title: Patient Stratification Using Electronic Health Records from a Chronic Disease Management Program.
abstract: OBJECTIVE
  The goal of this study is to devise a machine learning framework to assist care coordination programs in prognostic stratification to design and deliver personalized care plans and to allocate financial and medical resources effectively.
  
  
  METHODS
  This study is based on a de-identified cohort of 2,521 hypertension patients from a chronic care coordination program at the Vanderbilt University Medical Center. Patients were modeled as vectors of features derived from electronic health records (EHRs) over a six-year period. We applied a stepwise regression to identify risk factors associated with a decrease in mean arterial pressure of at least 2 mmHg after program enrollment. The resulting features were subsequently validated via a logistic regression classifier. Finally, risk factors were applied to group the patients through model-based clustering.
  
  
  RESULTS
  We identified a set of predictive features that consisted of a mix of demographic, medication, and diagnostic concepts. Logistic regression over these features yielded an area under the ROC curve (AUC) of 0.71 (95% CI: [0.67, 0.76]). Based on these features, four clinically meaningful groups are identified through clustering - two of which represented patients with more severe disease profiles, while the remaining represented patients with mild disease profiles.
  
  
  CONCLUSIONS
  Patients with hypertension can exhibit significant variation in their blood pressure control status and responsiveness to therapy. Yet this work shows that a clustering analysis can generate more homogeneous patient groups, which may aid clinicians in designing and implementing customized care programs.
  
  
  CONCLUSIONS
  The study shows that predictive modeling and clustering using EHR data can be beneficial for providing a systematic, generalized approach for care providers to tailor their management approach based upon patient-level factors.
authors.forename: Robert
authors.initials: R
authors.lastname: Chen
authors.forename: Jimeng
authors.initials: J
authors.lastname: Sun
authors.forename: Robert S
authors.initials: RS
authors.lastname: Dittus
authors.forename: Daniel
authors.initials: D
authors.lastname: Fabbri
authors.forename: Jacqueline
authors.initials: J
authors.lastname: Kirby
authors.forename: Cheryl L
authors.initials: CL
authors.lastname: Laffer
authors.forename: Candace D
authors.initials: CD
authors.lastname: McNaughton
authors.forename: Bradley
authors.initials: B
authors.lastname: Malin