Webinar: The Drexel Story: Reducing manual chart review for cohort selection with Natural Language Processing
If you are looking at thousands of patient charts to identify specific cohorts for clinical and observational studies, you might miss out on crucial information presented in EHR clinical notes records. While anybody in an IT department can identify a diagnosis in the discrete fields such as the problem list, they might miss out on critical information from EHRs that are contained in non-discrete fields, such as patient notes. Different providers may document the same diagnoses in many different ways - this process is seldom standardized. Linguamatics Natural Language Processing (NLP) technology can provides an augmented intelligence (AI) solution, which narrows down the number of patients’ charts clinicians need to look at.
Using Linguamatics, instead of residents having to review at 5,700 many thousands of charts, Drexel was able to reduce manual review to only 1,150 (1 in 6 charts) - a manual chart review reduction of by over 80%, a huge saving of time and related costs for the Drexel team. A complete analysis of the information within the EHR also allows for far more accurate decisions.
In this webinar you will learn :
- How Drexel was able to reduce manual chart review by 80% to 1 in 6 charts
- How NLP can be used across healthcare organizations to gain significant insights from clinician notes with the EHRs, increasing efficiency and improving patient outcomes