ABSTRACT
Medication non-adherence is common and the physicians awareness of it may be an important factor in clinical decision making. Few sources of data on physician awareness of medication non-adherence are available. We have designed an algorithm to identify documentation of medication non-adherence in the text of physician notes. The algorithm recognizes eight semantic classes of documentation of medication non-adherence. We evaluated the algorithm against manual ratings of 200 randomly selected notes of hypertensive patients. The algorithm detected 89% of the notes with documented medication non-adherence with specificity of 84.7% and positive predictive value of 80.2%. In a larger dataset of 1,000 documents, notes that documented medication non-adherence were more likely to report significantly elevated systolic (15.3% vs. 9.0%; p = 0.002) and diastolic (4.1% vs. 1.9%; p = 0.03) blood pressure. This novel clinically validated tool expands the range of information on medication non-adherence available to researchers.
