Classification of Clinical Notes from a Heart Failure Telehealth Network

Fabian Wiesmüller; Fabian Wiesmüller; Aaron Lauschensky; Martin Baumgartner; Dieter Hayn; Karl Kreiner; Bettina Fetz; Luca Brunelli; Gerhard Pölzl; Bernhard Pfeifer; Sabrina Neururer; Günter Schreier

doi:10.3233/SHTI230270

Classification of Clinical Notes from a Heart Failure Telehealth Network

Fabian Wiesmüller (Speaker), Fabian Wiesmüller, Aaron Lauschensky, Martin Baumgartner, Dieter Hayn, Karl Kreiner, Bettina Fetz, Luca Brunelli, Gerhard Pölzl, Bernhard Pfeifer, Sabrina Neururer, Günter Schreier

Digital Health Information Systems

Research output: Chapter in Book or Conference Proceedings › Conference Proceedings with Oral Presentation › peer-review

Abstract

Heart failure is a common chronic disease which is associated with high re-hospitalization and mortality rates. Within the telemedicine-assisted transitional care disease management program HerzMobil, monitoring data such as daily measured vital parameters and various other heart failure related data are collected in a structured way. Additionally, involved healthcare professionals communicate with one another via the system using free-text clinical notes. Since manual annotation of such notes is too time-consuming for routine care applications, an automated analysis process is needed. In the present study, we established a ground truth classification of 636 randomly selected clinical notes from HerzMobil based on annotations of 9 experts with different professional background (2 physicians, 4 nurses, and 3 engineers). We analyzed the influence of the professional background on the inter annotator reliability and compared the results with the accuracy of an automated classification algorithm. We found significant differences depending on the profession and on the category. These results indicate that different professional backgrounds should be considered when selecting annotators in such scenarios.

Original language	English
Title of host publication	Caring is Sharing – Exploiting the Value in Data for Health and Innovation
Subtitle of host publication	Proceedings of the MIE 2023
Editors	Maria Hägglun, Madeleine Blusi, Stefano Bonacina, Lina Nilsson, Inge Cort Madsen, Sylvia Pelayo, Anne Moen, Arriel Benis, Lars Lindsköld, Parisis Gallos
Publisher	IOS Press BV
Chapter	Section 7. Natural Language Processing
Pages	803-807
Number of pages	5
Volume	302
ISBN (Electronic)	978-1-64368-389-8
ISBN (Print)	978-1-64368-388-1
DOIs	https://doi.org/10.3233/SHTI230270
Publication status	Published - 18 May 2023
Event	Medical Informatics Europe 2023 (MIE 2023): Caring is Sharing - Exploiting Value in Data for Health and Innovation - Mässans gata 24, Gothenburg, Sweden Duration: 22 May 2023 → 25 May 2023 https://www.mie2023.org/

Publication series

Name	Studies in Health Technology and Informatics
Publisher	IOS Press
Volume	302
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Conference

Conference	Medical Informatics Europe 2023 (MIE 2023)
Abbreviated title	MIE 2023
Country/Territory	Sweden
City	Gothenburg
Period	22/05/23 → 25/05/23
Internet address	https://www.mie2023.org/

Research Field

Exploration of Digital Health

Keywords

Clinical notes
Annotation
Text classification
Natural Language Processing

Access to Document

10.3233/SHTI230270Licence: CC BY-NC

Cite this

Wiesmüller, F., Wiesmüller, F., Lauschensky, A., Baumgartner, M., Hayn, D., Kreiner, K., Fetz, B., Brunelli, L., Pölzl, G., Pfeifer, B., Neururer, S., & Schreier, G. (2023). Classification of Clinical Notes from a Heart Failure Telehealth Network. In M. Hägglun, M. Blusi, S. Bonacina, L. Nilsson, I. C. Madsen, S. Pelayo, A. Moen, A. Benis, L. Lindsköld, & P. Gallos (Eds.), Caring is Sharing – Exploiting the Value in Data for Health and Innovation: Proceedings of the MIE 2023 (Vol. 302, pp. 803-807). (Studies in Health Technology and Informatics; Vol. 302). IOS Press BV. https://doi.org/10.3233/SHTI230270

