International Journal of Medical Informatics

OBJECTIVE: The aims of this review are to clarify the current state of research in terms of assessment tools and assessors of the quality of health science-related short videos on TikTok, to identify limitations in existing research; and to provide a reference for future studies. METHODS: A scoping review was conducted. The Cochrane Library, PubMed, MEDLINE, Web of Science, Embase, Scopus, EBSCO, CNKI, VIP, Wanfang Data, and CBM databases were searched from September 2016 to November 2022...

INTRODUCTION: Health records serve not only as a database of a patient's health history and treatment process but also as a crucial tool for doctors to diagnose and treat patients. However, the storage and sharing of these records are sensitive issues as they involve maintaining patient privacy and ensuring data transparency, security, and interoperability between different parties. Challenges to achieving these goals in the current surgical process can impact the allocation of medical resources and surgical outcomes...

INTRODUCTION: Multifactorial falls risk assessment tools (FRATs) can be an effective falls prevention method for older adults, but are often underutilized by health care professionals (HCPs). This study aims to enhance the use and implementation of multifactorial FRATs by combining behavioral theory with the user-centered design (UCD) method of personas construction. Specifically, the study aimed to (1) construct personas that are based on external (i.e., needs, preferences) and intrinsic user characteristics (i...

BACKGROUND: Post-stroke pneumonia (PSP) is common among stroke patients. PSP occurring after hospital discharge continues to increase the risk of poor functional outcomes and death among stroke survivors. Currently, there is no prediction model specifically designed to predict the occurrence of PSP beyond the acute stage of stroke. This study aimed to explore the use of machine learning (ML) methods in predicting the risk of PSP after hospital discharge. METHODS: This study analyzed data from 5,754 hospitalized stroke patients...

INTRODUCTION: Duplicate prescribing clinical decision support alerts can prevent important prescribing errors but are frequently the cause of much alert fatigue. Stat dose prescriptions are a known reason for overriding these alerts. This study aimed to evaluate the effect of excluding stat dose prescriptions from duplicate prescribing alerts for antithrombotic medicines on alert burden, prescriber adherence, and prescribing. MATERIALS AND METHODS: A before (January 1st, 2017 to August 31st, 2022) and after (October 5th, 2022 to September 30th, 2023) study was undertaken of antithrombotic duplicate prescribing alerts and prescribing following a change in alert settings...

BACKGROUND: Electronic surveillance software (ESS) collects multiple patient data from hospital software to assist infection control professionals in the prevention and control of hospital-associated infections. This study aimed to understand the perceptions of end users (i.e., infection control professionals) and the facilitators and barriers related to a commercial ESS named ZINC and to assess its usability. METHODS: A mixed-method research approach was adopted among infection control professionals 10 months after the implementation of commercial ESS in the university hospital of Nancy, France...

BACKGROUND: Clinical Decision Support Systems (CDSSs) are electronic systems used to conduct assessments based on patient characteristics and to offer treatment recommendations for clinicians to consider during their decision-making processes. CDSSs are needed by mental health helpline services to optimise service delivery for clients and counsellors, while also collecting the data needed for the administration of the service. The aim of this systematic review was to provide a comprehensive overview of the design and implementation of CDSSs in mental health helpline services, to identify current issues in their design and implementation, and to provide recommendations that may address any identified issues...

BACKGROUND: Urothelial bladder cancer (UBC) is characterized by a high recurrence rate, which is predicted by scoring systems. However, recent studies show the superiority of Machine Learning (ML) models. Nevertheless, these ML approaches are rarely used in medical practice because most of them are black-box models, that cannot adequately explain how a prediction is made. OBJECTIVE: We investigate the global feature importance of different ML models. By providing information on the most relevant features, we can facilitate the use of ML in everyday medical practice...

BACKGROUND: Chronic Pelvic Pain (CPP) has been described as a public health priority worldwide, and it is among the most prevalent and costly healthcare problems. Graded motor imagery (GMI) is a therapeutic tool that has been successfully used to improve pain in several chronic conditions. GMI therapy is divided into three stages: laterality training (LRJT, Left Right Judgement Task), imagined movements, and mirror therapy. No tool that allows working with LRJT in pelvic floor has been developed to date...

INTRODUCTION: Cyberattacks on healthcare organisations are becoming increasingly common and represent a growing threat to patient safety. The majority of breaches in cybersecurity have been attributed to human error. Intensive care departments are particularly vulnerable to cyberattacks. The aim of this study was to investigate cybersecurity awareness, knowledge and behaviours among critical care staff. METHODS: This was a multi-site cross-sectional survey study administered to critical care staff...

