Evidence map›Paper›PMID 40107304›Full record

ArticleApplied clinical informatics2025

Relationship between Additional Required Nursing Documentation and Patient Outcomes: A Scoping Review.

Rachel Y Lee, Jennifer Thate, Jennifer Withall, Po-Yin Yen, Kenrick Cato, Sarah C Rossetti

Abstract readScoping Review
In one paragraph

Article in Applied clinical informatics, 2025. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

6 authors.

Rachel Y LeeDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, United States.ORCID 0000-0002-0392-5848
Jennifer ThateDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, United States.
Jennifer WithallDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, United States.
Po-Yin YenInstitute for Informatics, Data Science & Biostatistics, Washington University School of Medicine, St. Louis, Missouri, United States.
Kenrick CatoUniversity of Pennsylvania, Philadelphia, Pennsylvania, United States.
Sarah C RossettiDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, United States.

Funding

AHRQ HHS AHRQ R01HS0284NINR NIH HHS 1R01NR016941
6 · The paper itself

Abstract

Although many aspects of nursing documentation are considered an essential part of clinical communication and care coordination, other types of nursing documentation have been implemented to meet compliance and secondary uses. Adding required documentation without carefully assessing its association with patient outcomes adds excessive documentation burden on nurses. There is a gap in the evidence of the association between additional required nursing documentation and improvements in patient outcomes.This study aimed to synthesize and describe the state of the evidence on the relationship between adding required electronic nursing documentation and improved patient outcomes in inpatient hospital settings.Databases were searched using relevant terms for original studies examining the effects of additional required nursing documentation. Two authors screened titles, abstracts, and full texts for eligibility criteria. PubMed, CINAHL (EBSCO), Web of Science, and Embase were searched for data from January 2011 to May 2023.A total of 47 studies were included. Of the studies reviewed, 57.4% (

Indexed as

DocumentationHumans

Identifiers

PMID40107304
PMCPMC12240665

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.