Evidence map›Paper›PMID 18495549›Full record

ArticleJournal of biomedical informatics2008

Modeling the distribution of Nursing Effort using structured Labor and Delivery documentation.

Eric S Hall, Mollie R Poynton, Scott P Narus, Sidney N Thornton

Abstract read
In one paragraph

Article in Journal of biomedical informatics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.4field-weighted citation impact, top 10% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Consequences of nursing procedures measurement on job satisfaction.Iranian journal of nursing and midwifery research · 2013
    Article
  3. Article
  4. 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

4 authors at 2 institutions in 1 country.

Eric S HallDepartment of Biomedical Informatics, University of Utah, School of Medicine, 26 South 2000 East, Suite 5700 HSEB, Salt Lake City, UT 841112 5750, USA. eric.hall@hsc.utah.edu
Mollie R Poynton
Scott P Narus
Sidney N Thornton
Intermountain Healthcare · USUniversity of Utah · 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 1T15LM07124NLM NIH HHS T15 LM007124
6 · The paper itself

Abstract

Our study objectives included the development and evaluation of models for representing the distribution of shared unit-wide nursing care resources among individual Labor and Delivery patients using quantified measurements of nursing care, referred to as Nursing Effort. The models were intended to enable discrimination between the amounts of care delivered to patient subsets defined by attributes such as patient acuity. For each of five proposed models, scores were generated using an analysis set of 686,402 computerized nurse-documented events associated with 1093 patients at three hospitals during January and February 2006. Significant differences were detected in Nursing Effort scores according to patient acuity, care facility, and in scores generated during shift change versus non-shift change hours. The development of nursing care quantification strategies proposed in this study supports outcomes analysis by establishing a foundation for measuring the effect of patient-level nursing care on individual patient outcomes.

Indexed as

Labor, ObstetricModels, NursingFemaleHumansPregnancyRetrospective Studies

Identifiers

PMID18495549
PMCPMC2649767
OpenAlexW1991792148

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.