CDS-Compare: A Web Application for Machine Learning Assisted Curation of Clinical Order Sets

Zackary Falls; Steven H. Brown; Naveed Shah; Frank Lehouillier; Randeep Badwal; Kendria Hall; Gillian Franklin; William H. Kelly; Andrew Holdaway; Diane Montella; Linda Wedemeyer; Sarita Keni; Eric Rose; Jonathan R. Nebeker; Peter L. Elkin

doi:10.3233/SHTI220502

CDS-Compare: A Web Application for Machine Learning Assisted Curation of Clinical Order Sets

Zackary Falls
, Steven H. Brown
, Naveed Shah
, Frank Lehouillier
, Randeep Badwal
, Kendria Hall
, Gillian Franklin
, William H. Kelly
, Andrew Holdaway
, Diane Montella
, Linda Wedemeyer
, Sarita Keni
, Eric Rose
, Jonathan R. Nebeker
, Peter L. Elkin

Department of Veterans Affairs
Vanderbilt University
SUNY Buffalo
University of Washington
University of Utah

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Order sets that adhere to disease-specific guidelines have been shown to increase clinician efficiency and patient safety but curating these order sets, particularly for consistency across multiple sites, is difficult and time consuming. We created software called CDS-Compare to alleviate the burden on expert reviewers in rapidly and effectively curating large databases of order sets. We applied our clustering-based software to a database of NLP-processed order sets extracted from VA's Electronic Health Record, then had subject-matter experts review the web application version of our software for clustering validity.

Original language	English
Title of host publication	Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022
Editors	Brigitte Seroussi, Patrick Weber, Ferdinand Dhombres, Cyril Grouin, Jan-David Liebe, Jan-David Liebe, Jan-David Liebe, Sylvia Pelayo, Andrea Pinna, Bastien Rance, Bastien Rance, Lucia Sacchi, Adrien Ugon, Adrien Ugon, Arriel Benis, Parisis Gallos
Publisher	IOS Press BV
Pages	465-469
Number of pages	5
ISBN (Electronic)	9781643682846
DOIs	https://doi.org/10.3233/SHTI220502
State	Published - May 25 2022
Event	32nd Medical Informatics Europe Conference, MIE 2022 - Nice, France Duration: May 27 2022 → May 30 2022

Publication series

Name	Studies in Health Technology and Informatics
Volume	294
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Conference

Conference	32nd Medical Informatics Europe Conference, MIE 2022
Country/Territory	France
City	Nice
Period	05/27/22 → 05/30/22

Keywords

Clinical Decision Support
Database Curation
Machine Learning
Order sets

Access to Document

10.3233/SHTI220502

Cite this

Falls, Z., Brown, S. H., Shah, N., Lehouillier, F., Badwal, R., Hall, K., Franklin, G., Kelly, W. H., Holdaway, A., Montella, D., Wedemeyer, L., Keni, S., Rose, E., Nebeker, J. R., & Elkin, P. L. (2022). CDS-Compare: A Web Application for Machine Learning Assisted Curation of Clinical Order Sets. In B. Seroussi, P. Weber, F. Dhombres, C. Grouin, J.-D. Liebe, J.-D. Liebe, J.-D. Liebe, S. Pelayo, A. Pinna, B. Rance, B. Rance, L. Sacchi, A. Ugon, A. Ugon, A. Benis, & P. Gallos (Eds.), Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022 (pp. 465-469). (Studies in Health Technology and Informatics; Vol. 294). IOS Press BV. https://doi.org/10.3233/SHTI220502

Falls, Zackary ; Brown, Steven H. ; Shah, Naveed et al. / CDS-Compare : A Web Application for Machine Learning Assisted Curation of Clinical Order Sets. Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022. editor / Brigitte Seroussi ; Patrick Weber ; Ferdinand Dhombres ; Cyril Grouin ; Jan-David Liebe ; Jan-David Liebe ; Jan-David Liebe ; Sylvia Pelayo ; Andrea Pinna ; Bastien Rance ; Bastien Rance ; Lucia Sacchi ; Adrien Ugon ; Adrien Ugon ; Arriel Benis ; Parisis Gallos. IOS Press BV, 2022. pp. 465-469 (Studies in Health Technology and Informatics).

@inproceedings{e1670b24923a4e059605b14eed8e3303,

title = "CDS-Compare: A Web Application for Machine Learning Assisted Curation of Clinical Order Sets",

abstract = "Order sets that adhere to disease-specific guidelines have been shown to increase clinician efficiency and patient safety but curating these order sets, particularly for consistency across multiple sites, is difficult and time consuming. We created software called CDS-Compare to alleviate the burden on expert reviewers in rapidly and effectively curating large databases of order sets. We applied our clustering-based software to a database of NLP-processed order sets extracted from VA's Electronic Health Record, then had subject-matter experts review the web application version of our software for clustering validity.",

keywords = "Clinical Decision Support, Database Curation, Machine Learning, Order sets",

