Evidence map›Paper›PMID 35774921›Full record

ArticleJAMIA open2022

Medical data formatting to improve physician interpretation speed in the Military Healthcare System.

Jacob E Peterson

Open access · goldAbstract read
In one paragraph

Article in JAMIA open, 2022. 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, top 89% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

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

1 author at 1 institution in 1 country.

Jacob E PetersonMedical Corps, United States Navy, Portsmouth, Virginia, USA.ORCID https://orcid.org/0000-0002-1690-6718
Naval Medical Center Portsmouth · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The purpose of this project was to improve ease and speed of physician comprehension when interpreting daily laboratory data for patients admitted within the Military Healthcare System (MHS). Materials and Methods: A JavaScript program was created to convert the laboratory data obtained via the outpatient electronic medical record (EMR) into a "fishbone diagram" format that is familiar to most physicians. Using a balanced crossover design, 35 internal medicine trainees and staff at Naval Medical Center Portsmouth were asked to complete timed comprehension tests for laboratory data sets formatted in the outpatient EMR's format and in fishbone diagram format. The number of responses per second and error rate per response were measured for each format. Participants were asked to rate relative ease of use for each format and indicate which format they preferred. Results: Comprehension speed increased 37% (6.28 seconds per interpretation) with the fishbone diagram format with no observed increase in errors. Using a Likert scale of 1-5 (1 being hard, 5 easy), participants indicated the new format was easier to use (4.14 for fishbone vs 2.14 for table) with 89% expressing preference for the new format. Discussion: The publically available web application that converts tabular lab data to fishbone diagram format is currently used 10 000-12 000 times per month across the MHS, delivering significant benefit to the enterprise in terms of time saved and improved physician experience. Conclusions: This study supports the use of fishbone diagram formatting for laboratory data for inpatients within the MHS.

Indexed as

comprehensiondata displaydata visualizationuser-centered designuser-computer interface

Identifiers

PMID35774921
PMCPMC9239313
OpenAlexW4283706166

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.