HIE Data Used to Identify Homeless Patients

Feb. 16, 2015
Using health information exchange (HIE) data has helped researchers identify patients that are likely to be homeless, as well as helping them create a tool that could potentially better improve patient record matching.

Using health information exchange (HIE) data has helped researchers identify patients that are likely to be homeless, as well as helping them create a tool that could potentially better improve patient record matching.

The researchers analyzed address data from Healthix, a New York City–based health information exchange— to identify patterns that could indicate homelessness. Patients were categorized as likely to be homeless if they registered with the address of a hospital, homeless shelter, place of worship, or an address containing a keyword synonymous with “homelessness,” according to the researchers’ report, which was published in the Journal of the American Medical Informatics Association.

As of July 2013, the HIE organization linked records for more than 7 million individual patients across 32 major hospitals and 250 total participating facilities in New York City and Long Island. The researchers’ analysis required them to connect patient records across sites, determining which records belong to the same patient. The researchers think that the technique they presented may offer a tool to improve patient record matching.

 Hospitals and HIEs use algorithms that rely on patient demographic data, including address data, to match patient records, the researchers stated. The results of this record matching are stored in the registration system (master patient index, MPI) of each site and the HIE. If two patient records contain differing address information, the matching algorithm will likely split those records into two different patients, even if they correspond to one unique individual who has registered at different times with different addresses, the report explains. This fact is especially relevant for undomiciled patients, who register with more addresses and visit more healthcare facilities than the average patient. This issue could be mitigated by setting the MPI’s matching algorithm to down-weight address information for records belonging to patients having a previous instance of a proxy undomiciled address, they said.

 “We believe that better HIE record matching for homeless patients could improve HIE usefulness and HIE-enabled care coordination efforts aimed at helping this population,” the researchers concluded. “These findings demonstrate the difficulty of identifying homeless patients after they have accessed healthcare services. A patient’s housing status is frequently known to registration staff at the time a patient is registered, and we believe it may be beneficial to adopt a new policy that requires structured, standardized data on housing status to be collected whenever a patient registers for a healthcare encounter,” they said.

Sponsored Recommendations

Six Cloud Strategies to Combat Healthcare's Workforce Crisis

The healthcare workforce shortage is a complex challenge, but cloud communications offer powerful solutions to address it. These technologies go beyond filling gaps—they are transformin...

Transforming Healthcare with AI Powered Solutions

AI-powered solutions are revolutionizing healthcare by enhancing diagnostics, patient monitoring, and operational efficiency - learn how to integrate these innovations into your...

Enhancing Healthcare Through Strategic IT and AI Innovations

Learn how strategic IT and AI innovations are transforming healthcare - join Tomas Gregorio as he explores practical applications that enhance clinical decision-making, optimize...

The Intersection of Healthcare Compliance and Security in the Age of Deepfakes

As healthcare regulations struggle to keep up with rapid advancements in AI-driven threats like deepfakes, the security gaps have never been more concerning.