Evidence map›Paper›PMID 18693848›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2007

Extracting nursing practice patterns from structured labor and delivery data sets.

Eric S Hall, Sidney N Thornton

Open access · greenAbstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.2field-weighted citation impact, top 13% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Clinical use of an enterprise data warehouse.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2012
    Article
  2. Article
  3. Generating nurse profiles from computerized labor and delivery documentation.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2008
    Article
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

2 authors at 1 institution in 1 country.

Eric S HallDepartment of Biomedical Informatics, University of Utah and Intermountain Healthcare, Salt Lake City, UT, USA.
Sidney N Thornton
Intermountain Healthcare · US

Funding

UNIVERSITY OF UTAH MEDICAL INFORMATICS TRAININGT15LM007124 · NLM · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Karen Louise Eilbeck · 1997 to 2026
$22.0M
NLM NIH HHS 1T15LM07124-08NLM NIH HHS T15 LM007124
6 · The paper itself

Abstract

This study was designed to demonstrate the feasibility of a computerized care process model that provides real-time case profiling and outcome forecasting. A methodology was defined for extracting nursing practice patterns from structured point-of-care data collected using the labor and delivery information system at Intermountain Healthcare. Data collected during January 2006 were retrieved from Intermountain Healthcare's enterprise data warehouse for use in the study. The knowledge discovery in databases process provided a framework for data analysis including data selection, preprocessing, data-mining, and evaluation. Development of an interactive data-mining tool and construction of a data model for stratification of patient records into profiles supported the goals of the study. Five benefits of the practice pattern extraction capability, which extend to other clinical domains, are listed with supporting examples.

Indexed as

Practice Guidelines as TopicClinical Nursing ResearchData CollectionDelivery, ObstetricFeasibility StudiesFemaleHumansLabor, ObstetricNursing ProcessObstetrics and Gynecology Department, HospitalPattern Recognition, AutomatedPoint-of-Care SystemsPregnancy

Identifiers

PMID18693848
PMCPMC2813662
OpenAlexW1523132254

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.