Decision support tools

PURPOSE: Antibiotic overuse has increased over time related to provider knowledge gaps about best practices, provider perception of patient expectations on receiving an antibiotic, possible pressure to see patients in a timely fashion, and concerns about decreased patient satisfaction when an antibiotic is not prescribed. The Centers for Disease Control and Prevention estimates that up to 30% of antibiotics are inappropriately prescribed in the outpatient setting. APPROACH: This quality improvement project consisted of a multimodal approach to decrease inappropriate antibiotic prescribing for viral upper respiratory infections (URIs) by using provider education, passive patient education, and clinical decision support tools based on Centers for Disease Control and Prevention recommendations and the Be Antibiotic Aware tool...

BACKGROUND: Technological advancement has led to the growth and rapid increase of tuberculosis (TB) medical data generated from different health care areas, including diagnosis. Prioritizing better adoption and acceptance of innovative diagnostic technology to reduce the spread of TB significantly benefits developing countries. Trained TB-detection rats are used in Tanzania and Ethiopia for operational research to complement other TB diagnostic tools. This technology has increased new TB case detection owing to its speed, cost-effectiveness, and sensitivity...

BACKGROUND: People seeking abortion in early pregnancy have the choice between medication and procedural options for care. The choice is preference-sensitive-there is no clinically superior option and the choice depends on what matters most to the individual patient. Patient decision aids (PtDAs) are shared decision-making tools that support people in making informed, values-aligned health care choices. OBJECTIVE: We aimed to develop and evaluate the usability of a web-based PtDA for the Canadian context, where abortion care is publicly funded and available without legal restriction...

BACKGROUND: Though there has been considerable effort to implement machine learning (ML) methods for health care, clinical implementation has lagged. Incorporating explainable machine learning (XML) methods through the development of a decision support tool using a design thinking approach is expected to lead to greater uptake of such tools. OBJECTIVE: This work aimed to explore how constant engagement of clinician end users can address the lack of adoption of ML tools in clinical contexts due to their lack of transparency and address challenges related to presenting explainability in a decision support interface...

Breast cancer chemotherapy/immunotherapy can be associated with treatment-limiting cardiotoxicity. Radiomics techniques applied to ultrasound, known as ultrasomics, can be used in cardio-oncology to leverage echocardiography for added prognostic value. To utilize ultrasomics features collected prior to antineoplastic therapy to enhance prediction of mortality and heart failure (HF) in patients with breast cancer. Patients were retrospectively recruited in a study at the West Virginia University Cancer Institute...

OBJECTIVE: This case series explored the integration of smartwatches in a community mental health service to support severe mental illness (SMI) management and intervention. We examined whether biometric data provided by smartwatches could help to predict relapse and inform treatment decisions. METHOD: Four Australian SMI outpatients of mixed diagnoses (age range = 19-24) were selected from a prior study. Clinicians accessed patients' biometric data (activity, sleep, heart rate, and electrodermal activity) through smartwatches...

Grasslands cover approximately 24% of the Earth's surface and are the main feed source for cattle and other ruminants. Sustainable and efficient grazing systems require regular monitoring of the quantity and nutritive value of pastures. This study demonstrates the potential of estimating pasture leaf forage mass (FM), crude protein (CP) and fiber content of tropical pastures using Sentinel-2 satellite images and machine learning algorithms. Field datasets and satellite images were assessed from an experimental area of Marandu palisade grass (Urochloa brizantha sny...

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is the fourth most important cause of death in high-income countries. Inappropriate use of COPD inhaled therapy, including the low adherence (only 10% to 40% of patients reporting an adequate compliance) may shrink or even nullify the proven benefits of these medications. As such, an accurate prediction algorithm to assess at national level the risk of COPD exacerbation might be relevant for general practictioners (GPs) to improve patient's therapy...

BACKGROUND: The syndemic nature of gonococcal infections and HIV provides an opportunity to develop a synergistic intervention tool that could address the need for adequate treatment for gonorrhea, screen for HIV infections, and offer pre-exposure prophylaxis (PrEP) for persons who meet the criteria. By leveraging information available on electronic health records, a clinical decision support (CDS) system tool could fulfill this need and improve adherence to Centers for Disease Control and Prevention (CDC) treatment and screening guidelines for gonorrhea, HIV, and PrEP...

BACKGROUND:  Early identification of patients at higher risk of death and hospital admission is an important problem in Emergency Departments (ED). Most triage scales were developed before current electronic healthcare records were developed. The implementation of a national Emergency Care Data Set (ECDS) allows for the standardised recording of presenting complaints and the use of Electronic Patient Records (EPR) offers the potential for automated triage. The mortality risk and need for hospital admission associated with the different presenting complaints in a standardised national data set has not been previously reported...

