Social risk factors such as financial instability and housing insecurity are increasingly recognized as influencing health. But unlike diagnosis codes, prescription information, lab or other test reports, social risk factors do not adhere to standardized, controlled terminology in a patient's electronic medical record, making this information difficult to extract from the clinical notes where they typically are found.
, looking for key words or phrases that were likely to indicate difficulty with housing or financial needs of patients at a health care system in a new and quite different geographic area.
"Is a patient diagnosed with diabetes? It's relatively easy to find that information in an electronic health record because the same words and codes are more likely to be used inin central Indiana as are used in Florida or elsewhere in the U.S. But social risk factors don't have nearly as established and widely used words, phrases or codes to identify them.
"The more that we can disseminate and adapt natural language processing and other artificial intelligence methods that fully describe a patient to give clinicians a full 360 understanding of patients' needs, the better. If we can extract social information more efficiently, it's less costly. Then we can start to take what we'd call a population health perspective."
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