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A common research task in COVID-19 studies often involves the prevalence estimation of certain medical outcomes. Although point estimates with confidence intervals are typically obtained, a better approach is to estimate the entire posterior probability distribution of the prevalence, which can be easily accomplished with a standard Bayesian approach using binomial likelihood and its conjugate beta prior distribution. Using two recently published COVID-19 data sets, we performed Bayesian analysis to [...]

Accurate estimations of the seroprevalence of antibodies to severe acute respiratory syndrome coronavirus 2 need to properly consider the specificity and sensitivity of the antibody tests. In addition, prior knowledge of the extent of viral infection in a population may also be important for adjusting the estimation of seroprevalence. For this purpose, we have developed a Bayesian approach that can incorporate the variabilities of specificity and sensitivity of the antibody [...]

The study aimed to develop simplified diagnostic models for identifying girls with central precocious puberty (CPP), without the expensive and cumbersome gonadotropin-releasing hormone (GnRH) stimulation test, which is the gold standard for CPP diagnosis.

Family caregiving is an important public health issue, particularly with the aging population. In recent years, mobile health (mHealth) technology has emerged as a potential low-cost, scalable platform to address caregiver support needs, and thereby alleviate the burden on caregivers. This study sought to examine the support needs of family caregivers in their lived experiences of outpatient care to inform the development of a future mHealth intervention.

Coronavirus disease 2019, first reported in China in late 2019, has quickly spread across the world. The outbreak was declared a pandemic by the World Health Organization on March 11, 2020. Here, we describe our initial efforts at the University of Florida Health for processing of large numbers of tests, streamlining data collection, and reporting data for optimizing testing capabilities and superior clinical management. Specifically, we discuss clinical and pathology [...]

Electronic health records (EHRs) have become a common data source for clinical risk prediction, offering large sample sizes and frequently sampled metrics. There may be notable differences between hospital-based EHR and traditional cohort samples: EHR data often are not population-representative random samples, even for particular diseases, as they tend to be sicker with higher healthcare utilization, while cohort studies often sample healthier subjects who typically are more likely to participate [...]

Observational medical databases, such as electronic health records and insurance claims, track the healthcare trajectory of millions of individuals. These databases provide real-world longitudinal information on large cohorts of patients and their medication prescription history. We present an easy-to-customize framework that systematically analyzes such databases to identify new indications for on-market prescription drugs.

We developed a mobile application and secure patient data storage platform, FDA MyStudies, to address privacy, engagement, and extensibility challenges in mobile clinical research. The system extends the capabilities of the mobile frameworks Apple ResearchKit and ResearchStack through an intuitive front-end application and secure storage environment that can support health research studies. The platform supports single or multisite studies via role-based access and can be implemented within highly secure data [...]

The UK Biobank (UKB) is making primary care electronic health records (EHRs) for 500 000 participants available for COVID-19-related research. Data are extracted from four sources, recorded using five clinical terminologies and stored in different schemas. The aims of our research were to: (a) develop a semi-supervised approach for bootstrapping EHR phenotyping algorithms in UKB EHR, and (b) to evaluate our approach by implementing and evaluating phenotypes for 31 common biomarkers.

Learning health systems that conduct embedded research require infrastructure for the seamless adoption of clinical interventions; this infrastructure should integrate with electronic health record (EHR) systems and enable the use of existing data. As purchasers of EHR systems, and as critical partners, sponsors, and consumers of embedded research, healthcare organizations should advocate for EHR system functionality and data standards that will increase the capacity for embedded research in clinical settings [...]