Evidence map›Paper›PMID 25979153›Full record

ArticleJournal of biomedical informatics2015

Supporting information retrieval from electronic health records: A report of University of Michigan's nine-year experience in developing and using the Electronic Medical Record Search Engine (EMERSE).

David A Hanauer, Qiaozhu Mei, James Law, Ritu Khanna, Kai Zheng

Open access · hybridAbstract read
In one paragraph

Article in Journal of biomedical informatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 220 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
220citing papers in PubMed, 2 pooled it
60.9field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

220 citing papers in PubMed, 2 syntheses or guidelines pooled it, 440 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Trial
  6. Trial
  7. Trial
  8. Article
  9. Article
  10. Article
  11. Article
  12. Centralized Pain Diagnoses in Older Adults With and Without Cancer.Journal of pain & palliative care pharmacotherapy · 2026
    Article
  13. Observational
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

160 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

David A HanauerDepartment of Pediatrics, University of Michigan Medical School, Ann Arbor, MI, USA; School of Information, University of Michigan, Ann Arbor, MI, USA. Electronic address: hanauer@med.umich.edu.
Qiaozhu MeiSchool of Information, University of Michigan, Ann Arbor, MI, USA; Department of Electronic Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA.
James LawMedical Center Information Technology, University of Michigan Health System, Ann Arbor, MI, USA.
Ritu KhannaMedical Center Information Technology, University of Michigan Health System, Ann Arbor, MI, USA.
Kai ZhengSchool of Information, University of Michigan, Ann Arbor, MI, USA; School of Public Health, Department of Health Management and Policy, University of Michigan, Ann Arbor, MI, USA.
University of Michigan–Ann Arbor · USMichigan Medicine · US

Funding

XenograftP30CA046592 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI THEODORE S LAWRENCE · 1988 to 2026
$178.2M
MICHIGAN INSTITUTE FOR CLINICAL AND HEALTH RESEARCH (MICHR) (UL1): (BPCA)UL1RR024986 · NCRR · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI SHANLEY, THOMAS P. · 2007 to 2011
$51.2M
Michigan Institute for Clinical and Health Research (MCHR)UL1TR000433 · NCATS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MASHOUR, GEORGE ALEXANDER · 2012 to 2016
$49.9M
NCATS NIH HHS UL1 TR000433NCI NIH HHS CA46592NCI NIH HHS P30 CA046592NCRR NIH HHS UL1 RR024986NCRR NIH HHS UL1RR024986NLM NIH HHS HHSN276201000032CPHS HHS HHSN276201000032C)
6 · The paper itself

Abstract

objectiveThis paper describes the University of Michigan's nine-year experience in developing and using a full-text search engine designed to facilitate information retrieval (IR) from narrative documents stored in electronic health records (EHRs). The system, called the Electronic Medical Record Search Engine (EMERSE), functions similar to Google but is equipped with special functionalities for handling challenges unique to retrieving information from medical text. MATERIALS AND

methodsKey features that distinguish EMERSE from general-purpose search engines are discussed, with an emphasis on functions crucial to (1) improving medical IR performance and (2) assuring search quality and results consistency regardless of users' medical background, stage of training, or level of technical expertise.

resultsSince its initial deployment, EMERSE has been enthusiastically embraced by clinicians, administrators, and clinical and translational researchers. To date, the system has been used in supporting more than 750 research projects yielding 80 peer-reviewed publications. In several evaluation studies, EMERSE demonstrated very high levels of sensitivity and specificity in addition to greatly improved chart review efficiency. DISCUSSION: Increased availability of electronic data in healthcare does not automatically warrant increased availability of information. The success of EMERSE at our institution illustrates that free-text EHR search engines can be a valuable tool to help practitioners and researchers retrieve information from EHRs more effectively and efficiently, enabling critical tasks such as patient case synthesis and research data abstraction.

conclusionEMERSE, available free of charge for academic use, represents a state-of-the-art medical IR tool with proven effectiveness and user acceptance.

Indexed as

Natural Language ProcessingSearch EngineSoftwareData MiningElectronic Health RecordsMeaningful UseMichiganSoftware ValidationElectronic health records (E05.318.308.940.968.625.500)Information storage and retrieval (L01.470)Search engine (L01.470.875)

Identifiers

PMID25979153
PMCPMC4527540
OpenAlexW1930458234

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.