Evidence map›Paper›PMID 19535002›Full record

ArticleJournal of biomedical informatics2009

Patient-level analysis of outcomes using structured labor and delivery data.

Eric S Hall, Mollie R Poynton, Scott P Narus, Spencer S Jones, R Scott Evans, Michael W Varner, Sidney N Thornton

Abstract read
In one paragraph

Article in Journal of biomedical informatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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

7 authors.

Eric S HallDepartment of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA. eric.hall@cchmc.org
Mollie R Poynton
Scott P Narus
Spencer S Jones
R Scott Evans
Michael W Varner
Sidney N Thornton

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

This paper presents methods for identifying and analyzing associations among nursing care processes, patient attributes, and patient outcomes using unit-level and patient-level representations of care derived from computerized nurse documentation. The retrospective, descriptive analysis included documented nursing events for 900 Labor and Delivery patients at three hospitals over the 2-month period of January and February 2006. Two models were used to produce quantified measurements of nursing care received by each patient. The first model considered only the hourly census of nurses and patients. The second model considered the size of nurses' patient loads as represented by computerized nurse-entered documentation. Significant relationships were identified between durations of labor and nursing care scores generated by the second model. In addition to the clinical associations identified, the study demonstrated an approach with global application for representing the amount of nursing care received at the individual patient level in analyses of patient outcomes.

Indexed as

Delivery, ObstetricLabor, ObstetricPregnancy OutcomeFemaleHospitalsHumansLinear ModelsModels, NursingNursing CareObstetric NursingPatientsPregnancyRetrospective Studies

Identifiers

PMID19535002
PMCPMC2706298

What OpenQuestion holds

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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.