Literature DB >> 29101973

Patient-Centered Radiology Reporting: Using Online Crowdsourcing to Assess the Effectiveness of a Web-Based Interactive Radiology Report.

Ryan G Short1, Dana Middleton2, Nicholas T Befera3, Raj Gondalia3, Tina D Tailor3.   

Abstract

PURPOSE: The aim of this study was to evaluate the effectiveness of a patient-centered web-based interactive mammography report.
METHODS: A survey was distributed on Amazon Mechanical Turk, an online crowdsourcing platform. One hundred ninety-three US women ≥18 years of age were surveyed and then randomized to one of three simulated BI-RADS® 0 report formats: standard report, Mammography Quality Standards Act-modeled patient letter, or web-based interactive report. Survey questions assessed participants' report comprehension, satisfaction with and perception of the interpreting radiologist, and experience with the presented report. Two-tailed t tests and χ2 tests were used to evaluate differences among groups.
RESULTS: Participants in the interactive web-based group spent more than double the time viewing the report than the standard report group (160.0 versus 64.2 seconds, P < .001). Report comprehension scores were significantly higher for the interactive web-based and patient letter groups than the standard report group (P < .05). Scores of satisfaction with the interpreting radiologist were significantly higher for the web-based interactive report and patient letter groups than the standard report group (P < .01). There were no significant differences between the patient letter and web-based interactive report groups.
CONCLUSIONS: Radiology report format likely influences communication effectiveness. For result communication to a non-medical patient audience, patient-centric report formats, such as a Mammography Quality Standards Act-modeled patient letter or web-based interactive report, may offer advantages over the standard radiology report. Future work is needed to determine if these findings are reproducible in patient care settings and to determine how best to optimize radiology result communication to patients.
Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Patient-centered; crowdsourcing; mammography

Mesh:

Year:  2017        PMID: 29101973     DOI: 10.1016/j.jacr.2017.07.027

Source DB:  PubMed          Journal:  J Am Coll Radiol        ISSN: 1546-1440            Impact factor:   5.532


  10 in total

1.  Comprehensive Word-Level Classification of Screening Mammography Reports Using a Neural Network Sequence Labeling Approach.

Authors:  Ryan G Short; John Bralich; Dave Bogaty; Nicholas T Befera
Journal:  J Digit Imaging       Date:  2019-10       Impact factor: 4.056

2.  Common Laboratory Results Frequently Misunderstood by a Sample of Mechanical Turk Users.

Authors:  Nabeel Qureshi; Ateev Mehrotra; Robert S Rudin; Shira H Fischer
Journal:  Appl Clin Inform       Date:  2019-03-13       Impact factor: 2.342

3.  Social innovations to increase health coverage: evidence from a crowdsourcing contest in Ghana.

Authors:  Phyllis Dako-Gyeke; Emmanuel Asampong; Kwabena Opoku-Mensah; Philip Teg-Nefaah Tabong; Phyllis Awor; Joseph D Tucker
Journal:  BMJ Open       Date:  2022-06-07       Impact factor: 3.006

4.  Cardiovascular Risk in the Lung Cancer Screening Population: A Multicenter Study Evaluating the Association Between Coronary Artery Calcification and Preventive Statin Prescription.

Authors:  Tina D Tailor; Caroline Chiles; Joseph Yeboah; M Patricia Rivera; Betty C Tong; Fides R Schwartz; Thad Benefield; Lindsay M Lane; Ilona Stashko; Samantha M Thomas; Louise M Henderson
Journal:  J Am Coll Radiol       Date:  2021-02-26       Impact factor: 6.240

Review 5.  Full Radiology Report through Patient Web Portal: A Literature Review.

Authors:  Mohammad Alarifi; Timothy Patrick; Abdulrahman Jabour; Min Wu; Jake Luo
Journal:  Int J Environ Res Public Health       Date:  2020-05-22       Impact factor: 3.390

6.  Understanding patient needs and gaps in radiology reports through online discussion forum analysis.

Authors:  Mohammad Alarifi; Timothy Patrick; Abdulrahman Jabour; Min Wu; Jake Luo
Journal:  Insights Imaging       Date:  2021-04-19

7.  Proposed Questions to Assess the Extent of Knowledge in Understanding the Radiology Report Language.

Authors:  Mohammad Alarifi; Abdulrahman M Jabour; Min Wu; Abdullah Aldosary; Mansour Almanaa; Jake Luo
Journal:  Int J Environ Res Public Health       Date:  2022-09-19       Impact factor: 4.614

Review 8.  Communication of cancer screening results by letter, telephone or in person: A mixed methods systematic review of the effect on attendee anxiety, understanding and preferences.

Authors:  Sian Williamson; Jacoby Patterson; Rebecca Crosby; Rebecca Johnson; Harbinder Sandhu; Samantha Johnson; Jacquie Jenkins; Margaret Casey; Olive Kearins; Sian Taylor-Phillips
Journal:  Prev Med Rep       Date:  2018-12-29

Review 9.  Crowdsourcing in health and medical research: a systematic review.

Authors:  Cheng Wang; Larry Han; Gabriella Stein; Suzanne Day; Cedric Bien-Gund; Allison Mathews; Jason J Ong; Pei-Zhen Zhao; Shu-Fang Wei; Jennifer Walker; Roger Chou; Amy Lee; Angela Chen; Barry Bayus; Joseph D Tucker
Journal:  Infect Dis Poverty       Date:  2020-01-20       Impact factor: 4.520

Review 10.  Multispecialty Enterprise Imaging Workgroup Consensus on Interactive Multimedia Reporting Current State and Road to the Future: HIMSS-SIIM Collaborative White Paper.

Authors:  Christopher J Roth; David A Clunie; David J Vining; Seth J Berkowitz; Alejandro Berlin; Jean-Pierre Bissonnette; Shawn D Clark; Toby C Cornish; Monief Eid; Cree M Gaskin; Alexander K Goel; Genevieve C Jacobs; David Kwan; Damien M Luviano; Morgan P McBee; Kelly Miller; Abdul Moiz Hafiz; Ceferino Obcemea; Anil V Parwani; Veronica Rotemberg; Elliot L Silver; Erik S Storm; James E Tcheng; Karen S Thullner; Les R Folio
Journal:  J Digit Imaging       Date:  2021-06-15       Impact factor: 4.056

  10 in total

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