author = "Zackary Falls and Brown, \{Steven H.\} and Naveed Shah and Frank Lehouillier and Randeep Badwal and Kendria Hall and Gillian Franklin and Kelly, \{William H.\} and Andrew Holdaway and Diane Montella and Linda Wedemeyer and Sarita Keni and Eric Rose and Nebeker, \{Jonathan R.\} and Elkin, \{Peter L.\}",

note = "Publisher Copyright: {\textcopyright} 2022 European Federation for Medical Informatics (EFMI) and IOS Press.; 32nd Medical Informatics Europe Conference, MIE 2022 ; Conference date: 27-05-2022 Through 30-05-2022",

year = "2022",

month = may,

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doi = "10.3233/SHTI220502",

language = "English",

series = "Studies in Health Technology and Informatics",

publisher = "IOS Press BV",

pages = "465--469",

editor = "Brigitte Seroussi and Patrick Weber and Ferdinand Dhombres and Cyril Grouin and Jan-David Liebe and Jan-David Liebe and Jan-David Liebe and Sylvia Pelayo and Andrea Pinna and Bastien Rance and Bastien Rance and Lucia Sacchi and Adrien Ugon and Adrien Ugon and Arriel Benis and Parisis Gallos",

booktitle = "Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022",

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Falls, Z, Brown, SH, Shah, N, Lehouillier, F, Badwal, R, Hall, K , Franklin, G , Kelly, WH, Holdaway, A, Montella, D, Wedemeyer, L, Keni, S, Rose, E, Nebeker, JR & Elkin, PL 2022, CDS-Compare: A Web Application for Machine Learning Assisted Curation of Clinical Order Sets. in B Seroussi, P Weber, F Dhombres, C Grouin, J-D Liebe, J-D Liebe, J-D Liebe, S Pelayo, A Pinna, B Rance, B Rance, L Sacchi, A Ugon, A Ugon, A Benis & P Gallos (eds), Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022. Studies in Health Technology and Informatics, vol. 294, IOS Press BV, pp. 465-469, 32nd Medical Informatics Europe Conference, MIE 2022, Nice, France, 05/27/22. https://doi.org/10.3233/SHTI220502

CDS-Compare: A Web Application for Machine Learning Assisted Curation of Clinical Order Sets. / Falls, Zackary; Brown, Steven H.; Shah, Naveed et al.
Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022. ed. / Brigitte Seroussi; Patrick Weber; Ferdinand Dhombres; Cyril Grouin; Jan-David Liebe; Jan-David Liebe; Jan-David Liebe; Sylvia Pelayo; Andrea Pinna; Bastien Rance; Bastien Rance; Lucia Sacchi; Adrien Ugon; Adrien Ugon; Arriel Benis; Parisis Gallos. IOS Press BV, 2022. p. 465-469 (Studies in Health Technology and Informatics; Vol. 294).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - CDS-Compare

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AU - Brown, Steven H.

AU - Shah, Naveed

AU - Lehouillier, Frank

AU - Badwal, Randeep

AU - Hall, Kendria

AU - Franklin, Gillian

AU - Kelly, William H.

AU - Holdaway, Andrew

AU - Montella, Diane

AU - Wedemeyer, Linda

AU - Keni, Sarita

AU - Rose, Eric

AU - Nebeker, Jonathan R.

AU - Elkin, Peter L.

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AB - Order sets that adhere to disease-specific guidelines have been shown to increase clinician efficiency and patient safety but curating these order sets, particularly for consistency across multiple sites, is difficult and time consuming. We created software called CDS-Compare to alleviate the burden on expert reviewers in rapidly and effectively curating large databases of order sets. We applied our clustering-based software to a database of NLP-processed order sets extracted from VA's Electronic Health Record, then had subject-matter experts review the web application version of our software for clustering validity.

KW - Clinical Decision Support

KW - Database Curation

KW - Machine Learning

KW - Order sets

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M3 - Conference contribution

C2 - 35612123

AN - SCOPUS:85131107248

T3 - Studies in Health Technology and Informatics

SP - 465

EP - 469

BT - Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022

A2 - Seroussi, Brigitte

A2 - Weber, Patrick

A2 - Dhombres, Ferdinand

A2 - Grouin, Cyril

A2 - Liebe, Jan-David

A2 - Pelayo, Sylvia

A2 - Pinna, Andrea

A2 - Rance, Bastien

A2 - Sacchi, Lucia

A2 - Ugon, Adrien

A2 - Benis, Arriel

A2 - Gallos, Parisis

PB - IOS Press BV

Y2 - 27 May 2022 through 30 May 2022

ER -

Falls Z, Brown SH, Shah N, Lehouillier F, Badwal R, Hall K et al. CDS-Compare: A Web Application for Machine Learning Assisted Curation of Clinical Order Sets. In Seroussi B, Weber P, Dhombres F, Grouin C, Liebe JD, Liebe JD, Liebe JD, Pelayo S, Pinna A, Rance B, Rance B, Sacchi L, Ugon A, Ugon A, Benis A, Gallos P, editors, Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022. IOS Press BV. 2022. p. 465-469. (Studies in Health Technology and Informatics). doi: 10.3233/SHTI220502

CDS-Compare: A Web Application for Machine Learning Assisted Curation of Clinical Order Sets

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Keywords

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