Clinical decision support system

BACKGROUND: Clinical decision support (CDS) tools that incorporate machine learning-derived content have the potential to transform clinical care by augmenting clinicians' expertise. To realize this potential, such tools must be designed to fit the dynamic work systems of the clinicians who use them. We propose the use of academic detailing-personal visits to clinicians by an expert in a specific health IT tool-as a method for both ensuring the correct understanding of that tool and its evidence base and identifying factors influencing the tool's implementation...

OBJECTIVE: To evaluate the effectiveness of Cogmed Working Memory Training (Cogmed) in improving working memory (WM) and decision making (DM) in childhood traumatic brain injury (TBI), and any associated increases in functional outcomes such as academic achievement in mathematics, behavior, social skills, and quality of life. METHOD: A randomized controlled trial of the Cogmed (RM version) intervention for children with TBI. A total of 69 children post-TBI were screened for WM impairments, of which 31 eligible participants ( M age : 10...

Critical care medicine in the 21st century has witnessed remarkable advancements that have significantly improved patient outcomes in intensive care units (ICUs). This abstract provides a concise summary of the latest developments in critical care, highlighting key areas of innovation. Recent advancements in critical care include Precision Medicine: Tailoring treatments based on individual patient characteristics, genomics, and biomarkers to enhance the effectiveness of therapies. The objective is to describe the recent advancements in Critical Care Medicine...

INTRODUCTION: Clinical decision support (CDS) systems (CDSSs) that integrate clinical guidelines need to reflect real-world co-morbidity. In patient-specific clinical contexts, transparent recommendations that allow for contraindications and other conflicts arising from co-morbidity are a requirement. In this work, we develop and evaluate a non-proprietary, standards-based approach to the deployment of computable guidelines with explainable argumentation, integrated with a commercial electronic health record (EHR) system in Serbia, a middle-income country in West Balkans...

Polypharmacy remains an important challenge for patients with extensive medical complexity. Given the primary care shortage and the increasing aging population, effective polypharmacy management is crucial to manage the increasing burden of care. The capacity of large language model (LLM)-based artificial intelligence to aid in polypharmacy management has yet to be evaluated. Here, we evaluate ChatGPT's performance in polypharmacy management via its deprescribing decisions in standardized clinical vignettes...

OBJECTIVE: The aim of this study is to assess the efficacy of employing a deep learning methodology for the automated identification and enumeration of permanent teeth in bitewing radiographs. The experimental procedures and techniques employed in this study are described in the following section. STUDY DESIGN: A total of 1248 bitewing radiography images were annotated using the CranioCatch labeling program, developed in Eskişehir, Turkey. The dataset has been partitioned into 3 subsets: training (n = 1000, 80% of the total), validation (n = 124, 10% of the total), and test (n = 124, 10% of the total) sets...

AIMS: The objective of this study was to develop a two-year overall survival model for inoperable stage I-III non-small cell lung cancer (NSCLC) patients using routine radiation oncology data over a federated (distributed) learning network and evaluate the potential of decision support for curative versus palliative radiotherapy. METHODS: A federated infrastructure of data extraction, de-identification, standardisation, image analysis, and modelling was installed for seven clinics to obtain clinical and imaging features and survival information for patients treated in 2011-2019...

A pathology-supported genetic testing (PSGT) framework was established in South Africa to improve access to precision medicine for patients with breast carcinomas. Nevertheless, the frequent identification of variants of uncertain significance (VUSs) with the use of genome-scale next-generation sequencing has created a bottleneck in the return of results to patients. This review highlights the importance of incorporating functional genomics into the PSGT framework as a proposed initiative. Here, we explore various model systems and experimental methods available for conducting functional studies in South Africa to enhance both variant classification and clinical interpretation...

BACKGROUND: Carers often assume key roles in cancer care. However, many carers report feeling disempowered and ill-equipped to support patients. Our group published evidence-based guidelines (the Triadic Oncology [TRIO] Guidelines) to improve oncology clinician engagement with carers and the management of challenging situations involving carers. OBJECTIVE: To facilitate implementation of the TRIO Guidelines in clinical practice, we aimed to develop, iteratively refine, and conduct user testing of a suite of evidence-based and interactive web-based education modules for oncology clinicians (e-Triadic Oncology [eTRIO]), patients with cancer, and carers (eTRIO for Patients and Carers [eTRIO-pc])...

