Clinical Decision Support Systems (CDSS) are computer-based tools that leverage the analysis of large volumes of health data to assist healthcare professionals in making clinical decisions, whether preventive, diagnostic, or therapeutic. This review examines the impact of CDSS on clinical practice, highlighting both their potential benefits and their limitations and challenges. We detail the experience of clinical medical professionals in the development of a virtual control center for COVID-19 patients (C3 COVID-19) in Spain during the SARS-CoV-2 pandemic. This tool enabled real-time monitoring of clinical data for hospitalized COVID-19 patients, optimizing personalized and informed medical decision-making. CDSS can offer significant advantages, such as improving the quality of inpatient care, promoting evidence-based clinical and therapeutic decision-making, facilitating treatment personalization, and enhancing healthcare system efficiency and productivity. However, the implementation of CDSS presents challenges, including the need for physicians to become familiar with the systems and software, and the necessity for ongoing updates and technical support of the systems.
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http://dx.doi.org/10.37201/req/088.2024 | DOI Listing |
Biodegradation
December 2024
Department of Civil engineering, Islamic Azad university, Mashhad Branch, Iran.
The widespread use of pesticides, including diazinon, poses an increased risk of environmental pollution and detrimental effects on biodiversity, food security, and water resources. In this study, we investigated the impact of Potentially Toxic Elements (PTE) including Zn, Cd, V, and Mn on the degradation of diazinon in three different soils. We investigated the capability and performance of four machine learning models to predict residual pesticide concentration, including adaptive neuro-fuzzy inference system (ANFIS), support vector regression (SVR), radial basis function (RBF), and multi-layer perceptron (MLP).
View Article and Find Full Text PDFLangmuir
December 2024
Department of Physical Chemistry, Faculty of Chemistry and Petroleum Sciences, Bu-Ali Sina University, Hamedan 65167 ,Iran.
Interfacial solar evaporator generation (ISVG) is a new, cost-effective, and eco-friendly emerging method for water desalination. Two main criteria for evaluating ISVG performance are evaporation rate () and solar-to-vapor conversion efficiency (η). The main challenge of the previously presented models for the estimation of and η in 2D systems is that in most cases the calculated values are beyond the theoretical limits, > 1.
View Article and Find Full Text PDFBiometrics
October 2024
RAND Corporation, Pittsburgh, PA 15213, United States.
Health care decisions are increasingly informed by clinical decision support algorithms, but these algorithms may perpetuate or increase racial and ethnic disparities in access to and quality of health care. Further complicating the problem, clinical data often have missing or poor quality racial and ethnic information, which can lead to misleading assessments of algorithmic bias. We present novel statistical methods that allow for the use of probabilities of racial/ethnic group membership in assessments of algorithm performance and quantify the statistical bias that results from error in these imputed group probabilities.
View Article and Find Full Text PDFImplement Sci Commun
December 2024
Department of Health Promotion and Behavioral Sciences, School of Public Health, The University of Texas Health Science Center at Houston, 7000 Fannin Street, Houston, TX, 77030, USA.
Background: All for Them is a theory-based and evidence-informed multilevel, multicomponent program delivered through schools to increase HPV vaccination among medically underserved youth across Texas. Given the potential logistical challenges of program implementation, understanding how to best support the implementation and sustainment of the program is critical. The overall goals of this study are twofold: 1) develop a multifaceted implementation strategy, Implementing All for Them (IM-AFT); and 2) evaluate the impact of IM-AFT on implementation outcomes for schools and healthcare providers to successfully implement All for Them in their respective settings.
View Article and Find Full Text PDFBMC Med Inform Decis Mak
December 2024
Nivel, Netherlands Institute for Health Services Research, Otterstraat 118, Utrecht, 3513 CR, The Netherlands.
Background: At the beginning of the COVID-19 pandemic in 2020, little was known about the spread of COVID-19 in Dutch nursing homes while older people were particularly at risk of severe symptoms. Therefore, attempts were made to develop a nationwide COVID-19 repository based on routinely recorded data in the electronic health records (EHRs) of nursing home residents. This study aims to describe the facilitators and barriers encountered during the development of the repository and the lessons learned regarding the reuse of EHR data for surveillance and research purposes.
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