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Alkermes Announces Data From ALKS 4230 Clinical Development PubMed articles on BioPortfolio. Our PubMed references draw on over 21 million records from the medical literature. Here you can see the latest Alkermes Announces Data From ALKS 4230 Clinical Development articles that have been published worldwide.
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To address the need for automatically assessing the quality of clinical data in terms of accuracy, relevance, conformity, and completeness, through the concise development and application of an automated method which is able to automatically detect problematic fields and match clinical terms under a specific domain.
Data collection in clinical trials is becoming complex, with a huge number of variables that need to be recorded, verified, and analyzed to effectively measure clinical outcomes. In this study, we used data warehouse (DW) concepts to achieve this goal. A DW was developed to accommodate data from a large clinical trial, including all the characteristics collected. We present the results related to baseline variables with the following objectives: developing a data quality (DQ) control strategy and improving ...
Clinical trials, prospective research studies on human participants carried out by a distributed team of clinical investigators, play a crucial role in the development of new treatments in health care. This is a complex and expensive process where investigators aim to enroll volunteers with predetermined characteristics, administer treatment(s), and collect safety and efficacy data. Therefore, choosing top-enrolling investigators is essential for efficient clinical trial execution and is 1 of the primary dr...
Research on family accommodation is burgeoning, implicating it in the development, maintenance, and treatment of childhood anxiety. Additional data are needed to guide theory development and clinical application in this area. The factors underlying family accommodation measures have never been confirmed, nor have any test-retest data been reported. The study's objectives were to provide confirmatory data of the factorial structure and the first test-retest reliability data on the most widely used measure of...
With the advance of high-throughout sequencing technology and its extensive application in clinical diagnosis, analysis of sequencing data has become an important part of clinical diagnosis. To date, the development and establishment of various software and databases have made it convenient to extract useful information from massive amounts of high-throughput sequencing data. However, it is still a challenge for correlating the clinical-genetic diagnosis based on the above-mentioned sequence data with the s...
Data collection for clinical research can be difficult, and electronic health record systems can facilitate this process. The aim of this study was to describe and evaluate the secondary use of electronic health records in data collection for an observational clinical study. We used Cerner Millennium®, an electronic health record software, following these steps: (1) data crossing between the study's case report forms and the electronic health record; (2) development of a manual collection method for data n...
The development of treatments for heart failure (HF) is challenged by burdensome clinical trials. Reducing the need for extensive data collection and increasing opportunities for data compatibility between trials may improve efficiency and reduce resource burden. The Heart Failure Collaboratory (HFC) multi-stakeholder consortium sought to create a lean case report form (CRF) for use in HF clinical trials evaluating cardiac devices. The HFC convened patients, clinicians, clinical researchers, the U.S. Food ...
Novel approaches that complement and go beyond evidence-based medicine are required in the domain of chronic diseases, given the growing incidence of such conditions on the worldwide population. A promising avenue is the secondary use of electronic health records (EHRs), where patient data are analyzed to conduct clinical and translational research. Methods based on machine learning to process EHRs are resulting in improved understanding of patient clinical trajectories and chronic disease risk prediction, ...
To develop a multicenter, multistakeholder, prospective clinical registry of children and adolescents with migraine to support the collection of real-world data of sufficient quality to support regulatory submissions and provide site-based infrastructure support for future clinical trials.
We review current applications of Big Data in diabetes care and consider the future potential by carrying out a scoping study of the academic literature on Big Data and diabetes care. Healthcare data are being produced at ever-increasing rates, and this information has the potential to transform the provision of diabetes care. Big Data is beginning to have an impact on diabetes care through data research. The use of Big Data for routine clinical care is still a future application. Vast amounts of healthcare...
There exists a communication gap between the biomedical informatics community on one side and the computer science/artificial intelligence community on the other side regarding the meaning of the terms "semantic integration" and "knowledge representation". This gap leads to approaches that attempt to provide one-to-one mappings between data elements and biomedical ontologies. Our aim is to clarify the representational differences between traditional data management and semantic-web-based data management by ...
Patients with inflammatory bowel diseases (IBD) have increased risks of dysplasia and colitis-associated cancer (CAC). We evaluated the risk of development of high-grade dysplasia (HGD) or CAC after diagnosis of dysplasia using data from a national cohort of patients with IBD.
A clinical pathway is one of the tools used to support clinical decision making that provides a standardized care process in a specific context. The objective of this research was to develop a method for building data-driven clinical pathways using electronic health record data.
Clinical supervisors, who support and assess health students' clinical learning, encounter many challenges. Professional development opportunities for clinical supervisors to overcome the challenges are available but are often designed to meet organisational and tertiary provider administrative needs, rather than the needs of intended target groups.
The use of "big data" for pediatric hearing research requires new approaches to both data collection and research methods. The widespread deployment of electronic health record systems creates new opportunities and corresponding challenges in the secondary use of large volumes of audiological and medical data. Opportunities include cost-effective hypothesis generation, rapid cohort expansion for rare conditions, and observational studies based on sample sizes in the thousands to tens of thousands. Challenge...
Recognition and treatment of malnutrition in pediatric oncology patients is crucial because it is associated with increased morbidity and mortality. Nutrition-relevant data collected from cancer clinical trials and nutrition-specific studies are insufficient to drive high-impact nutrition research without augmentation from additional data sources. To date, clinical big data resources are underused for nutrition research in pediatric oncology. Health-care big data can be broadly subclassified into three clin...
Electronic medical records (EMR) contain numerical data important for clinical outcomes research, such as vital signs and cardiac ejection fractions (EF), which tend to be embedded in narrative clinical notes. In current practice, this data is often manually extracted for use in research studies. However, due to the large volume of notes in datasets, manually extracting numerical data often becomes infeasible. The objective of this study is to develop and validate a natural language processing (NLP) tool th...
The increasing adoption of electronic health records (EHRs) in clinical practice holds the promise of improving care and advancing research by serving as a rich source of data, but most EHRs allow clinicians to enter data in a text format without much structure. Natural language processing (NLP) may reduce reliance on manual abstraction of these text data by extracting clinical features directly from unstructured clinical digital text data and converting them into structured data.
Although randomized clinical trials are considered to be the criterion standard for generating clinical evidence, the use of real-world evidence to evaluate the efficacy and safety of medical interventions is gaining interest. Whether observational data can be used to address the same clinical questions being answered by traditional clinical trials is still unclear.
The development of new management strategies for women presenting with placenta accreta spectrum requires quality epidemiology data which have so far been limited by the high variability in clinical and histopathologic data confirming the diagnosis at birth.
Poor translation of efficacy data derived from animal models can lead to clinical trials unlikely to benefit patients-or even put them at risk-and is a potential contributor to costly and unnecessary attrition in drug development.
The treatment and care of individuals who have a Difference of Sex Development (DSD) have been revised over the past two decades and new guidelines have been published. In order to study the impact of treatments and new forms of management in these rare and heterogeneous conditions, standardized assessment procedures across centres are needed. Diagnostic work-up and detailed genital phenotyping are crucial at first assessment. DSDs may affect general health, have associated features or lead to comorbidities...
This article will describe the outcomes associated with restructuring clinical nurse specialists (CNSs) into a centralized model with dedicated efforts focused on team and individual development.