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Developing algorithms to extract phenotypes from electronic health records (EHRs) can be challenging and time-consuming. We developed PheMap, a high-throughput phenotyping approach that leverages multiple independent, online resources to streamline the phenotyping process within EHRs.

The lack of precise and inclusive gender, sex, and sexual orientation (GSSO) data in electronic health records (EHRs) is perpetuating inequities of sexual and gender minorities (SGM). We conducted a rapid review on how GSSO documentation in EHRs should be modernized to improve the health of SGM.

In recent years numerous studies have achieved promising results in Alzheimer's Disease (AD) detection using automatic language processing. We systematically review these articles to understand the effectiveness of this approach, identify any issues and report the main findings that can guide further research.

Reducing risk of coronavirus disease 2019 (COVID-19) infection among healthcare personnel requires a robust occupational health response involving multiple disciplines. We describe a flexible informatics solution to enable such coordination, and we make it available as open-source software.

The growing complexity of data systems in health care has precipitated increasing demand for clinical informatics subspecialists. The first board certification exam for the clinical informatics subspecialty was offered in 2013. Characterizing trends in this novel workforce is important to inform its development.

Global pandemics call for large and diverse healthcare data to study various risk factors, treatment options, and disease progression patterns. Despite the enormous efforts of many large data consortium initiatives, scientific community still lacks a secure and privacy-preserving infrastructure to support auditable data sharing and facilitate automated and legally compliant federated analysis on an international scale. Existing health informatics systems do not incorporate the latest progress in modern security and [...]

Health and healthcare disparities continue despite clinical, research, and policy efforts. Large clinical datasets may not contain data relevant to healthcare disparities and leveraging these for research may be crucial to improve health equity. The Health Disparities Collaborative Research Group was commissioned by the Patient-Centered Outcomes Research Institute to examine the data science needs for quality and complete data and provide recommendations for improving data science around health disparities. The [...]

The study sought to understand the potential roles of a future artificial intelligence (AI) documentation assistant in primary care consultations and to identify implications for doctors, patients, healthcare system, and technology design from the perspective of general practitioners.

This integrative review identifies and analyzes the extant literature to examine the integration of social determinants of health (SDoH) domains into electronic health records (EHRs), their impact on risk prediction, and the specific outcomes and SDoH domains that have been tracked.