Literature DB >> 30298436

Utilization of Structured Reporting to Monitor Outcomes of Doppler Ultrasound Performed for Deep Vein Thrombosis.

Travis Browning1,2, Sura Giri3,4, Ron Peshock4, Julia Fielding4.   

Abstract

Determining the clinical impact of imaging exams at the enterprise level is problematic, as radiology reports historically have been created with the content meant primarily for the referring provider. Structured reporting can establish the foundation for enterprise monitoring of imaging outcomes without manual review providing the framework for assessment of utilization and quality. Ultrasound (US) for deep vein thrombosis evaluation (DVT) is an ideal testbed for assessing this functionality. The system standard template for Doppler US for extremity venous evaluation for DVT was updated with a discrete fixed picklist of impression options and implemented system wide. Template utilization and interpretive outcomes were actively monitored and use reinforced as part of standard clinical practice. From January 1, 2017 to December 31, 2017, 9111 US exams for DVT were performed with 8997 utilizing structured reporting (98.75%). Of those in the structured reporting group, 1074 (11.79%) were positive for any type of DVT with 732 (8.03%) reported as Acute/New above the knee. Positive rates for any type of DVT were 10.29% emergency department, 14.17% inpatient, and 13.20% outpatient. While being the lowest positive rate, the emergency department had the highest overall volume of exams. Structured reporting for DVT US assessment outcomes can be implemented with a very high rate of radiologist adoption and adherence providing accurate determination of positive rates, month by month, in differing patient locations. Structured elements can be used to automatically trigger downstream processes; in our institution, this will alert providers in the EHR if the patient does not receive anticoagulation within 2 h of a positive test. This lays the foundation for effective enterprise assessment of imaging outcomes forming the basis of future quality and safety initiatives on optimizing health system resource utilization.

Entities:  

Keywords:  DVT; Enterprise reporting; Quality; Structured reporting; Utilization

Year:  2019        PMID: 30298436      PMCID: PMC6499843          DOI: 10.1007/s10278-018-0131-6

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  12 in total

1.  Radiology report clarity: a cohort study of structured reporting compared with conventional dictation.

Authors:  Annette J Johnson; Michael Y M Chen; Michael E Zapadka; Eric M Lyders; Benjamin Littenberg
Journal:  J Am Coll Radiol       Date:  2010-07       Impact factor: 5.532

Review 2.  Radiology reporting, past, present, and future: the radiologist's perspective.

Authors:  Bruce I Reiner; Nancy Knight; Eliot L Siegel
Journal:  J Am Coll Radiol       Date:  2007-05       Impact factor: 5.532

3.  Toward best practices in radiology reporting.

Authors:  Charles E Kahn; Curtis P Langlotz; Elizabeth S Burnside; John A Carrino; David S Channin; David M Hovsepian; Daniel L Rubin
Journal:  Radiology       Date:  2009-09       Impact factor: 11.105

4.  The radiology report of the future: a summary of the 2007 Intersociety Conference.

Authors:  N Reed Dunnick; Curtis P Langlotz
Journal:  J Am Coll Radiol       Date:  2008-05       Impact factor: 5.532

5.  IT infrastructure in the era of imaging 3.0.

Authors:  Geraldine B McGinty; Bibb Allen; J Raymond Geis; Christoph Wald
Journal:  J Am Coll Radiol       Date:  2014-12-01       Impact factor: 5.532

6.  Creation of an Open Framework for Point-of-Care Computer-Assisted Reporting and Decision Support Tools for Radiologists.

Authors:  Tarik K Alkasab; Bernardo C Bizzo; Lincoln L Berland; Sujith Nair; Pari V Pandharipande; H Benjamin Harvey
Journal:  J Am Coll Radiol       Date:  2017-06-23       Impact factor: 5.532

7.  Actionable findings and the role of IT support: report of the ACR Actionable Reporting Work Group.

Authors:  Paul A Larson; Lincoln L Berland; Brent Griffith; Charles E Kahn; Lawrence A Liebscher
Journal:  J Am Coll Radiol       Date:  2014-01-30       Impact factor: 5.532

Review 8.  Natural Language Processing in Radiology: A Systematic Review.

Authors:  Ewoud Pons; Loes M M Braun; M G Myriam Hunink; Jan A Kors
Journal:  Radiology       Date:  2016-05       Impact factor: 11.105

9.  Large-Scale Implementation of Structured Reporting of Adnexal Masses on Ultrasound.

Authors:  Elizabeth J Suh-Burgmann; Tracy Flanagan; Nina Lee; Todd Osinski; Cliff Sweet; Margaret Lynch; Marianna Caponigro; Jaysheel Mehta; Mubarika Alavi; Lisa J Herrinton
Journal:  J Am Coll Radiol       Date:  2018-03-20       Impact factor: 5.532

10.  Structured reporting of multiphasic CT for pancreatic cancer: potential effect on staging and surgical planning.

Authors:  Olga R Brook; Alexander Brook; Charles M Vollmer; Tara S Kent; Norberto Sanchez; Ivan Pedrosa
Journal:  Radiology       Date:  2014-10-03       Impact factor: 11.105

View more
  1 in total

1.  Structured report data can be used to develop deep learning algorithms: a proof of concept in ankle radiographs.

Authors:  Daniel Pinto Dos Santos; Sebastian Brodehl; Bettina Baeßler; Gordon Arnhold; Thomas Dratsch; Seung-Hun Chon; Peter Mildenberger; Florian Jungmann
Journal:  Insights Imaging       Date:  2019-09-23
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.