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A multi-institutional research team recently reported that veterans with both PTSD and unmet social needs appear to have higher rates of dementia or cognitive impairment years later. The study involved 3,817,970 veterans—and, therefore, millions of data points—so the team relied on support from researchers in the Manning College of Information and Computer Sciences (CICS) at UMass Amherst, who helped process the large amounts of data needed for the study.

Avijit Mitra, who was a UMass CICS doctoral student at the time and now works as an applied scientist II at Amazon, had developed an NLP (natural language processing, a subfield of AI focused on helping computers understand and generate human language) system while at UMass.

For the PTSD study, now published in JAMA Network Open, Mitra applied that same system to detect health-related social needs (HRSNs)—individual social circumstances that can affect health, such as financial problems, housing instability and food insecurity—and investigate potential connections between HRSNs, PTSD, and mild cognitive impairment, Alzheimer's disease and Alzheimer's–related dementia.

Traditionally, epidemiological research has depended on claims and coded EHR (electronic health records) fields, said Hong Yu, a CICS adjunct professor who leads the BioNLP Lab at UMass Amherst and UMass Lowell.

EHR narratives such as doctor's visit notes, discharge summaries and history reports, for example, have often been neglected by epidemiologists due to concerns about bias within the documentation, as well as the difficulty in extracting information reliably, especially on a large scale, Yu noted.

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