Evidence map›Paper›PMID 35068208›Full record

ArticleHealth informatics journal

Display and perception of risk: Analysis of decision support system display and its impact on perceived clinical risk of sepsis-induced health deterioration.

Muge Capan, Laura C Schubel, Ishika Pradhan, Ken Catchpole, Nawar Shara, Ryan Arnold, J Sanford Schwartz, Jake Seagull, Kristen Miller

Open access · goldAbstract read
In one paragraph

Article in Health informatics journal. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 44% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
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 at 5 institutions in 1 country.

Muge CapanLeBow College of Business, 6527Drexel University, Philadelphia, PA, USA.
Laura C SchubelNational Center for Human Factors in Healthcare, 121577MedStar Health Research Institute, Washington, DC, USA.ORCID 0000-0001-5258-1407
Ishika PradhanLeBow College of Business, 6527Drexel University, Philadelphia, PA, USA.
Ken CatchpoleClinical Practice and Human Factors, 2345Medical University of South Carolina, Charleston, SC, USA.
Nawar SharaBiostatistics and Biomedical Informatics, 121577MedStar Health Research Institute, Washington, DC, USA.
Ryan ArnoldEmergency Medicine, 22856Santa Ynez Valley Cottage Hospital, Santa Barbara, CA, USA.
J Sanford SchwartzDepartment of Health Care Management, 51288University of Pennsylvania, Philadelphia, PA, USA.
Jake Seagull121577MedStar Health Research Institute, Hyattsville, MD, USA.ORCID 0000-0001-8075-1637
Kristen MillerNational Center for Human Factors in Healthcare, 121577MedStar Health Research Institute, Washington, DC, USA.ORCID 0000-0002-8991-2342
MedStar Health · USDrexel University · USMedical University of South Carolina · USSanta Ynez Valley Cottage Hospital · USUniversity of Pennsylvania · US

Funding

Signaling Sepsis: Developing a framework to optimize alert designR01LM012300 · NLM · MEDSTAR HEALTH RESEARCH INSTITUTE · PI MILLER, KRISTEN ELIZABETH · 2016 to 2020
$1.4M
NIGMS NIH HHS L30 GM120757NLM NIH HHS R01 LM012300
6 · The paper itself

Abstract

Despite acknowledging the value of clinical decision support systems (CDSS) in identifying risk for sepsis-induced health deterioration in-hospitalized patients, the relationship between display features, decision maker characteristics, and recognition of risk by the clinical decision maker remains an understudied, yet promising, area. The objective of this study is to explore the relationship between CDSS display design and perceived clinical risk of in-hospital mortality associated with sepsis. The study utilized data collected through in-person experimental sessions with 91 physicians from the general medical and surgical floors who were recruited across 12 teaching hospitals within the United States. Results of descriptive and statistical analyses provided evidence supporting the impact of display configuration and clinical case severity on perceived risk associated with in-hospital mortality. Specifically, findings showed that a high level of information (represented by the Predisposition, Infection, Response and Organ dysfunction (PIRO) score) and Figure display (as opposed to Text or baseline) increased awareness to recognizing the risk for in-hospital mortality of hospitalized sepsis patients. A CDSS display that synthesizes the optimal features associated with information level and design elements has the potential to enhance the quantification and communication of clinical risk in complex health conditions beyond sepsis.

Indexed as

Decision Support Systems, ClinicalSepsisHospital MortalityHumansOrgan Dysfunction ScoresPerceptionclinical decision-makingclinical decision supportdecision support systemshuman factorsrisk perception

Identifiers

PMID35068208
PMCPMC11804939
OpenAlexW4207052031

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.