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Crowdsourcing consensus: proposal of a novel method for assessing accuracy in echocardiography interpretation.

Publication ,  Journal Article
Minter, S; Armour, A; Tinnemore, A; Strub, K; Crowley, AL; Bloomfield, GS; Alexander, JH; Douglas, PS; Kisslo, JA; Velazquez, EJ; Samad, Z
Published in: Int J Cardiovasc Imaging
November 2018

Quality in stress echocardiography interpretation is often gauged against coronary angiography (CA) data but anatomic obstructive coronary disease on CA is an imperfect gold standard for a stress induced wall motion abnormality. We examined the utility of crowd-sourcing a "majority-vote" consensus as an alternative 'gold standard' against which to evaluate the accuracy of an individual echocardiographer's interpretation of stress echocardiography studies. Participants independently interpreted baseline and post-exercise stress echocardiographic images of cases that had undergone follow up CA within 3 months of the stress echo in two surveys, 2 years apart. We examined the agreement of consensus on survey (survey participant response (> 60%) for one decision) with the stress echocardiography clinical read and with CA results. In the first survey, 29 participants reviewed and independently interpreted 14 stress echo cases. Consensus was reached in all 14 cases. There was good agreement between clinical and consensus (kappa = 0.57), survey participant response and consensus (kappa = 0.68) and consensus and CA results (kappa = 0.40). In the validation survey, the agreement between clinical reads and consensus (kappa = 0.75) and survey participant response and consensus (kappa = 0.81) remained excellent. Independent consensus is achievable and offers a fair comparison for stress echocardiographic interpretation. Future validation work, in other laboratories, and against hard outcomes, is necessary to test the feasibility and effectiveness of this approach.

Duke Scholars

Published In

Int J Cardiovasc Imaging

DOI

EISSN

1875-8312

Publication Date

November 2018

Volume

34

Issue

11

Start / End Page

1725 / 1730

Location

United States

Related Subject Headings

  • Reproducibility of Results
  • Quality Indicators, Health Care
  • Quality Improvement
  • Quality Assurance, Health Care
  • Predictive Value of Tests
  • Pilot Projects
  • Observer Variation
  • Nuclear Medicine & Medical Imaging
  • Humans
  • Feasibility Studies
 

Citation

APA
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MLA
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Minter, S., Armour, A., Tinnemore, A., Strub, K., Crowley, A. L., Bloomfield, G. S., … Samad, Z. (2018). Crowdsourcing consensus: proposal of a novel method for assessing accuracy in echocardiography interpretation. Int J Cardiovasc Imaging, 34(11), 1725–1730. https://doi.org/10.1007/s10554-018-1389-y
Minter, Stephanie, Alicia Armour, Amanda Tinnemore, Karen Strub, Anna Lisa Crowley, Gerald S. Bloomfield, John H. Alexander, et al. “Crowdsourcing consensus: proposal of a novel method for assessing accuracy in echocardiography interpretation.Int J Cardiovasc Imaging 34, no. 11 (November 2018): 1725–30. https://doi.org/10.1007/s10554-018-1389-y.
Minter S, Armour A, Tinnemore A, Strub K, Crowley AL, Bloomfield GS, et al. Crowdsourcing consensus: proposal of a novel method for assessing accuracy in echocardiography interpretation. Int J Cardiovasc Imaging. 2018 Nov;34(11):1725–30.
Minter, Stephanie, et al. “Crowdsourcing consensus: proposal of a novel method for assessing accuracy in echocardiography interpretation.Int J Cardiovasc Imaging, vol. 34, no. 11, Nov. 2018, pp. 1725–30. Pubmed, doi:10.1007/s10554-018-1389-y.
Minter S, Armour A, Tinnemore A, Strub K, Crowley AL, Bloomfield GS, Alexander JH, Douglas PS, Kisslo JA, Velazquez EJ, Samad Z. Crowdsourcing consensus: proposal of a novel method for assessing accuracy in echocardiography interpretation. Int J Cardiovasc Imaging. 2018 Nov;34(11):1725–1730.

Published In

Int J Cardiovasc Imaging

DOI

EISSN

1875-8312

Publication Date

November 2018

Volume

34

Issue

11

Start / End Page

1725 / 1730

Location

United States

Related Subject Headings

  • Reproducibility of Results
  • Quality Indicators, Health Care
  • Quality Improvement
  • Quality Assurance, Health Care
  • Predictive Value of Tests
  • Pilot Projects
  • Observer Variation
  • Nuclear Medicine & Medical Imaging
  • Humans
  • Feasibility Studies