Impact of specialized renal technologists on optimizing delivery of continuous kidney replacement therapy in critical care areas a retrospective study.

Background: Continuous renal replacement therapy (CKRT) is delivered to some of the most critically ill patients in hospitals. This therapy is expensive and requires coordination of multidisciplinary teams to ensure the prescribed dose is delivered. With increased demands on the critical care nursing staff and increased complexities of patients admitted to critical care units, we evaluated the role of specialized renal technologists in ensuring the prescribed dose is delivered.

Barriers Preventing Medical Trainees from Active Participation in Research Activities.

Background: Research has increasingly become important to career progression and a compulsory component in most medical programs. While medical trainees are consistently urged to undertake research endeavors, they frequently encounter obstacles at both personal and organizational levels that impede the pursuit of high-quality research. This study aims to identify the barriers and recommend successful interventions to increase research productivity amongst medical trainees.

Assessment of the organizational factors in incident management practices in healthcare: A tree augmented Naive Bayes model.

Despite the exponential transformation occurring in the healthcare industry, operational failures pose significant challenges in the delivery of safe and efficient care. Incident management plays a crucial role in mitigating these challenges; however, it encounters limitations due to organizational factors within complex and dynamic healthcare systems. Further, there are limited studies examining the interdependencies and relative importance of these factors in the context of incident management practices.

Evaluation of point-of-care ultrasound training among healthcare providers: a pilot study.

Background: The use of Point-of-Care Ultrasound (POCUS) has become prevalent across a variety of clinical settings. Many healthcare professionals have started getting hands-on training. To evaluate the effectiveness of such training programs, this study aimed to assess a 4 day POCUS training course on healthcare providers' skills and knowledge acquisition.

Leveraging artificial intelligence and decision support systems in hospital-acquired pressure injuries prediction: A comprehensive review.

Background: Hospital-acquired pressure injuries (HAPIs) constitute a significant challenge harming thousands of people worldwide yearly. While various tools and methods are used to identify pressure injuries, artificial intelligence (AI) and decision support systems (DSS) can help to reduce HAPIs risks by proactively identifying patients at risk and preventing them before harming patients.

Objective: This paper comprehensively reviews AI and DSS applications for HAPIs prediction using Electronic Health Records (EHR), including a systematic literature review and bibliometric analysis.

A Systematic Literature Review of Safety Culture in Hemodialysis Settings.

Background: Safety culture is an important aspect of quality in healthcare settings. There are many risks that patients can encounter in hemodialysis settings one of which is the infection risks due to the regular need to access bloodstreams using catheters and needles. Implementation of prevention guidelines, protocols and strategies that reinforce safety culture excellence are essential to mitigate risks.

Evaluating Drivers of the Patient Experience Triangle: Stress, Anxiety, and Frustration.

Patient experience is a widely used indicator for assessing the quality-of-care process during a patient's journey in hospital. However, the literature rarely discusses three components: patient stress, anxiety, and frustration. Furthermore, little is known about what drives each component during hospital visits.

COVID-19, jobs and skills-Exploratory analysis of the job postings in the US and UK healthcare job market.

The COVID-19 pandemic has significantly affected all spheres of life, including the healthcare workforce. While the COVID-19 pandemic has started driving organizational and societal shifts, it is vital for healthcare organizations and decision-makers to analyze patterns in the changing workforce. In this study, we aim to identify patterns in healthcare job postings during the pandemic to understand which jobs and associated skills are trending after the advent of COVID-19.

Identifying Patient Satisfaction Determinants in Hemodialysis Settings: A Systematic Review.

Purpose: Patient satisfaction is a measure of care quality that assists providers in determining the effectiveness of their services while meeting patients' expectations. This study aimed to review existing studies that have focused on patients' satisfaction determinants in Hemodialysis (HD) settings.

Methods: Electronic databases (PubMed, ScienceDirect, Scopus, and Google Scholar) were searched from 2000 onwards to identify studies using search terms related to patient satisfaction and hemodialysis centers.

Burnout and Cardiovascular Risk in Healthcare Professionals During the COVID-19 Pandemic.

Introduction: The objective of this study was to investigate the psychosocial and cardiovascular markers in healthcare professionals during the COVID-19 pandemic.

Methods: This was a STROBE compliant, blended exploratory study. Residents, staff physicians, nurses, and auxiliary healthcare professionals from both inpatient and outpatient medicine services were recruited using a planned random probability sample.

Nexus between drivers of COVID-19 and country risks.

COVID-19 has disrupted all spheres of life, including country risk regarding the exposure of economies to multi-dimensional risk drivers. However, it remains unexplored how COVID-19 has impacted different drivers of country risk in a probabilistic network setting. This paper uses two datasets on country-level COVID-19 and country risks to explore dependencies among associated drivers using a Bayesian Belief Network model.

The integration of mHealth technologies in telemedicine during the COVID-19 era: A cross-sectional study.

Telemedicine is a rapidly expanding field of medicine and an alternative method for delivering quality medical care to patients' fingertips. With the COVID-19 pandemic, there has been an increase in the use of telemedicine to connect patients and healthcare providers, which has been made possible by mobile health (mHealth) applications. The goal of this study was to compare the satisfaction of patients with telemedicine among mHealth users and non-users.

Exploring Quality Differences in Telemedicine Between Hospital Outpatient Departments and Community Clinics: Cross-sectional Study.