Wiesmüller, Fabian ; Wiesmüller, Fabian ; Lauschensky, Aaron et al. / Classification of Clinical Notes from a Heart Failure Telehealth Network. Caring is Sharing – Exploiting the Value in Data for Health and Innovation: Proceedings of the MIE 2023. editor / Maria Hägglun ; Madeleine Blusi ; Stefano Bonacina ; Lina Nilsson ; Inge Cort Madsen ; Sylvia Pelayo ; Anne Moen ; Arriel Benis ; Lars Lindsköld ; Parisis Gallos. Vol. 302 IOS Press BV, 2023. pp. 803-807 (Studies in Health Technology and Informatics).

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title = "Classification of Clinical Notes from a Heart Failure Telehealth Network",

abstract = "Heart failure is a common chronic disease which is associated with high re-hospitalization and mortality rates. Within the telemedicine-assisted transitional care disease management program HerzMobil, monitoring data such as daily measured vital parameters and various other heart failure related data are collected in a structured way. Additionally, involved healthcare professionals communicate with one another via the system using free-text clinical notes. Since manual annotation of such notes is too time-consuming for routine care applications, an automated analysis process is needed. In the present study, we established a ground truth classification of 636 randomly selected clinical notes from HerzMobil based on annotations of 9 experts with different professional background (2 physicians, 4 nurses, and 3 engineers). We analyzed the influence of the professional background on the inter annotator reliability and compared the results with the accuracy of an automated classification algorithm. We found significant differences depending on the profession and on the category. These results indicate that different professional backgrounds should be considered when selecting annotators in such scenarios.",

keywords = "Clinical notes, Annotation, Text classification, Natural Language Processing",

author = "Fabian Wiesm{\"u}ller and Fabian Wiesm{\"u}ller and Aaron Lauschensky and Martin Baumgartner and Dieter Hayn and Karl Kreiner and Bettina Fetz and Luca Brunelli and Gerhard P{\"o}lzl and Bernhard Pfeifer and Sabrina Neururer and G{\"u}nter Schreier",

note = "{\textcopyright} 2023 European Federation for Medical Informatics (EFMI) and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0); Medical Informatics Europe 2023 (MIE 2023) : Caring is Sharing - Exploiting Value in Data for Health and Innovation, MIE 2023 ; Conference date: 22-05-2023 Through 25-05-2023",

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pages = "803--807",

editor = "Maria H{\"a}gglun and Madeleine Blusi and Stefano Bonacina and Lina Nilsson and Madsen, {Inge Cort} and Sylvia Pelayo and Anne Moen and Arriel Benis and Lars Lindsk{\"o}ld and Parisis Gallos",

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Wiesmüller, F , Wiesmüller, F , Lauschensky, A , Baumgartner, M , Hayn, D , Kreiner, K, Fetz, B, Brunelli, L, Pölzl, G, Pfeifer, B, Neururer, S & Schreier, G 2023, Classification of Clinical Notes from a Heart Failure Telehealth Network. in M Hägglun, M Blusi, S Bonacina, L Nilsson, IC Madsen, S Pelayo, A Moen, A Benis, L Lindsköld & P Gallos (eds), Caring is Sharing – Exploiting the Value in Data for Health and Innovation: Proceedings of the MIE 2023. vol. 302, Studies in Health Technology and Informatics, vol. 302, IOS Press BV, pp. 803-807, Medical Informatics Europe 2023 (MIE 2023), Gothenburg, Sweden, 22/05/23. https://doi.org/10.3233/SHTI230270

Classification of Clinical Notes from a Heart Failure Telehealth Network. / Wiesmüller, Fabian (Speaker); Wiesmüller, Fabian ; Lauschensky, Aaron et al.
Caring is Sharing – Exploiting the Value in Data for Health and Innovation: Proceedings of the MIE 2023. ed. / Maria Hägglun; Madeleine Blusi; Stefano Bonacina; Lina Nilsson; Inge Cort Madsen; Sylvia Pelayo; Anne Moen; Arriel Benis; Lars Lindsköld; Parisis Gallos. Vol. 302 IOS Press BV, 2023. p. 803-807 (Studies in Health Technology and Informatics; Vol. 302).

