Neither Words nor Images: Health Departments' and Hospitals' Use of Twitter During COVID-19 Had Limited Racial Representation and Content on Disparities Decreased Over Time.

Objective: To determine the degree to which hospitals and state health departments used written content or visual representation on social media to draw attention to racial disparities during the COVID-19 pandemic.

Study Design: A retrospective analysis, using Twitter content (words and images) between May-June 2020 and May-June 2021 from organizations in the 5 states with the largest documented racial disparities in COVID-19-related mortality.

Main Outcomes: All tweets and retweets (n = 6790) were coded along several lines.

Personal Location as Health-Related Data: Public Knowledge, Public Concern, and Personal Action.

Objectives: Personal health information (PHI), including health status and behaviors, are often associated with personal locations. Smart devices and other technologies routinely collect personal location. Therefore, technologies collecting personal location do not just create generic questions of privacy, but specific concerns related to PHI.

Funding Community Health Activities: An Experiment Comparing Health Foundation's Priorities to Those of Public Health Agencies, Hospitals, and Nonprofit Organizations.

Context: Health foundations provide significant financial resources for community health. Foundation priorities, therefore, can play a key role in setting community agenda, but little is known about the criteria foundations use to prioritize projects.

Objective: To understand the priorities that guide decision makers in health foundations and compare those priorities with what is known about nonprofit hospitals, public health, and community-based nonprofits.

Electronic Health Records as Biased Tools or Tools Against Bias: A Conceptual Model.

Unlabelled: Policy Points Electronic health records (EHRs) are subject to the implicit bias of their designers, which risks perpetuating and amplifying that bias over time and across users. If left unchecked, the bias in the design of EHRs and the subsequent bias in EHR information will lead to disparities in clinical, organizational, and policy outcomes. Electronic health records can instead be designed to challenge the implicit bias of their users, but that is unlikely to happen unless incentivized through innovative policy.