursing programs to capture their experiences related to various aspects of the teaching and learning process adopted in their college. The students’ attitude was captured through the SES questionnaire and the data were analyzed through six sigma analytical tool using the Poisson distribution model. From the non-conformance level apprehended through the responses from the students about the various categories of teaching and learning process prevailing in the College, the corresponding sigma rating for each teaching and learning process was calculated. Consequently, an innovative six point quality rating system was developed for each sigma values.