Background
Numerous population-based surveys indicate that overweight and obese patients can benefit from lifestyle counseling during routine clinical care.
Purpose
To determine if natural language processing (NLP) could be applied to information in the electronic health record (EHR) to automatically assess delivery of counseling related to weight management in clinical health care encounters.
Methods
The MediClass system with NLP capabilities was used to identify weight management counseling in EHR encounter records. Knowledge for the NLP application was derived from the 5As framework for behavior counseling: Ask (evaluate weight and related disease), Advise at-risk patients to lose weight, Assess patients’ readiness to change behavior, Assist through discussion of weight loss methods and programs and Arrange follow-up efforts including referral. Using samples of EHR data in 1/1/2007-3/31/2011 period from two health systems, the accuracy of the MediClass processor for identifying these counseling elements was evaluated in post-partum visits of 600 women with gestational diabetes mellitus (GDM) compared to manual chart review as gold standard. Data were analyzed in 2013.
Results
Mean sensitivity and specificity for each of the 5As compared to the gold standard was at or above 85%, with the exception of sensitivity for Assist which was measured at 40% and 60% respectively for each of the two health systems. The automated method identified many valid cases of Assist not identified in the gold standard.
Conclusions
The MediClass processor has performance capability sufficiently similar to human abstractors to permit automated assessment of counseling for weight loss in post-partum encounter records.