Decision support tools

When non-invasive tests are unable to define the epileptogenic zone in patients, intracranial electroencephalography (iEEG) is a method of localising the epileptogenic zone. Compared to non-invasive evaluations, it offers more precise information about patterns of epileptiform activity, which results in useful diagnostic information that supports surgical decision-making. The primary aim of the present study was to assess the utility of iEEG for definitive surgery for patients suffering from drug-resistant epilepsy (DRE)...

BACKGROUND: Cardiovascular conditions (eg, cardiac and coronary conditions, hypertensive disorders of pregnancy, and cardiomyopathies) were the leading cause of maternal mortality between 2017 and 2019. The United States has the highest maternal mortality rate of any high-income nation, disproportionately impacting those who identify as non-Hispanic Black or Hispanic. Novel clinical approaches to the detection and diagnosis of cardiovascular conditions are therefore imperative. Emerging research is demonstrating that machine learning (ML) is a promising tool for detecting patients at increased risk for hypertensive disorders during pregnancy...

BACKGROUND: Patient and staff experience is a vital factor to consider in the evaluation of remote patient monitoring (RPM) interventions. However, no comprehensive overview of available RPM patient and staff experience-measuring methods and tools exists. OBJECTIVE: This review aimed at obtaining a comprehensive set of experience constructs and corresponding measuring instruments used in contemporary RPM research and at proposing an initial set of guidelines for improving methodological standardization in this domain...

Sustainable agricultural practices help to manage and use natural resources efficiently. Due to global climate and geospatial land design, soil texture, soil-water content (SWC), and other parameters vary greatly; thus, real time, robust, and accurate soil analytical measurements are difficult to be developed. Conventional statistical analysis tools take longer to analyze and interpret data, which may have delayed a crucial decision. Therefore, this review paper is presented to develop the researcher's insight toward robust, accurate, and quick soil analysis using artificial intelligence (AI), deep learning (DL), and machine learning (ML) platforms to attain robustness in SWC and soil texture analysis...

INTRODUCTION: Screening to promote social-emotional well-being in toddlers has positive effects on long-term health and functioning. Communication about social-emotional well-being can be challenging for primary care clinicians for various reasons including lack of time, training and expertise, resource constraints, and cognitive burden. Therefore, we explored clinicians' perspectives on identifying and communicating with caregivers about social-emotional risk in toddlers. METHOD: In 2021, semistructured interviews were conducted with pediatric clinicians (N = 20) practicing in Federally Qualified Health Centers in a single metropolitan area...

Leading national health organizations have declared pediatric mental health an urgent public health issue. Pediatric primary care is an ideal setting to improve mental health in young children; however, various existing barriers limit the effective identification of social-emotional risk among toddlers. This special section of Families, Systems, & Health includes four articles that identify multilevel barriers and facilitators to population-level early childhood mental health screening, identification, and referral and describe implementation strategies that may be used to improve pediatric mental health...

BACKGROUND: "Lock to Live" (L2L) is a novel web-based decision aid for helping people at risk of suicide reduce access to firearms. Researchers have demonstrated that L2L is feasible to use and acceptable to patients, but little is known about how to implement L2L during web-based mental health care and in-person contact with clinicians. OBJECTIVE: The goal of this project was to support the implementation and evaluation of L2L during routine primary care and mental health specialty web-based and in-person encounters...

OBJECTIVE: We applied a user experience (UX) design approach to clinical decision support (CDS) tool development for the specific use case of pediatric asthma. Our objective was to understand physicians' workflows, decision-making processes, barriers (ie, pain points), and facilitators to increase usability of the tool. MATERIALS AND METHODS: We used a mixed-methods approach with semi-structured interviews and surveys. The coded interviews were synthesized into physician-user journey maps (ie, visualization of a process to accomplish goals) and personas (ie, user types)...

BACKGROUND: The human population in Guyana, located on the South American continent, is vulnerable to zoonotic diseases due to an appreciable reliance on Neotropical wildlife as a food source and for trade. An existing suboptimal health surveillance system may affect the effective monitoring of important zoonotic diseases. To effectively address this deficit, a One Health zoonotic disease prioritization workshop was conducted to identify nationally significant zoonoses. METHODS: Prioritization of zoonotic diseases was conducted for the first time in Guyana & Caribbean region using literature review, prioritization criteria and a risk prioritization tool in combination with a consultative One Health workshop...

