The IADC has leveraged NLP methods to define data elements of interest which are captured in the form of unstructured free text notes. Using the INPC as a primary data source, the IADC has built numerous algorithms which can help track outcomes which may not be well captured as structured data. Data Requestors can work with the IADC to determine if their project could benefit from some of the algorithms already developed, or help define new methods for uncovering other types of data in the clinical record.
To date, the IADC have worked with research teams to build NLP algorithms which help identify populations who have abused or misused opioids, as well as algorithms aimed at identifying social insecurities of individuals including:
- Housing Instability
- Unemployment
- Financial insecurity
- History of incarceration
- Transportation issues