Automating assessment of lifestyle counseling in electronic health records.

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 weight management-related counseling in clinical healthcare encounters. METHODS: The MediClass system with NLP capabilities was used to identify weight-management counseling in EHRs. 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 between January 1, 2007, and March 31, 2011, from two health systems, the accuracy of the MediClass processor for identifying these counseling elements was evaluated in postpartum visits of 600 women with gestational diabetes mellitus (GDM) compared to manual chart review as the 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 40% and 60% for each of the two health systems. The automated method identified many valid Assist cases 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 postpartum encounter records.

Documentation of the 5 as for smoking cessation by PCPs across distinct health systems.

OBJECTIVES: Physicians can help patients quit smoking using the 5 As of smoking cessation. This study aimed to (1) identify the proportion of known smokers that receive smoking cessation services in the course of routine clinical practice; (2) describe demographic and comorbidity characteristics of patients receiving the 5 As in these systems; and (3) evaluate differences in performance of the 5 As across health systems, gender, and age categories. STUDY DESIGN: Electronic medical records of 200 current smokers from 6 unique health systems (N = 1200) were randomly selected from 2006 to 2010. Primary care encounter progress notes were hand coded for occurrences of the 5 As. METHODS: Bivariate comparisons of delivery of the 3 smoking-cessation services by site, gender, and age category were analyzed using χ² tests. RESULTS: About 50% of smokers were advised to quit smoking, 39% were assessed for their readiness to quit, and 54% received some type of assistance to help them quit smoking. Only 2% had a documented plan for follow-up regarding their quitting efforts (arrange). Significant differences were found among sites for documentation of receiving the 5 As and between age groups receiving assistance with quitting. There was no statistically significant difference between genders in receipt of the 5 As. CONCLUSIONS: Documentation of adherence to the 5 As varied by site and some demographics. Adjustments to protocols for addressing cessation and readiness to quit may be warranted. Health systems could apply the methodology described in this paper to assess their own performance, and then use that as a basis to guide improvement initiatives.