Risk prediction for chronic kidney disease progression using heterogeneous electronic health record data andtime series analysis

October 15, 2015
Free for all
Adler Perotte, MD

Adler Perotte, MD is an Associate Research Scientist in the Department of Biomedical Informatics and the Assistant Director for Technology at the Center for Advanced Technology for Columbia University. Dr. Perotte’s primary research area is the development and application of statistical machine learning methods, including probabilistic graphical models for biomedical informatics.

At the Center for Advanced Technology Dr. Perotte is responsible for new entrepreneurship initiatives and the evaluation of new projects co-sponsored between Columbia University and industry partners. In this capacity, Dr. Perotte is spearheading the Health Tech Assembly, a group for students and faculty from the medical, engineering, and business schools at Columbia designed to foster the conception and translation of solutions to biomedical problems through entrepreneurship.

The PubMed citation for the paper under discussion is:

Perotte A, Ranganath R, Hirsch JS, Blei D, Elhadad N.

Risk prediction for chronic kidney disease progression using heterogeneous electronic health record data andtime series analysis.

J Am Med Inform Assoc 2015;22:872–880. doi:10.1093/jamia/ocv024 First published online: 20 April 2015

Statement of Purpose

As adoption of electronic health records (EHRs) continues to increase, there is an opportunity to incorporate clinical documentation as well as laboratory values and demographics into risk prediction modeling. The authors developed a risk prediction model for chronic kidney disease (CKD) progression from stage III to stage IV that includes longitudinal data and features drawn from clinical documentation. In this webinar we consider the potential of enhancing the EHR beyond its current use as a health data repository to include risk prediction models for conditions of interest.

Target Audience

The target audience for this activity is professionals and students interested in biomedical and health informatics.

Learning Objective

After participating in this live webinar, the learner should be better able to:

  • Consider application of several analytical techniques to EHR data to create a risk prediction model


Adler Perotte, MD
Associate Research Scientist
Columbia University Department of Biomedical Informatics
Assistant Director for Technology
Center for Advanced Technology for Columbia University
New York, NY

Accreditation Statement

The American Medical Informatics Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.

Credit Designation Statement

The American Medical Informatics Association designates this live activity for a maximum of 1 AMA PRA Category 1 Credit(s)™.  Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Criteria for Successful Completion

Completion of this activity is demonstrated by:

  • Viewing the live webinar
  • Optional submission of questions via webinar feature; optional to follow @AMIAinformatics  and tweet via #JAMIAJC
  • Completion of the evaluation survey at https://www.surveymonkey.com/r/JAMIAjc-1 and
  • Verification of attendance through the participant’s electronic report through the individual login at www.amia.org.

The physician participant will be able to generate a CME certificate through the AMIA automated system.
For a certificate of completion, contact Pesha@amia.org.

Commercial Support

No commercial support was received for this activity.

Disclosure Policy

As a provider accredited by the ACCME, AMIA requires that everyone who is in a position to control the content of an educational activity disclose all relevant financial relationships with any commercial interest for 12 months prior to the educational activity.

The ACCME considers relationships of the person involved in the CME activity to include financial relationships of a spouse or partner.
Faculty and planners who refuse to disclose relevant financial relationships will be disqualified from participating in the CME activity. For an individual with no relevant financial relationship(s), the participants must be informed that no conflicts of interest or financial relationship(s) exist.

AMIA uses a number of methods to resolve potential conflicts of interest, including: limiting content of the presentation to that which has been reviewed by one or more peer reviewers; ensuring that all scientific research referred to conforms to generally accepted standards of experimental design, data collection, and analysis; undertaking review of the educational activity by a content reviewer to evaluate for potential bias, balance in presentation, evidence-based content or other indicators of integrity, and absence of bias; monitoring the educational activity to evaluate for commercial bias in the presentation; and/or reviewing participant feedback to evaluate for commercial bias in the activity .

Disclosures for This Activity

These faculty, planners, and staff who are in a position to control the content of this activity disclose that they and their life partners have no relevant financial relationships with commercial interests:
Faculty: Adler Perotte
JAMIA Journal Club planners: Mary Regina Boland, Matthew Breitenstein
AMIA staff: Susanne Arnold, Pesha Rubinstein

JAMIA Journal Club planner Michael Chiang discloses the following:

  • Received Grant/Research Support from the National Institutes of Health
  • Is an unpaid member of the Scientific Advisory Board of Clarity Medical Systems

Instructions for Claiming CME/CE Credit

CME site (MyAMIA) works best with IE 8 or above version, Chrome, Safari, and Firefox.

  • Login to your AMIA account on the AMIA.org website
  • Go to “My Profile”
  • Click “Invoices & Transactions” tab
  • Scroll down to Events section and click ‘Credits’ next to “Webinar: JAMIA Journal Club - October 2015”
  • Physicians: for “Select Credit Type” click “Physician” in the drop-down menu.
  • For “Select Physician Credit Type” click “Physician” (not MOC-II)
  • Click Submit
  • Click on the AMIA Activities tab in your account; click “download” in the row for “Webinar: JAMIA Journal Club - October 2015”; you may print out your certificate

Other attendees: if you require a certificate of participation, please contact pesha@amia.org

Contact Info

For questions about content or CE, email pesha@amia.org