Evidence map›Paper›PMID 37736130›Full record

ArticleJournal of patient experience2023

Humanizing the Intensive Care Unit: Perspectives of Patients and Families on the Get to Know Me Board.

Sumera R Ahmad, Lori Rhudy, Lindsay A Fogelson, Allison M LeMahieu, Amelia K Barwise, Ognjen Gajic, Lioudmila V Karnatovskaia

Abstract read
In one paragraph

Article in Journal of patient experience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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.

Sumera R AhmadDivision of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, USA.ORCID https://orcid.org/0000-0002-0225-3330
Lori RhudyDepartment of Graduate Nursing, Winona State University, Rochester, MN, USA.
Lindsay A FogelsonAnesthesia and Critical Care Research Unit, Mayo Clinic, Rochester, MN, USA.
Allison M LeMahieuDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Amelia K BarwiseDepartment of Bioethics Research Program, Mayo Clinic, Rochester, MN, USA.
Ognjen GajicDivision of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, USA.
Lioudmila V KarnatovskaiaDivision of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this qualitative study, we explored perspectives of patients in the intensive care unit (ICU) and their families on the Get to Know Me board (GTKMB). Of the 46 patients approached, 38 consented to participate. Of the 66 family members approached, 60 consented to participate. Most patients (26, 89%) and family members (52, 99%) expressed that GTKMB was important in recognizing patient's humanity. Most patients (20, 68%) and families (39, 74%) said that it helped to build a better relationship with the provider team. 60% of patients and families commented that the GTKMB was used as a platform by providers to interact with them. Up to 45 (85%) of the family members supported specific contents of the GTKMB. In structured interviews (11 patients, 7 family members), participants additionally commented on ways providers used the GTKMB to communicate, support patient's personhood, and on caveats in interacting with GTKMB. Critically ill patients and families found the GTKMB helpful in preserving personhood of patient, fostering communication, and building relationships with clinicians.

Indexed as

anonymityfamily centered careget to know me boardHumanizationintensive care unitpatient centered care

Identifiers

PMID37736130
PMCPMC10510354

What OpenQuestion holds

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LicenceCC BY-NC
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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.