Background: Telemedicine is a care delivery modality that has the potential to broaden the reach and flexibility of health care services. In the United Arab Emirates, telemedicine services are mainly delivered through either integrated hospital outpatient department (OPDs) or community clinics. However, it is unknown if patients' perceptions of, and satisfaction with, telemedicine services differ between these two types of health care systems during the COVID-19 pandemic.

Prioritizing Multidimensional Interdependent Factors Influencing COVID-19 Risk.

COVID-19 has significantly affected various industries and domains worldwide. Since such pandemics are considered as rare events, risks associated with pandemics are generally managed through reactive approaches, which involve seeking more information about the severity of the pandemic over time and adopting suitable strategies accordingly. However, policy-makers at a national level must devise proactive strategies to minimize the harmful impacts of such pandemics.

Variation in hospital performance measures from the Turkey Ministry of Health.

Background: The Turkish healthcare system has seen broad population-based improvements in expanded health insurance coverage and access to healthcare services. Hospital performance in this national system is understudied. We aimed to identify trends in hospital performance over time following implementation of the Health Transformation Program and describe how regional outcomes correlate with regional vital statistics.

Physicians' Attitudes Toward Telemedicine Consultations During the COVID-19 Pandemic: Cross-sectional Study.

Background: To mitigate the effect of the COVID-19 pandemic, health care systems worldwide have implemented telemedicine technologies to respond to the growing need for health care services during these unprecedented times. In the United Arab Emirates, video and audio consultations have been implemented to deliver health services during the pandemic.

Objective: This study aimed to evaluate whether differences exist in physicians' attitudes and perceptions of video and audio consultations when delivering telemedicine services during the COVID-19 pandemic.

Exploring drivers of patient satisfaction using a random forest algorithm.

Background: Patient satisfaction is a multi-dimensional concept that provides insights into various quality aspects in healthcare. Although earlier studies identified a range of patient and provider-related determinants, their relative importance to patient satisfaction remains unclear.

Methods: We used a tree-based machine-learning algorithm, random forests, to estimate relationships between patient and provider-related determinants and satisfaction level in two of the main patient journey stages, registration and consultation, through survey data from 411 patients at a hospital in Abu Dhabi, UAE.

Evaluation of System Modelling Techniques for Waste Identification in Lean Healthcare Applications.

Purpose: Waste identification plays a vital role in lean healthcare applications. While the value stream map (VSM) is among the most commonly used tools for waste identification, it may be limited to visualize the behaviour of dynamic and complex healthcare systems. To address this limitation, system modelling techniques (SMTs) can be used to provide a comprehensive picture of various system-wide wastes.

Adoption of a Data-Driven Bayesian Belief Network Investigating Organizational Factors that Influence Patient Safety.

Medical errors pose high risks to patients. Several organizational factors may impact the high rate of medical errors in complex and dynamic healthcare systems. However, limited research is available regarding probabilistic interdependencies between the organizational factors and patient safety errors.

Ensuring protocol compliance and data transparency in clinical trials using Blockchain smart contracts.

Background: Clinical Trials (CTs) help in testing and validating the safety and efficacy of newly discovered drugs on specific patient population cohorts. However, these trials usually experience many challenges, such as extensive time frames, high financial cost, regulatory and administrative barriers, and insufficient workforce. In addition, CTs face several data management challenges pertaining to protocol compliance, patient enrollment, transparency, traceability, data integrity, and selective reporting.

Evaluating the Impact of Patient No-Shows on Service Quality.

Purpose: Patient no-shows are long-standing issues affecting resource utilization and posing risks to the quality of healthcare services. They also lead to loss of anticipated revenue, particularly in services where resources are expensive and in great demand.

Methods: In order to address common reasons why patients miss appointments, this study reviews the current literature and investigates various tools and methods that have been implemented to mitigate such issues.

Application of Artificial Intelligence in the Health Care Safety Context: Opportunities and Challenges.

There is a growing awareness that artificial intelligence (AI) has been used in the analysis of complicated and big data to provide outputs without human input in various health care contexts, such as bioinformatics, genomics, and image analysis. Although this technology can provide opportunities in diagnosis and treatment processes, there still may be challenges and pitfalls related to various safety concerns. To shed light on such opportunities and challenges, this article reviews AI in health care along with its implication for safety.

The link between healthcare risk identification and patient safety culture.

Purpose: Risk identification plays a key role identifying patient safety risks. As previous research on risk identification practices, as applied to patient safety, and its association with safety culture is limited, the purpose of this paper is to evaluate current practice to address gaps and potential room for improvement.

Design/methodology/approach: The authors carry out interview-based questionnaires in one UK hospital to investigate real-world risk identification practices with eight healthcare staff, including managers, nurses and a medical consultant.

Evaluating inputs of failure modes and effects analysis in identifying patient safety risks.

Purpose: There is a growing awareness on the use of systems approaches to improve patient safety and quality. While earlier studies evaluated the validity of such approaches to identify and mitigate patient safety risks, so far only little attention has been given to their inputs, such as structured brainstorming and use of system mapping approaches (SMAs), to understand their impact in the risk identification process. To address this gap, the purpose of this paper is to evaluate the inputs of a well-known systems approach, failure modes and effects analysis (FMEA), in identifying patient safety risks in a real healthcare setting.