Evidence map›Paper›PMID 33936413›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2020

We're Lost, But We are Making Good Time: Navigating Complex Pathways in a Patient-Order Management Task.

Benjamin J Duncan, Alexandra N Kassis, David R Kaufman, Adela Grando, Karl A Poterack, Rick A Helmers, Timothy K Miksch, Lu Zheng, Bradley N Doebbeling

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

9 authors.

Benjamin J DuncanCollege of Health Solutions, Arizona State University, AZ, US.
Alexandra N KassisCollege of Health Solutions, Arizona State University, AZ, US.
David R KaufmanSenior author.
Adela GrandoCollege of Health Solutions, Arizona State University, AZ, US.
Karl A PoterackKern Center Informatics and Knowledge Management, Mayo Clinic, Rochester, MN, US.
Rick A HelmersKern Center Informatics and Knowledge Management, Mayo Clinic, Rochester, MN, US.
Timothy K MikschKern Center Informatics and Knowledge Management, Mayo Clinic, Rochester, MN, US.
Lu ZhengCollege of Health Solutions, Arizona State University, AZ, US.
Bradley N DoebbelingCollege of Health Solutions, Arizona State University, AZ, US.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patient order management (POM) is a mission-critical task for perioperative workflow. Interface complexity within different EHR systems result in poor usability, increasing documentation burden. POM interfaces were compared across two systems prior to (Cerner SurgiNet) and subsequent to an EHR conversion (Epic). Here we employ a navigational complexity framework useful for examining differences in EHR interface systems. The methodological approach includes 1) expert-based methods-specifically, functional analysis, keystroke level model (KLM) and cognitive walkthrough, and 2) quantitative analysis of observed interactive user behaviors. We found differences in relation to navigational complexity with the SurgiNet interface displaying a higher number of unused POM functions, with 12 in total whereas Epic displayed 7 total functions. As reflected in all measures, Epic facilitated a more streamlined task-focused user experience. The approach enabled us to scrutinize the impact of different EHR interfaces on task performance and usability barriers subsequent to system implementation.

Indexed as

Electronic Health RecordsPerioperative PeriodTask Performance and AnalysisUser-Computer InterfaceWorkflowCognitionDocumentationHumans

Identifiers

PMID33936413
PMCPMC8075447

What OpenQuestion holds

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Registered trials

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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.