HARVEST: Longitudinal Patient Record Summarization
As more and more raw data observations are recorded about patients in their
record, providers are face with an overwhelming amount of complex data points,
with little time for making sense of them all. This phenomenon of information
overload has been observed in several care settings, from outpatient clinics
and primary care, to hospital admissions, and the emergency room. With the
advant of health information exchange, reviewing of patient data will only
become more complex and time consuming for clinicians. One of the promises of
the electronic health record is to support clinicians at the point of care.
Clinical information systems, unfortunately, seldom provide effective cognitive
support - i.e., they do not present information in an optimal format to
clinicians when and where it is needed.
HARVEST is an interactive, problem-oriented patient record summarization
system. The summarizer differs from previous work in three critical ways: (i)
it extracts content from the patient notes, where key clinical information
resides; (ii) it aggregates and presents information from multiple care
settings, including inpatient, ambulatory, and emergency department encounters;
and (iii) it is integrated into the clinical information review system iNYP at
New York Presbyterian Hospital, and is available for all patients in our
institution, not just a curated dataset or for specific patient cohorts.
Patient record summarization papers
People - HARVEST
- Noémie Elhadad
- Sharon Lipsky Gorman, MS
- Danish Ghazali
- Rebekah Kim
- Benjamin Bloxham, MD (alumn)
- Jamie Hirsch, MD, MA (alumn)
- Connie Liu, BS (alumn)
- Cristel Oropesa (alumn)
- Daniel Reichert, MA (alumn)
- Rimma Pivovarov, PhD (alumn)
- Jessica Tanenbaum, MD (alumn)
- Rebecca Tisdale, MD (alumn)
People - NewYork-Presbyterian Hospital
- Marc Sturm
- David Vawdrey
- Karthik Natarajan
- Rimma Pivovarov, Yael Coppleson, Sharon Lipsky Gorman, David Vawdrey,
Can Patient Record Summarization Support Quality Metric Abstraction?
2016. AMIA Fall Symposium. Chicago, IL. [pdf]
- Rimma Pivovarov, Noémie Elhadad.
Automated Methods for the Summarization of Electronic Health Records.
2015. Journal of the American Medical Informatics Association (JAMIA).
- Jamie Hirsch, Jessica Tanenbaum, Sharon Lipsky Gorman, Connie Liu, Eric Schmitz, Dritan Hashorva, Artem Ervits, David Vawdrey, Marc Sturm, Noémie Elhadad.
HARVEST, a Longitudinal Patient Record Summarizer.
2014. Journal of the American Medical Informatics Association (JAMIA). [html]
- Noémie Elhadad, Sharon Lipsky Gorman, Jamie Hirsch, Connie Liu, David
Vawdrey, Marc Sturm.
HARVEST, a Holistic Patient Record Summarizer at the Point of Care.
2014. AMIA Fall Symposium. [pdf]
- Raphael Cohen, Iddo Aviram, Michael Elhadad, and Noémie Elhadad.
Redundancy-Aware Latent Dirichlet Allocation for Patient Record Notes.
2014. PloS ONE 9(2): e87555. [html]
- Preethi Raghavan, Eric Fosler-Lussier, Noémie Elhadad, and Albert Lai.
Cross-narrative Temporal Ordering of Medical Events.
2014. ACL. pp. 998-1008. Baltimore, MD. [pdf]
- Raphael Cohen, Michael Elhadad, and Noémie Elhadad.
Redundancy in Electronic Health Record Corpora: Analysis, Impact on Text Mining Performance, and Mitigation Strategies.
2013. BMC Bioinformatics. 14:10. [pdf]
- Rimma Pivovarov and Noémie Elhadad.
A Hybrid Knowledge-Based and Data-Driven Approach to Identifying Semantically Similar Concepts.
2012. Journal of Biomedical Informatics. 45(3):471-81. [pdf]
- Daniel Reichert, David Kaufman, Benjamin Bloxham, Herbert Chase, and Noémie Elhadad.
Cognitive Analysis of the Summarization of Longitudinal Patient Records.
2010. AMIA Annual Symposium, pp.667-671. Washington, DC. [pdf]
- Tielman Van Vleck and Noémie Elhadad.
Corpus-based Problem Selection for EHR Note Summarization.
2010. AMIA Annual Symposium, pp. 817-821. Washington, DC. [pdf]
- Tielman Van Vleck, Adam Wilcox, Peter Stetson, Stephen Johnson, and
Content and Structure of Clinical Problem Lists:
A Corpus Analysis.
2008. AMIA Annual Symposium, pp. 753-757. Washington,
- Noémie Elhadad, Kathleen McKeown, David Kaufman, and Desmond
Facilitating Physicians' Access to Information via Tailored Text
2005. AMIA Annual Symposium, pp. 226-230. Washington, DC.
Work for HARVEST is funded by the National Library of Medicine (R01 LM010027)
and the National Science Foundation (#1344668).
Last Updated: 7/2016
noemie.elhadad @ columbia.edu