Objectives: To investigate whether and what user data are collected by health related mobile applications (mHealth apps), to characterise the privacy conduct of all the available mHealth apps on Google Play, and to gauge the associated risks to priva
Risk adjustment of quality measures using clinical risk factors is widely accepted; risk adjustment using social risk factors remains controversial. We argue here that social risk adjustment is appropriate and necessary in defined circumstances and t
Examining the feasibility of developing an index measure for the social determinants of health using public data is needed. We examined these characteristics at the ZIP code in California and New York using public data extracted from the US
Introduction: Recently, numerous studies have linked social determinants of health (SDoH) with clinical outcomes. While this association is well known, the interfacility variability of these risk favors within the Veterans Health Administration (VHA)
The work of knitting together large government data systems so that they seamlessly connect and provide customer-friendly services to the public is difficult yet achievable and valuable. If this type of data sharing was easy, every
This report is being jointly published by the Government Accountability Office (GAO) and the National Academy of Medicine (NAM). Part One of this joint publication is the full presentation of GAO’s Technology Assessment: Artificial
This article describes an explosion in the availability of individual-level public administrative data in the United States and worldwide. These datasets can be used as stand-alone resources or linked across different sources. These new res
The Sequoia Project patient identity management experts partnered with Blue Cross Blue Shield System to apply A Framework for Cross-Organizational Patient Identity Management to the payer community and develop person matching strategies across its 36
November 18, 2020 - Stakeholders and healthcare professionals across the country developed 10 patient data sharing principles. These principles intend to help guide health organizations and universities toward the appropriate use of data
COVID-19 has highlighted the need to invest in a robust public health system that supports health equity. “It’s critical that we bolster the secure flow of de-identified health information into public health surveillance systems,” said W
To help providers identify primary care patients with social risks, researchers at Regenstrief Institute and Indiana University turned to machine learning technology. The team developed Uppstroms, a machine learning application that iden
