Evidence map›Paper›PMID 41033350›Full record

ArticleApplied clinical informatics2025

Choosing between Patient Care Needs and Accurate Data Capture: Exploring Nurses' Experiences of Excessive Documentation Burden.

Jennifer Thate, Rachel Y Lee, Rosemary Mugoya, Courtney J Diamond, Temiloluwa Daramola, Po-Yin Yen, Sarah C Rossetti

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. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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.

Jennifer ThateDepartment of Nursing, Siena College, Albany, New York, United States.
Rachel Y LeeDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, United States.
Rosemary MugoyaGoldfarb School of Nursing, Barns-Jewish College, BJC HealthCare, St. Louis, Missouri, United States.
Courtney J DiamondDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, United States.
Temiloluwa DaramolaDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, United States.
Po-Yin YenGoldfarb School of Nursing, Barns-Jewish College, BJC HealthCare, St. Louis, Missouri, United States.
Sarah C RossettiDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, United States.

Funding

Training in Biomedical Informatics at Columbia UniversityT15LM007079 · NLM · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI NOEMIE ELHADAD, GEORGE M HRIPCSAK · 1992 to 2026
$28.9M
AHRQ HHS R01 HS028454NLM NIH HHS T15 LM007079
6 · The paper itself

Abstract

This study aimed to explore: (1) how nurses in the acute care setting describe their experience(s) of excessive documentation burden (ExDocBurden); (2) what factors contribute to ExDocBurden for nurses in the inpatient setting; and (3) nurses' perspectives on solutions to mitigate ExDocBurden that support documentation practices that they deem essential to providing safe, high-quality care.Semistructured interviews were conducted with 18 acute care nurses. Transcribed interviews were analyzed using the constant comparative method.All sources of ExDocBurden were categorized as issues of usability which included four themes: (1) inaccurate data resulting from EHR rules or logic that force or limit responses; (2) burdensome lengthy flowsheets-scrolling, clicking, and searching for the right place to document; (3) checking the box prevents meaningful information capture; and (4) a moving target-ongoing updates and inadequate training. Strategies to reduce ExDocBurden were categorized as "current approaches" and "future innovations."Based on synthesis of categories and themes, alongside existing literature, we propose the following recommendations: (1) develop evidence-based consensus on essential EHR data elements, (2) minimize structured data entry interfaces and maximize forms of data entry that develop and reflect nurses' clinical reasoning, (4) leverage emerging technologies to capture and parse data into structured formats suitable for secondary uses.Addressing usability issues identified by nurses is critical to reducing ExDocBurden. Increasing required data entry in structured flowsheets not only contributes to ExDocBurden, but also leads to inaccurate data capture that has serious implications for AI tools that rely on the quality of previously documented data.

Indexed as

Data AccuracyDocumentationNursesPatient CareElectronic Health RecordsHumans

Identifiers

PMID41033350
PMCPMC12488241

What OpenQuestion holds

Textmetadata
LicenceTDM
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.