title: Mining Clinicians' Electronic Documentation to Identify Heart Failure Patients with Ineffective Self-Management: A Pilot Text-Mining Study.
abstract: Effective self-management can decrease up to 50% of heart failure hospitalizations. Unfortunately, self-management by patients with heart failure remains poor. This pilot study aimed to explore the use of text-mining to identify heart failure patients with ineffective self-management. We first built a comprehensive self-management vocabulary based on the literature and clinical notes review. We then randomly selected 545 heart failure patients treated within Partners Healthcare hospitals (Boston, MA, USA) and conducted a regular expression search with the compiled vocabulary within 43,107 interdisciplinary clinical notes of these patients. We found that 38.2% (n = 208) patients had documentation of ineffective heart failure self-management in the domains of poor diet adherence (28.4%), missed medical encounters (26.4%) poor medication adherence (20.2%) and non-specified self-management issues (e.g., "compliance issues", 34.6%). We showed the feasibility of using text-mining to identify patients with ineffective self-management. More natural language processing algorithms are needed to help busy clinicians identify these patients.
authors.affiliation: Harvard Medical School, Boston, MA, USA.
authors.forename: Maxim
authors.initials: M
authors.lastname: Topaz
authors.affiliation: School of Nursing, University of Texas, Austin, TX, USA.
authors.forename: Kavita
authors.initials: K
authors.lastname: Radhakrishnan
authors.affiliation: Brigham Women's Health Hospital, Boston, MA, USA.
authors.forename: Victor
authors.initials: V
authors.lastname: Lei
authors.affiliation: Harvard Medical School, Boston, MA, USA.
authors.forename: Li
authors.initials: L
authors.lastname: Zhou
mesh_terms: D001900:Boston / Q000453:epidemiology; D057225:Data Mining; D057286:Electronic Health Records / Q000145:classification / Q000706:statistics & numerical data*; D006333:Heart Failure / Q000175:diagnosis* / Q000453:epidemiology / Q000628:therapy*; D006801:Humans; D009323:Natural Language Processing; D017063:Outcome Assessment, Health Care / Q000379:methods*; D010349:Patient Compliance / Q000706:statistics & numerical data*; D010865:Pilot Projects; D015995:Prevalence; D015203:Reproducibility of Results; D018570:Risk Assessment; D012648:Self Care; D012680:Sensitivity and Specificity; D009626:Terminology as Topic; D017211:Treatment Failure; D016896:Treatment Outcome; D018875:Vocabulary, Controlled