Using EHRs for Heart Failure Therapy Recommendation Using Multidimensional Patient Similarity Analytics

Maryam Panahiazar, Vahid Taslimitehrani, Naveen L. Pereira, Jyotishman Pathak

Research output: Chapter in Book/Report/Conference proceedingConference contribution

18 Scopus citations


Electronic Health Records (EHRs) contain a wealth of information about an individual patient's diagnosis, treatment and health outcomes. This information can be leveraged effectively to identify patients who are similar to each for disease diagnosis and prognosis. In recent years, several machine learning methods 1 have been proposed to assessing patient similarity, although the techniques have primarily focused on the use of patient diagnoses data from EHRs for the learning task. In this study, we develop a multidimensional patient similarity assessment technique that leverages multiple types of information from the EHR and predicts a medication plan for each new patient based on prior knowledge and data from similar patients. In our algorithm, patients have been clustered into different groups using a hierarchical clustering approach and subsequently have been assigned a medication plan based on the similarity index to the overall patient population. We evaluated the performance of our approach on a cohort of heart failure patients (N=1386) identified from EHR data at Mayo Clinic and achieved an AUC of 0.74. Our results suggest that it is feasible to harness population-based information from EHRs for an individual patient-specific assessment.

Original languageEnglish (US)
Title of host publicationDigital Healthcare Empowering Europeans - Proceedings of MIE 2015
EditorsRonald Cornet, Lacramioara Stoicu-Tivadar, Ronald Cornet, Carlos Luis Parra Calderon, Stig Kjaer Andersen, Alexander Horbst, Mira Hercigonja-Szekeres
PublisherIOS Press
Number of pages5
ISBN (Electronic)9781614995111
StatePublished - 2015
Event26th Medical Informatics in Europe Conference, MIE 2015 - Madrid, Spain
Duration: May 27 2015May 29 2015

Publication series

NameStudies in Health Technology and Informatics
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365


Other26th Medical Informatics in Europe Conference, MIE 2015


  • electronic health records
  • heart failure
  • patient similarity

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management


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