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To gain insights into how data vendor companies (DVs), an important source of de-identified/anonymized licensed patient-related data (D/ALD) used in clinical informatics research in life sciences and the pharmaceutical industry, characterize, conduct, and communicate data quality assessments to researcher purchasers of D/ALD.

Electronic health records (EHRs) are often used for recruitment into research studies, as they efficiently facilitate targeted outreach. While studies increasingly are reaching out to potential participants through the EHR patient portal, there is little available information about which approaches are most effective. We surveyed all investigators at one academic medical center who had used the Epic MyChart patient portal for recruitment. We found that messages were typically adapted for [...]

Hypertension has long been recognized as one of the most important predisposing factors for cardiovascular diseases and mortality. In recent years, machine learning methods have shown potential in diagnostic and predictive approaches in chronic diseases. Electronic health records (EHRs) have emerged as a reliable source of longitudinal data. The aim of this study is to predict the onset of hypertension using modern deep learning (DL) architectures, specifically long short-term memory [...]

Despite smartphone ownership becoming ubiquitous, it is unclear whether and where disparities persist in experience using health apps. In 2 diverse samples of adults with type 2 diabetes collected 2017-2018 and 2020-2021, we examined adjusted disparities in smartphone ownership and health app use by age, gender, race, education, annual household income, health insurance status, health literacy, and hemoglobin A1c. In the earlier sample (N = 422), 87% owned a smartphone and 49% [...]

[This corrects the article DOI: 10.1093/jamiaopen/ooac073.].

One challenge that arises when analyzing mobile health (mHealth) data is that updates to the proprietary algorithms that process these data can change apparent patterns. Since the timings of these updates are not publicized, an analytic approach is necessary to determine whether changes in mHealth data are due to lifestyle behaviors or algorithmic updates. Existing methods for identifying changepoints do not consider multiple types of changepoints, may require prespecifying the [...]

To carry out exhaustive data-driven computations for the performance of noninvasive vital signs heart rate (HR), respiratory rate (RR), peripheral oxygen saturation (SpO2), and temperature (Temp), considered both independently and in all possible combinations, for early detection of sepsis.

To close gaps between research and clinical practice, tools are needed for efficient pragmatic trial recruitment and patient-reported outcome collection. The objective was to assess feasibility and process measures for patient-reported outcome collection in a randomized trial comparing electronic health record (EHR) patient portal questionnaires to telephone interview among adults with epilepsy and anxiety or depression symptoms.

One of the increasingly accepted methods to evaluate the privacy of synthetic data is by measuring the risk of membership disclosure. This is a measure of the F1 accuracy that an adversary would correctly ascertain that a target individual from the same population as the real data is in the dataset used to train the generative model, and is commonly estimated using a data partitioning methodology with a 0.5 partitioning [...]

The purpose of this study is to provide an overview of apps to help control the spread of Covid-19 in Germany and rate them according to standardized instruments.