In developing countries, one-quarter of young women have suffered from anemia. However, the available studies in Ethiopia have been usually used the traditional stastical methods. Therefore, this study aimed to employ multiple machine learning algorithms to identify the most effective model for the prediction of anemia among youth girls in Ethiopia. A total of 5642 weighted samples of young girls from the 2016 Ethiopian Demographic and Health Survey dataset were utilized. The data underwent preprocessing, with 80% of the observations used for training the model and 20% for testing...

BACKGROUND: Primary care professionals encounter difficulties coordinating the continuum of care between primary care providers and second-line specialists and adhere to practice guidelines pertaining to diabetic foot ulcers management. Family medicine groups are providing primary care services aimed to improve access, interdisciplinary care, coordination and quality of health services, and reduce emergency department visits. Most professionals working in family medicine groups are primary care physicians and registered nurses...

BACKGROUND: The 'diagnostic odyssey' is a common challenge faced by patients living with rare diseases and poses a significant burden for patients, their families and carers, and the healthcare system. The diagnosis of rare diseases in clinical settings is challenging, with patients typically experiencing a multitude of unnecessary tests and procedures. To improve diagnosis of rare disease, clinicians require evidence-based guidance on when their patient may be presenting with a rare disease...

In real-world classification problems, it is important to build accurate prediction models and provide information that can improve decision-making. Decision-support tools are often based on network models, and this article uses information encoded by social networks to solve the problem of employer turnover. However, understanding the factors behind black-box prediction models can be challenging. Our question was about the predictability of employee turnover, given information from the multilayer network that describes collaborations and perceptions that assess the performance of organizations that indicate the success of cooperation...

MOTIVATION: ITree is an intuitive web tool for the manual, semi-automatic, and automatic induction of decision trees. It enables interactive modifications of tree structures and incorporates Relative Expression Analysis for detecting complex patterns in high-throughput molecular data. This makes ITree a versatile tool for both research and education in biomedical data analysis. RESULTS: The tool allows users to instantly see the effects of modifications on decision trees, with updates to predictions and statistics displayed in real time, facilitating a deeper understanding of data classification processes...

BACKGROUND: Substantial variation exists in surgeon decision making. In response, multiple specialty societies have established criteria for the appropriate use of spine surgery. Yet few strategies exist to facilitate routine use of appropriateness criteria by surgeons. Behavioral science nudges are increasingly used to enhance decision making by clinicians. We sought to design "surgical appropriateness nudges" to support routine use of appropriateness criteria for degenerative lumbar scoliosis and spondylolisthesis...

PURPOSE OF REVIEW: Based on shared decision-making (SDM) principles, a decision aid was previously developed to help patients, their caregivers, and physicians decide which peanut allergy management approach best suits them. This study refined the decision aid's content to better reflect patients' and caregivers' lived experience. RECENT FINDINGS: Current standard of care for peanut allergy is avoidance, although peanut oral immunotherapy has been approved by the Food and Drug Administration for use in patients 4-17 years old...

BACKGROUND AND AIMS: The American Society for Gastrointestinal Endoscopy (ASGE) AI Task Force along with experts in endoscopy, technology space, regulatory authorities, and other medical subspecialties initiated a consensus process that analyzed the current literature, highlighted potential areas, and outlined the necessary research in artificial intelligence (AI) to allow a clearer understanding of AI as it pertains to endoscopy currently. METHODS: A modified Delphi process was used to develop these consensus statements...

OBJECTIVE: To investigate how missing data in the patient problem list may impact racial disparities in the predictive performance of a machine learning (ML) model for emergency department (ED) triage. MATERIALS AND METHODS: Racial disparities may exist in the missingness of EHR data (eg, systematic differences in access, testing, and/or treatment) that can impact model predictions across racialized patient groups. We use an ML model that predicts patients' risk for adverse events to produce triage-level recommendations, patterned after a clinical decision support tool deployed at multiple EDs...

Aquatic invasive species (AIS) are one of the greatest threats to the functioning of aquatic ecosystems worldwide. Once an invasive species has been introduced to a new region, many governments develop management strategies to reduce further spread. Nevertheless, managing AIS in a new region is challenging because of the vast areas that need protection and limited resources. Spatial heterogeneity in invasion risk is driven by environmental suitability and propagule pressure, which can be used to prioritize locations for surveillance and intervention activities...

BACKGROUND: The effective management of epilepsy in women of child-bearing age necessitates a concerted effort from multidisciplinary teams. Nevertheless, there exists an inadequacy in the seamless exchange of knowledge among healthcare providers within this context. Consequently, it is imperative to enhance the availability of informatics resources and the development of decision support tools to address this issue comprehensively. MATERIALS AND METHODS: The development of the Women with Epilepsy of Child-Bearing Age Ontology (WWECA) adhered to established ontology construction principles...