Evidence map›Paper›PMID 40216402›Full record

ArticleApplied clinical informatics2025

Improving Nurse Documentation Time via an Electronic Health Record Documentation Efficiency Tool.

John Will, Deborah Jacques, Denise Dauterman, Rachelle Torres, Glenn Doty, Kerry O'Brien, Lisa Groom

Abstract read
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. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

John WillMCIT Department of Health Informatics, New York University Langone Health, New York, New York, United States.
Deborah JacquesMCIT Department of Health Informatics, New York University Langone Health, New York, New York, United States.
Denise DautermanMCIT Department of Health Informatics, New York University Langone Health, New York, New York, United States.
Rachelle TorresMCIT Department of Health Informatics, New York University Langone Health, New York, New York, United States.
Glenn DotyMCIT Department of Health Informatics, New York University Langone Health, New York, New York, United States.
Kerry O'BrienMCIT Department of Health Informatics, New York University Langone Health, New York, New York, United States.
Lisa GroomMCIT Department of Health Informatics, New York University Langone Health, New York, New York, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nursing documentation burden is a growing point of concern in the United States health care system. Documentation in the electronic health record (EHR) is a contributor to perceptions of burden. Efficiency tools like flowsheet macros are one development intended to ease the burden of documentation.This study aimed to evaluate whether flowsheet macros, a documentation efficiency tool in the EHR that consolidates documentation into a single click, reduces the time spent on documentation activities and the EHR overall.Nurses in the health system were encouraged to create and utilize flowsheet macros for their documentation. Flowsheet documentation and time in system data for nurses' first and last shifts in the evaluation period were extracted from the EHR. Linear regression with control variables was utilized to understand if the utilization of flowsheet macros for documentation reduced the time spent in flowsheets or the EHR.The results of linear regression showed a significant, negative relationship between flowsheet macros use and time in flowsheets (adjusted odds ratio [AOR] = -0.291, 95% confidence interval [CI] = -0.342 to -0.240,

Indexed as

DocumentationEfficiencyElectronic Health RecordsNursesHumansTime Factors

Identifiers

PMID40216402
PMCPMC12373461

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.