Evidence map›Paper›PMID 17947628›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA

An electronic health record based on structured narrative.

Stephen B Johnson, Suzanne Bakken, Daniel Dine, Sookyung Hyun, Eneida Mendonça, Frances Morrison, Tiffani Bright, Tielman Van Vleck, Jesse Wrenn, Peter Stetson

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed, 4 pooled it
–field-weighted citation impact
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

62 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  16. Clinical Documentation as End-User Programming.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2020
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2 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

10 authors.

Stephen B JohnsonDepartment of Biomedical Informatics, Columbia University, New York, NY, USA. sbj2@columbia.edu
Suzanne Bakken
Daniel Dine
Sookyung Hyun
Eneida Mendonça
Frances Morrison
Tiffani Bright
Tielman Van Vleck
Jesse Wrenn
Peter Stetson

Funding

Using Narrative Data to Enrich the Online Medical RecordR01LM007268 · NLM · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI JOHNSON, STEPHEN B. · 2002 to 2004
$1.3M
Automated Detection of Medical ErrorsK22LM008805 · NLM · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI STETSON, PETER D · 2005 to 2007
$405k
NLM NIH HHS 1K22 LM008805NLM NIH HHS 5R01 LM007268NLM NIH HHS K22 LM008805NLM NIH HHS R01 LM007268
6 · The paper itself

Abstract

objectiveTo develop an electronic health record that facilitates rapid capture of detailed narrative observations from clinicians, with partial structuring of narrative information for integration and reuse.

designWe propose a design in which unstructured text and coded data are fused into a single model called structured narrative. Each major clinical event (e.g., encounter or procedure) is represented as a document that is marked up to identify gross structure (sections, fields, paragraphs, lists) as well as fine structure within sentences (concepts, modifiers, relationships). Marked up items are associated with standardized codes that enable linkage to other events, as well as efficient reuse of information, which can speed up data entry by clinicians. Natural language processing is used to identify fine structure, which can reduce the need for form-based entry. VALIDATION: The model is validated through an example of use by a clinician, with discussion of relevant aspects of the user interface, data structures and processing rules. DISCUSSION: The proposed model represents all patient information as documents with standardized gross structure (templates). Clinicians enter their data as free text, which is coded by natural language processing in real time making it immediately usable for other computation, such as alerts or critiques. In addition, the narrative data annotates and augments structured data with temporal relations, severity and degree modifiers, causal connections, clinical explanations and rationale.

conclusionStructured narrative has potential to facilitate capture of data directly from clinicians by allowing freedom of expression, giving immediate feedback, supporting reuse of clinical information and structuring data for subsequent processing, such as quality assurance and clinical research.

Indexed as

Medical Records Systems, ComputerizedNatural Language ProcessingUser-Computer InterfaceDocumentationHumansInformation Storage and RetrievalMedical History TakingSoftwareSystems IntegrationVocabulary, Controlled

Identifiers

PMID17947628
PMCPMC2274868

What OpenQuestion holds

Textmetadata
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.