BACKGROUND: Ensuring safe adoption of AI tools in healthcare hinges on access to sufficient data for training, testing and validation. Synthetic data has been suggested in response to privacy concerns and regulatory requirements and can be created by training a generator on real data to produce a dataset with similar statistical properties. Competing metrics with differing taxonomies for quality evaluation have been proposed, resulting in a complex landscape. Optimising quality entails balancing considerations that make the data fit for use, yet relevant dimensions are left out of existing frameworks...

PURPOSE: This study aims to assess the extent to which the demand for ophthalmologic care among patients at the state level is reflected in Google Trends data, serving as an indicator of patient desire in ophthalmology. METHODS: For each state, patient interest in ophthalmologic care was estimated using the Google Trends resource measuring web search and YouTube search rates for multiple ophthalmologic terms. We compared the change in search for ophthalmologic terms over time and used ordinary least squares regression to evaluate whether search interest for ophthalmologic terms was able to predict the rate of practicing ophthalmologists in each state...

BACKGROUND: Health and Wellbeing Living Labs are a valuable research infrastructure for exploring innovative solutions to tackle complex healthcare challenges and promote overall wellbeing. A knowledge gap exists in categorizing and understanding the types of ICT tools and technical devices employed by Living Labs. AIM: Define a comprehensive taxonomy that effectively categorizes and organizes the digital data collection and intervention tools employed in Health and Wellbeing Living Lab research studies...

AIM: To evaluate YouTube videos on vital pulp capping (VPC) for content, quality, source, usefulness, and reliability. MATERIALS AND METHODS: This study assessed 249 English-language videos on vital pulp therapy using the Total Content Score (TCS), Video Information and Quality Index (VIQI), Global Quality Scale (GQS), Journal of the American Medical Association (JAMA) score and modified DISCERN score. Videos were categorized based on communication quality, duration, likes and dislikes, views, source, and video type...

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OBJECTIVES: Liver cirrhosis (LC) can be caused by obesity, alcohol consumption, viral infection, and autoimmune disease. Early diagnosis and management of LC is important for patient quality of life. Non-invasive diagnostic methods are useful for predicting the current status and mortality risk of LC. The purpose of this study is to identify relevant diagnostic factors measured in routine laboratory test of alcohol-related liver cirrhosis (ALC) patients. METHODS: This study analyzed data from 127 patients with ALC, including their laboratory test results and clinical information, including coagulation parameters, hematologic parameters, and biochemical parameters...

BACKGROUND: Parenting self-efficacy is essential for the transition to parenthood. As digital parenting educational interventions are rapidly being developed, their effects have not been examined by pooling available randomized controlled trials (RCTs). OBJECTIVES: To comprehensively investigate the effects of digital educational interventions on parents' self-efficacy, social support, and depressive symptoms in the first year after childbirth and identify the significant associated factors...

INTRODUCTION: Despite the growing trend in the use of digital technologies in physiotherapy, the overall adoption and satisfaction of both, practice management software (PMS) and electronic health records in physiotherapy clinics has been low and slow over time. Satisfaction of expectations or perceived quality (PQ) is an abstract construct based on the discrepancy between expectations and perceptions, to measure the satisfaction of physiotherapists on PMS. This study aims to develop and validate an instrument to measure PQ on PMS, and to describe the PQ of the currently available physiotherapy PMS...

BACKGROUND: Wrist-worn gadgets like smartphones are ideal for unobtrusively gathering user data, in various fields such as health and fitness monitoring, communication, and productivity enhancement. They seamlessly integrate into users' daily lives, providing valuable insights and features without the need for constant attention or disruption. In sensitive domains like mental health, these devices provide user-friendly, privacy-protected means of diagnosis and treatment, offering a secure and cost-effective avenue for seeking help...

BACKGROUND: Gastric cancer (GC) is one of the most common malignant tumors in the world, posing a serious threat to human health. Currently, gastric cancer treatment strategies emphasize a multidisciplinary team (MDT) consultation approach. However, there are numerous treatment guidelines and insights from clinical trials. The application of AI-based Clinical Decision Support System (CDSS) in tumor diagnosis and screening is increasing rapidly. OBJECTIVE: The purpose of this study is to (1) summarize the treatment decision process for GC according to the treatment guidelines in China, and then create a knowledge graph (KG) for GC, (2) based on aforementioned KG, built a CDSS and conducted an initial feasibility evaluation for the current system...