Notes

Med7: Any transferable specialized medical natural language running model for electronic wellbeing information.
The UKB is an open access resource available to health researchers across all scientific disciplines from both academia and industry with no preferential access or exclusivity. In this paper, we consider how we may best utilize the UKB CMR data to advance cardiovascular research and review notable achievements to date.
This research project aims to measure and evaluate the impact of health literacy on self-medication and to achieve a better understating of patients' behaviors.

A cross-sectional approach was conducted and participants were recruited outpatient clinics through convenience sampling. Health literacy was measured by Single Item Literacy Screener.

A total of 194 participants agreed to participate (63.9% were females). The results showed that more than half (57.2%) had adequate health literacy. Almost 30% of the participants were over the age of 50. The prevalence of self-medication was 74.2%. Nearly, two-thirds of the total participants reported self-administration of antibiotics. There was a significant relationship between the overall health literacy level and practice of self-medication.

Improving the health literacy level of the public can reduce inappropriate self-medication, especially the self-medication with antibiotics, which represented a high prevalence situation in our sample. Appropriate reading skills are important for accessing health information, using health care services, and achieving desirable health outcomes.
Improving the health literacy level of the public can reduce inappropriate self-medication, especially the self-medication with antibiotics, which represented a high prevalence situation in our sample. Appropriate reading skills are important for accessing health information, using health care services, and achieving desirable health outcomes.
The study sought to develop and empirically validate an integrative situational privacy calculus model for explaining potential users' privacy concerns and intention to install a contact tracing mobile application (CTMA).

A survey instrument was developed based on the extant literature in 2 research streams of technology adoption and privacy calculus. Survey participants (N = 853) were recruited from all 50 U.S. states. Partial least squares structural equation modeling was used to validate and test the model.

Individuals' intention to install a CTMA is influenced by their risk beliefs, perceived individual and societal benefits to public health, privacy concerns, privacy protection initiatives (legal and technical protection), and technology features (anonymity and use of less sensitive data). We found only indirect relationships between trust in public health authorities and intention to install CTMA. Pyrotinib molecular weight Sex, education, media exposure, and past invasion of privacy did not have a significant relationship either, but interestingly, older people were slightly more inclined than younger people to install a CTMA.

Our survey results confirm the initial concerns about the potentially low adoption rates of CTMA. Our model provides public health agencies with a validated list of factors influencing individuals' privacy concerns and beliefs, enabling them to systematically take actions to address these identified issues, and increase CTMA adoption.

Developing CTMAs and increasing their adoption is an ongoing challenge for public health systems and policymakers. This research provides an evidence-based and situation-specific model for a better understanding of this theoretically and pragmatically important phenomenon.
Developing CTMAs and increasing their adoption is an ongoing challenge for public health systems and policymakers. This research provides an evidence-based and situation-specific model for a better understanding of this theoretically and pragmatically important phenomenon.
The study sought to describe the contributions of clinical informatics (CI) fellows to their institutions' coronavirus disease 2019 (COVID-19) response.

We designed a survey to capture key domains of health informatics and perceptions regarding fellows' application of their CI skills. We also conducted detailed interviews with select fellows and described their specific projects in a brief case series.

Forty-one of the 99 CI fellows responded to our survey. Seventy-five percent agreed that they were "able to apply clinical informatics training and interest to the COVID-19 response." The most common project types were telemedicine (63%), reporting and analytics (49%), and electronic health record builds and governance (32%). Telehealth projects included training providers on existing telehealth tools, building entirely new virtual clinics for video triage of COVID-19 patients, and pioneering workflows and implementation of brand-new emergency department and inpatient video visit types. Analytics projects included reports and dashboards for institutional leadership, as well as developing digital contact tracing tools. For electronic health record builds, fellows directly contributed to note templates with embedded screening and testing guidance, adding COVID-19 tests to order sets, and validating clinical triage workflows.

Fellows were engaged in projects that span the breadth of the CI specialty and were able to make system-wide contributions in line with their educational milestones.

CI fellows contributed meaningfully and rapidly to their institutions' response to the COVID-19 pandemic.
CI fellows contributed meaningfully and rapidly to their institutions' response to the COVID-19 pandemic.
Therapeutic drug monitoring of anti-epileptic drugs is important to manage seizure control in patients with epilepsy. Oxcarbazepine is a second-generation anti-epileptic drug approved for use in pediatric patients, and eslicarbazepine acetate is a newer generation drug used as adjunctive therapy and monotherapy for partial-onset (focal) seizures. While several second and third generation anti-epileptic drugs have broader therapeutic efficacy in patients, these drugs can still have severe side effects and variable interpatient pharmacokinetics. Consequently, there is a need for accurate and sensitive analytical methods to support therapeutic drug monitoring.

An assay improvement for a LC-MS/MS method was developed for the major metabolite of oxcarbazepine and eslicarbazepine, licarbazepine (MHD), using a 13C-labeled form of the compound as the internal standard. Additionally, retrospective data analysis was used to compare the distribution of results observed in adult vs pediatric patients.

Accuracy and linearity across the analytical measuring range of 1 to 60 µg/mL was acceptable.
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