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.
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.
The target audience for this activity is professionals and students interested in biomedical and health informatics.
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
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.
No commercial support was received for this activity.
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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
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