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

Maryam Panahiazar, Vahid Taslimitehrani, Naveen Luke Pereira, Jyotishman Pathak

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

12 Scopus citations

Abstract

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 <sup>1</sup> 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 publicationStudies in Health Technology and Informatics
PublisherIOS Press
Pages369-373
Number of pages5
Volume210
ISBN (Print)9781614995111
DOIs
StatePublished - 2015
Event26th Medical Informatics in Europe Conference, MIE 2015 - Madrid, Spain
Duration: May 27 2015May 29 2015

Other

Other26th Medical Informatics in Europe Conference, MIE 2015
CountrySpain
CityMadrid
Period5/27/155/29/15

Keywords

  • electronic health records
  • heart failure
  • patient similarity

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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  • Cite this

    Panahiazar, M., Taslimitehrani, V., Pereira, N. L., & Pathak, J. (2015). Using EHRs for Heart Failure Therapy Recommendation Using Multidimensional Patient Similarity Analytics. In Studies in Health Technology and Informatics (Vol. 210, pp. 369-373). IOS Press. https://doi.org/10.3233/978-1-61499-512-8-369