↓ Skip to main content

Defining and Measuring Diagnostic Uncertainty in Medicine: A Systematic Review

Overview of attention for article published in Journal of General Internal Medicine, September 2017
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

news
7 news outlets
twitter
49 X users

Citations

dimensions_citation
179 Dimensions

Readers on

mendeley
265 Mendeley
Title
Defining and Measuring Diagnostic Uncertainty in Medicine: A Systematic Review
Published in
Journal of General Internal Medicine, September 2017
DOI 10.1007/s11606-017-4164-1
Pubmed ID
Authors

Viraj Bhise, Suja S. Rajan, Dean F. Sittig, Robert O. Morgan, Pooja Chaudhary, Hardeep Singh

Abstract

Physicians routinely encounter diagnostic uncertainty in practice. Despite its impact on health care utilization, costs and error, measurement of diagnostic uncertainty is poorly understood. We conducted a systematic review to describe how diagnostic uncertainty is defined and measured in medical practice. We searched OVID Medline and PsycINFO databases from inception until May 2017 using a combination of keywords and Medical Subject Headings (MeSH). Additional search strategies included manual review of references identified in the primary search, use of a topic-specific database (AHRQ-PSNet) and expert input. We specifically focused on articles that (1) defined diagnostic uncertainty; (2) conceptualized diagnostic uncertainty in terms of its sources, complexity of its attributes or strategies for managing it; or (3) attempted to measure diagnostic uncertainty. We identified 123 articles for full review, none of which defined diagnostic uncertainty. Three attributes of diagnostic uncertainty were relevant for measurement: (1) it is a subjective perception experienced by the clinician; (2) it has the potential to impact diagnostic evaluation-for example, when inappropriately managed, it can lead to diagnostic delays; and (3) it is dynamic in nature, changing with time. Current methods for measuring diagnostic uncertainty in medical practice include: (1) asking clinicians about their perception of uncertainty (surveys and qualitative interviews), (2) evaluating the patient-clinician encounter (such as by reviews of medical records, transcripts of patient-clinician communication and observation), and (3) experimental techniques (patient vignette studies). The term "diagnostic uncertainty" lacks a clear definition, and there is no comprehensive framework for its measurement in medical practice. Based on review findings, we propose that diagnostic uncertainty be defined as a "subjective perception of an inability to provide an accurate explanation of the patient's health problem." Methodological advancements in measuring diagnostic uncertainty can improve our understanding of diagnostic decision-making and inform interventions to reduce diagnostic errors and overuse of health care resources.

X Demographics

X Demographics

The data shown below were collected from the profiles of 49 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 265 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 265 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 37 14%
Student > Ph. D. Student 34 13%
Student > Master 32 12%
Student > Bachelor 21 8%
Other 18 7%
Other 63 24%
Unknown 60 23%
Readers by discipline Count As %
Medicine and Dentistry 88 33%
Nursing and Health Professions 29 11%
Psychology 15 6%
Social Sciences 10 4%
Engineering 7 3%
Other 39 15%
Unknown 77 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 81. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 March 2023.
All research outputs
#530,499
of 25,540,105 outputs
Outputs from Journal of General Internal Medicine
#413
of 8,217 outputs
Outputs of similar age
#11,044
of 326,110 outputs
Outputs of similar age from Journal of General Internal Medicine
#9
of 59 outputs
Altmetric has tracked 25,540,105 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,217 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.1. This one has done particularly well, scoring higher than 94% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 326,110 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 59 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.