Evidence map›Paper›PMID 26039293›Full record

ArticleRevista latino-americana de enfermagem

Assessment of nursing care using indicators generated by software.

Ana Paula Souza Lima, Tânia Couto Machado Chianca, Meire Chucre Tannure

Erratum issuedOpen access · diamondAbstract read
In one paragraph

Article in Revista latino-americana de enfermagem. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
9.2field-weighted citation impact, top 3% 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

1 citing paper in PubMed, 10 citations in OpenAlex.

  1. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 1 country.

Ana Paula Souza LimaHospital da Polícia Militar, Belo Horizonte, MG, Brazil.
Tânia Couto Machado ChiancaEscola de Enfermagem, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil.
Meire Chucre TannureEscola de Enfermagem, Pontifícia Universidade Católica de Minas Gerais, Belo Horizonte, MG, Brazil.
Hospital Central da Polícia Militar · BRPontifícia Universidade Católica de Minas Gerais · BRUniversidade Federal de Minas Gerais · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveto analyze the efficacy of the Nursing Process in an Intensive Care Unit using indicators generated by software.

methodcross-sectional study using data collected for four months. RNs and students daily registered patients, took history (at admission), performed physical assessments, and established nursing diagnoses, nursing plans/prescriptions, and assessed care delivered to 17 patients using software. Indicators concerning the incidence and prevalence of nursing diagnoses, rate of effectiveness, risk diagnoses, and rate of effective prevention of complications were computed.

resultsthe Risk for imbalanced body temperature was the most frequent diagnosis (23.53%), while the least frequent was Risk for constipation (0%). The Risk for Impaired skin integrity was prevalent in 100% of the patients, while Risk for acute confusion was the least prevalent (11.76%). Risk for constipation and Risk for impaired skin integrity obtained a rate of risk diagnostic effectiveness of 100%. The rate of effective prevention of acute confusion and falls was 100%.

conclusionthe efficacy of the Nursing Process using indicators was analyzed because these indicators reveal how nurses have identified patients' risks and conditions, and planned care in a systematized manner.

Indexed as

Quality Indicators, Health CareSoftwareAdultAgedAged, 80 and overCross-Sectional StudiesFemaleHumansIntensive Care UnitsMaleMiddle AgedNursing DiagnosisNursing Process

Identifiers

PMID26039293
PMCPMC4458996
OpenAlexW1590551919

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.