Research output: Chapter in Book or Conference Proceedings › Conference Proceedings with Oral Presentation › peer-review

TY - GEN

T1 - Classification of Clinical Notes from a Heart Failure Telehealth Network

AU - Wiesmüller, Fabian

AU - Lauschensky, Aaron

AU - Baumgartner, Martin

AU - Hayn, Dieter

AU - Kreiner, Karl

AU - Fetz, Bettina

AU - Brunelli, Luca

AU - Pölzl, Gerhard

AU - Pfeifer, Bernhard

AU - Neururer, Sabrina

AU - Schreier, Günter

A2 - Wiesmüller, Fabian

A2 - Hägglun, Maria

A2 - Blusi, Madeleine

A2 - Bonacina, Stefano

A2 - Nilsson, Lina

A2 - Madsen, Inge Cort

A2 - Pelayo, Sylvia

A2 - Moen, Anne

A2 - Benis, Arriel

A2 - Lindsköld, Lars

A2 - Gallos, Parisis

N1 - © 2023 European Federation for Medical Informatics (EFMI) and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0)

PY - 2023/5/18

Y1 - 2023/5/18

N2 - Heart failure is a common chronic disease which is associated with high re-hospitalization and mortality rates. Within the telemedicine-assisted transitional care disease management program HerzMobil, monitoring data such as daily measured vital parameters and various other heart failure related data are collected in a structured way. Additionally, involved healthcare professionals communicate with one another via the system using free-text clinical notes. Since manual annotation of such notes is too time-consuming for routine care applications, an automated analysis process is needed. In the present study, we established a ground truth classification of 636 randomly selected clinical notes from HerzMobil based on annotations of 9 experts with different professional background (2 physicians, 4 nurses, and 3 engineers). We analyzed the influence of the professional background on the inter annotator reliability and compared the results with the accuracy of an automated classification algorithm. We found significant differences depending on the profession and on the category. These results indicate that different professional backgrounds should be considered when selecting annotators in such scenarios.

AB - Heart failure is a common chronic disease which is associated with high re-hospitalization and mortality rates. Within the telemedicine-assisted transitional care disease management program HerzMobil, monitoring data such as daily measured vital parameters and various other heart failure related data are collected in a structured way. Additionally, involved healthcare professionals communicate with one another via the system using free-text clinical notes. Since manual annotation of such notes is too time-consuming for routine care applications, an automated analysis process is needed. In the present study, we established a ground truth classification of 636 randomly selected clinical notes from HerzMobil based on annotations of 9 experts with different professional background (2 physicians, 4 nurses, and 3 engineers). We analyzed the influence of the professional background on the inter annotator reliability and compared the results with the accuracy of an automated classification algorithm. We found significant differences depending on the profession and on the category. These results indicate that different professional backgrounds should be considered when selecting annotators in such scenarios.

KW - Clinical notes

KW - Annotation

KW - Text classification

KW - Natural Language Processing

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U2 - 10.3233/SHTI230270

DO - 10.3233/SHTI230270

M3 - Conference Proceedings with Oral Presentation

C2 - 37203499

SN - 978-1-64368-388-1

VL - 302

T3 - Studies in Health Technology and Informatics

SP - 803

EP - 807

BT - Caring is Sharing – Exploiting the Value in Data for Health and Innovation

PB - IOS Press BV

T2 - Medical Informatics Europe 2023 (MIE 2023)

Y2 - 22 May 2023 through 25 May 2023

ER -

Wiesmüller F , Wiesmüller F , Lauschensky A , Baumgartner M , Hayn D , Kreiner K et al. Classification of Clinical Notes from a Heart Failure Telehealth Network. In Hägglun M, Blusi M, Bonacina S, Nilsson L, Madsen IC, Pelayo S, Moen A, Benis A, Lindsköld L, Gallos P, editors, Caring is Sharing – Exploiting the Value in Data for Health and Innovation: Proceedings of the MIE 2023. Vol. 302. IOS Press BV. 2023. p. 803-807. (Studies in Health Technology and Informatics). doi: 10.3233/SHTI230270

Classification of Clinical Notes from a Heart Failure Telehealth Network

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