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.

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.

Academic Medical Centers (AMCs) in Saudi Arabia are dedicated to providing high-quality patient care and promoting the health and wellbeing of its citizens. Additionally, they provide medical education and conduct research in a wide range of clinical disciplines. A recent global trend in academic hospitals with mandates similar to those in Saudi Arabia is that they have started utilizing digital health technology in a bid to increase efficiency and improve the quality of patient care. This paper takes the position that such digital health technologies should also be utilized in AMC settings in Saudi Arabia. Electronic health records (EHRs), smartphones, video-imaging technologies, virtual desktop infrastructures, mobile EHR access, and smart-beds can help AMCs serve patients more effectively. Rural people can be connected to consultants at AMCs using these technologies using virtual self-care tools. Validation of new digital health devices can be performed in collaboration with digital health partners and serve to enrich the knowledge of medical students in the area of digital health. This review aims to draw the attention of stakeholders to the need to implement digital health technology in AMCs in Saudi Arabia and help improve the quality of healthcare.

Purpose: The purpose of this paper is to evaluate the impact of adopting the Six Sigma define, measure, analyze, improve and control (DMAIC) approach in reducing patients fall rate in an Academic Medical Center, Saudi Arabia. Design/methodology/approach: A prospective study design was adopted and this study was conducted at King Fahd Hospital of the University (KFHU) during the year 2014. Based on the historical data of the patients’ falls reported at KFHU during the year 2013, the goal was fixed to reduce the falls rate from 7.18 to<3 (over 60 percent reduction) by the end of December 2014. This study was conducted through the five phases of “DMAIC” approach using various quality tools. Three time periods were identified, namely, pre-intervention phase; intervention phase; and post-intervention phase. Appropriate strategies were identified through the process of brainstorming and were implemented to study the potential causes leading to the occurrence of falls. Findings: The pre-intervention falls rate was reported as 6.57 whereas the post-intervention falls rate was measured as 1.91 (demonstrating a 70.93 percent reduction) after the implementation of improvement strategies. The adherence rate toward the practice of carrying falls risk assessment and hourly rounding was observed to be high where 88 percent of nurses are regularly practicing it. A control plan was also executed to sustain the improvements obtained. Originality/value: The Six Sigma “DMAIC” approach improves the processes related to the prevention of falls. A greater reduction in patients falls rate (over 70 percent) was observed after the implementation of the improvement strategy.

Objective: The aim of this paper was to determine the validity and reliability of a questionnaire tool for measuring students' attitudes toward components relevant to research training programs in the Kingdom of Saudi Arabia. Materials and Methods: The paper reports the responses of 564 Saudi Arabian students from seven government universities to the questionnaire comprising 16 items on 3 conceptual subscales, which measured students' attitude to research activities in the college; students' opinion of faculty involvement in research; and infrastructural facilities in the college. The results of this study provide the final scale, with all the 16 items of the initial Likert scale, for which strong evidence was obtained. Results: Results indicated that the students' attitude toward the research (SAR) scale had three latent factors, which explained 62% of the variance: The three subscales measured includes: (i) Research activities offered in the college, (ii) students' opinion of faculty involvement in research, and (iii) infrastructural facilities offered in the college for research. The full scale including three subscales had good internal consistency (r_s = 0.72 and α = 0.77 for full scale; and α between 0.71 and 0.79 for three subscales). Conclusion: This study provides evidence of reliability and validity of the SAR scale for the measurement of students' attitudes toward research training programs in Saudi Arabian Universities. The research findings will provide the basis for further research on health science students.

Background: Measuring patient satisfaction is a key factor in assessing the quality of patient care. Patient satisfaction outcomes are affected by many variables. Identifying and analyzing effective factors related to patients’ overall satisfaction constitutes an essential aspect of the study of modern healthcare. Aim: The aim of this study is to determine the factors vital to patients’ satisfaction with outpatient service. Methods: A cross-sectional study design was carried out from April to June 2015, consisting of 945 patients in the outpatient services division of King Fahd Hospital of the Imam Abdulrahman Bin Faisal University. Subjects were selected through the simple random sampling method, and data were collected using a structured questionnaire. The questionnaire was checked for validity and reliability using the Cronbach α coefficient and Reliability analysis. The factor analysis technique was used to find the most significant factors affecting patient satisfaction. Results: Exploratory factor analysis showed that the outpatients’ satisfaction comprised four factors namely, professional care, availability of services, waiting time, and satisfaction of laboratory service. These four factors explained 82% of the total variance of patient satisfaction. Based on the results of the factor analysis, satisfaction with physician services and appointment service was identified as the most important aspects of overall satisfaction. Conclusion: Physician-related services, the waiting time for getting test reports, and the wait time for appointment are the major factors affecting patient satisfaction in the outpatient department. Hence, improving the quality of these factors will improve the overall quality of outpatient services for patients.