Wrong dose calculation medication errors are widespread in pediatric patients mainly due to weight-based dosing. PediPain app is a clinical decision support tool that provides weight- and age- based dosages for various analgesics. We hypothesized that the use of a clinical decision support tool, the PediPain app versus pocket calculators for calculating pain medication dosages in children reduces the incidence of wrong dosage calculations and shortens the time taken for calculations. The study was a randomised controlled trial comparing the PediPain app vs...

BACKGROUND: Managing postoperative pain while minimizing opioid-related adverse drug events (ORADEs) remains a significant challenge. The OPI•AID Zone Tool is proposed as a novel clinical decision support tool that - both graphically and in a scoring-system - represents the relationship between pain management and the occurrence of ORADEs, aiming to enhance patient outcomes in postoperative care. The OPI•AID Zone Tool places pain score on the x-axis and an ORADE score on the y-axis, and stratifies patients into five zones to reflect the composite impact of pain severity and ORADEs on the quality of postoperative patient care...

Model-based tumor growth inhibition (TGI) metrics are increasingly used to predict overall survival (OS) data in Phase III immunotherapy clinical trials. However, there is still a lack of understanding regarding the differences between two-stage or joint modeling methods to leverage Phase I/II trial data and help early decision-making. A recent study showed that TGI metrics such as the tumor growth rate constant KG may have good operating characteristics as early endpoints. This previous study used a two-stage approach that is easy to implement and intuitive but prone to bias as it does not account for the relationship between the longitudinal and time-to-event processes...

Mental health professionals are tasked with making difficult clinical decisions in treatment settings. In the forensic system, decision making regarding staff supervised community outings (SSCOs) provides a significant challenge due to the need to balance patient liberties, mental health recovery, and public safety. This study explored the characteristics and rehabilitative nature of SSCOs, characteristics of patients attending SSCOs, and any adverse events that occurred during the outings. Employing a cross-sectional design, 110 patients who participated in SSCOs over a one-year period from a Canadian Forensic Psychiatric Hospital were included...

BACKGROUND: Sub-Saharan Africa is the region with the highest under-five mortality rate globally. Child healthcare decisions should be based on rigorously developed evidence-informed guidelines. The Global Evidence, Local Adaptation (GELA) project is enhancing capacity to use global research to develop locally relevant guidelines for newborn and child health in South Africa (SA), Malawi, and Nigeria. The first step in this process was to identify national priorities for newborn and child health guideline development, and this paper describes our approach...

OBJECTIVES: Exploring clinical information-seeking behaviour (CISB) and its associated factors contributes to its theoretical advancement and offers a valuable framework for addressing physicians' information needs. This study delved into the dimensions, interactions, strategies and determinants of CISB among physicians at the point of care. DESIGN: A grounded theory study was developed based on Strauss and Corbin's approach. Data were collected by semistructured interviews and then analysed through open, axial and selective coding...

OBJECTIVE: System-level safety measures do not exist to ensure that patients with iron deficiency anaemia (IDA) undergo proper diagnostic evaluations. We sought to determine if a set of EHR (electronic health record) tools and an expedited referral workflow increase short-term completion of bidirectional endoscopy in higher risk patients with IDA. MATERIALS AND METHODS: We conducted a pragmatic, cluster-randomised trial randomised by primary care physician (PCP) that included 16 PCPs and 316 patients with IDA...

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...

BACKGROUND: The 'PenCS Flu Topbar' app was deployed in Central Queensland (CQ), Australia, medical practices through a pilot programme in March 2021. METHODS: We evaluated the app's user experience and examined whether the introduction of 'PenCS Flu Topbar' in medical practices could improve the coverage of NIP-funded influenza vaccinations. We conducted a mixed-method study including a qualitative analysis of in-depth interviews with key end-users and a quantitative analysis of influenza vaccine administrative data...

Polatuzumab vedotin is a CD79b-directed antibody-drug conjugate that targets B cells and delivers the cytotoxic payload monomethyl auristatin E (MMAE). The phase III POLARIX study (NCT03274492) evaluated polatuzumab vedotin in combination with rituximab, cyclophosphamide, doxorubicin, and prednisone (R-CHP) as first-line treatment of diffuse large B-cell lymphoma (DLBCL). To examine dosing decisions for this regimen, population pharmacokinetic (popPK) analysis, using a previously developed popPK model, and exposure-response (ER) analysis, were performed...