The expansion of Internet access from urban to rural and coastal areas has changed all aspects of life, including lifestyles and work practices. Although several studies have shown that Internet use is essential in the fisheries sector, more information about the link between Internet usage and subjective well-being among small-scale fishermen is needed. This study is the first attempt to investigate the effect of Internet use on subjective well-being, particularly for small-scale fishers. This study used cross-sectional data from 220 respondents in East Java, Indonesia...

BACKGROUND/AIM: We aimed to validate clinical decision support tools (CDSTs) to predict real-life effectiveness of vedolizumab (VDZ) in patients with inflammatory bowel disease. METHODS: We retrospectively enrolled patients with Crohn's disease (CD) or ulcerative colitis (UC) treated with VDZ at 10 tertiary referral centres in Korea between January 2017 and November 2021. We assessed clinical remission (CREM) and response (CRES), corticosteroid-free clinical remission (CSF-CREM) and response (CSF-CRES), biochemical response based on C-reactive protein (BioRES[CRP]) and faecal calprotectin (BioRES[FC]), endoscopic healing (EH), and the need to optimise or switch drugs based on CDST-defined response groups...

BACKGROUND: COVID-19 and bacterial/fungal coinfections have posed significant challenges to human health. However, there is a lack of good tools for predicting coinfection risk to aid clinical work. OBJECTIVE: We aimed to investigate the risk factors for bacterial/fungal coinfection among COVID-19 patients and to develop machine learning models to estimate the risk of coinfection. METHODS: In this retrospective cohort study, we enrolled adult inpatients confirmed with COVID-19 in a tertiary hospital between January 1 and July 31, 2023, in China and collected baseline information at admission...

Milk recording is a critical tool in dairy farming, providing individual cow information. When used effectively, this data contributes to on-farm productivity, herd health management decisions and supports prudent veterinary prescribing of antimicrobials. Although an industry and government priority, uptake has been relatively slow in Ireland. This multi-methods, three-part study aimed to gain a comprehensive understanding of the benefits to farm performance, and factors driving uptake of milk recording on Irish dairy farms...

OBJECTIVE: Patients with an unruptured abdominal aortic aneurysm (AAA) at the surgical threshold may benefit from aneurysmal exclusion either by open surgery or endovascular repair. A patient decision aid (PtDA) could be useful to help patients and their surgeons choose between the two techniques. The aim of this study was to develop a shared medical decision support tool, in french language, for the surgical treatment of AAA. METHODS: Following the steps recommended by the International Patient Decision Aids Standards, we carried out a qualitative study using semi-structured interviews with patients and vascular surgeons and focus group with patients to identify their main points of interest...

BACKGROUND: The increasing utilization of large language models (LLMs) in Generative Artificial Intelligence across various medical and dental fields, and specifically orthodontics, raises questions about their accuracy. OBJECTIVE: This study aimed to assess and compare the answers offered by four LLMs: Google's Bard, OpenAI's ChatGPT-3.5, and ChatGPT-4, and Microsoft's Bing, in response to clinically relevant questions within the field of orthodontics. MATERIALS AND METHODS: Ten open-type clinical orthodontics-related questions were posed to the LLMs...

In industry 4.0, where the automation and digitalization of entities and processes are fundamental, artificial intelligence (AI) is increasingly becoming a pivotal tool offering innovative solutions in various domains. In this context, nutrition, a critical aspect of public health, is no exception to the fields influenced by the integration of AI technology. This study aims to comprehensively investigate the current landscape of AI in nutrition, providing a deep understanding of the potential of AI, machine learning (ML), and deep learning (DL) in nutrition sciences and highlighting eventual challenges and futuristic directions...

Reporting key dietary indicators from sales data can help us guide store decision makers in developing effective store policy to support healthier customer purchases. We aimed to develop a web-based reporting tool of key dietary indicators from sales data to support health-promoting policy and practice in stores in geographically remote Aboriginal and Torres Strait Islander communities. Tool development included identifying key dietary indicators (informed by sales data from 31 stores), community consultation (19 Aboriginal and Torres Strait Islander store directors and two store managers) and a web-build...

INTRODUCTION: Point-of-care ultrasound has become a universal practice, employed by physicians across various disciplines, contributing to diagnostic processes and decision-making. AIM: To assess the association of reduced (<50%) left-ventricular ejection fraction (LVEF) based on prospective point-of-care ultrasound operated by medical students using an artificial intelligence (AI) tool and 1-year primary composite outcome, including mortality and readmission for cardiovascular-related causes...

BACKGROUND: Cutaneous melanoma remains an increasing global public health burden, particularly in fair-skinned populations. Advancing technologies, particularly artificial intelligence (AI), may provide an additional tool for clinicians to help detect malignancies with a more accurate success rate. This systematic review aimed to report the performance metrics of commercially available convolutional neural networks (CNNs) tasked with detecting MM. METHODS: A systematic literature search was performed using CINAHL, Medline, Scopus, ScienceDirect and Web of Science databases...