Assessing the representation of occupation information in free-text clinical documents across multiple sources

Elizabeth A. Lindemann; Elizabeth S. Chen; Sripriya Rajamani; Nivedha Manohar; Yan Wang; Genevieve B. Melton

doi:10.3233/978-1-61499-830-3-486

Assessing the representation of occupation information in free-text clinical documents across multiple sources

Elizabeth A. Lindemann, Elizabeth S. Chen, Sripriya Rajamani, Nivedha Manohar, Yan Wang, Genevieve B. Melton

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

2 Scopus citations

Abstract

There has been increasing recognition of the key role of social determinants like occupation on health. Given the relatively poor understanding of occupation information in electronic health records (EHRs), we sought to characterize occupation information within free-text clinical document sources. From six distinct clinical sources, 868 total occupation-related sentences were identified for the study corpus. Building off approaches from previous studies, refined annotation guidelines were created using the National Institute for Occupational Safety and Health Occupational Data for Health data model with elements added to increase granularity. Our corpus generated 2,005 total annotations representing 39 of 41 entity types from the enhanced data model. Highest frequency entities were: Occupation Description (17.7%); Employment Status - Not Specified (12.5%); Employer Name (11.0%); Subject (9.8%); Industry Description (6.2%). Our findings support the value of standardizing entry of EHR occupation information to improve data quality for improved patient care and secondary uses of this information.

Original language	English (US)
Title of host publication	MEDINFO 2017
Subtitle of host publication	Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics
Editors	Zhao Dongsheng, Adi V. Gundlapalli, Jaulent Marie-Christine
Publisher	IOS Press
Pages	486-490
Number of pages	5
ISBN (Electronic)	9781614998297
DOIs	https://doi.org/10.3233/978-1-61499-830-3-486
State	Published - 2017
Event	16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017 - Hangzhou, China Duration: Aug 21 2017 → Aug 25 2017

Publication series

Name	Studies in Health Technology and Informatics
Volume	245
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Other

Other	16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017
Country/Territory	China
City	Hangzhou
Period	8/21/17 → 8/25/17

Bibliographical note

Publisher Copyright:
© 2017 International Medical Informatics Association (IMIA) and IOS Press.

Keywords

Electronic health records
Occupations
Social determinants of health

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access

10.3233/978-1-61499-830-3-486

OpenUrl availability

Full text

Cite this

Lindemann, E. A., Chen, E. S., Rajamani, S., Manohar, N., Wang, Y., & Melton, G. B. (2017). Assessing the representation of occupation information in free-text clinical documents across multiple sources. In Z. Dongsheng, A. V. Gundlapalli, & J. Marie-Christine (Eds.), MEDINFO 2017: Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics (pp. 486-490). (Studies in Health Technology and Informatics; Vol. 245). IOS Press. https://doi.org/10.3233/978-1-61499-830-3-486

Assessing the representation of occupation information in free-text clinical documents across multiple sources. / Lindemann, Elizabeth A.; Chen, Elizabeth S.; Rajamani, Sripriya et al.
MEDINFO 2017: Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics. ed. / Zhao Dongsheng; Adi V. Gundlapalli; Jaulent Marie-Christine. IOS Press, 2017. p. 486-490 (Studies in Health Technology and Informatics; Vol. 245).

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

Lindemann, EA, Chen, ES, Rajamani, S, Manohar, N, Wang, Y & Melton, GB 2017, Assessing the representation of occupation information in free-text clinical documents across multiple sources. in Z Dongsheng, AV Gundlapalli & J Marie-Christine (eds), MEDINFO 2017: Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics. Studies in Health Technology and Informatics, vol. 245, IOS Press, pp. 486-490, 16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017, Hangzhou, China, 8/21/17. https://doi.org/10.3233/978-1-61499-830-3-486

Lindemann EA, Chen ES, Rajamani S, Manohar N, Wang Y, Melton GB. Assessing the representation of occupation information in free-text clinical documents across multiple sources. In Dongsheng Z, Gundlapalli AV, Marie-Christine J, editors, MEDINFO 2017: Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics. IOS Press. 2017. p. 486-490. (Studies in Health Technology and Informatics). doi: 10.3233/978-1-61499-830-3-486

Lindemann, Elizabeth A. ; Chen, Elizabeth S. ; Rajamani, Sripriya et al. / Assessing the representation of occupation information in free-text clinical documents across multiple sources. MEDINFO 2017: Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics. editor / Zhao Dongsheng ; Adi V. Gundlapalli ; Jaulent Marie-Christine. IOS Press, 2017. pp. 486-490 (Studies in Health Technology and Informatics).

@inproceedings{400677bbe0c44cda8d9711caa1e80a2a,

title = "Assessing the representation of occupation information in free-text clinical documents across multiple sources",

abstract = "There has been increasing recognition of the key role of social determinants like occupation on health. Given the relatively poor understanding of occupation information in electronic health records (EHRs), we sought to characterize occupation information within free-text clinical document sources. From six distinct clinical sources, 868 total occupation-related sentences were identified for the study corpus. Building off approaches from previous studies, refined annotation guidelines were created using the National Institute for Occupational Safety and Health Occupational Data for Health data model with elements added to increase granularity. Our corpus generated 2,005 total annotations representing 39 of 41 entity types from the enhanced data model. Highest frequency entities were: Occupation Description (17.7%); Employment Status - Not Specified (12.5%); Employer Name (11.0%); Subject (9.8%); Industry Description (6.2%). Our findings support the value of standardizing entry of EHR occupation information to improve data quality for improved patient care and secondary uses of this information.",

keywords = "Electronic health records, Occupations, Social determinants of health",

author = "Lindemann, {Elizabeth A.} and Chen, {Elizabeth S.} and Sripriya Rajamani and Nivedha Manohar and Yan Wang and Melton, {Genevieve B.}",

note = "Publisher Copyright: {\textcopyright} 2017 International Medical Informatics Association (IMIA) and IOS Press.; 16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017 ; Conference date: 21-08-2017 Through 25-08-2017",

year = "2017",

doi = "10.3233/978-1-61499-830-3-486",

language = "English (US)",

series = "Studies in Health Technology and Informatics",

publisher = "IOS Press",

pages = "486--490",

editor = "Zhao Dongsheng and Gundlapalli, {Adi V.} and Jaulent Marie-Christine",

booktitle = "MEDINFO 2017",

}

TY - GEN

T1 - Assessing the representation of occupation information in free-text clinical documents across multiple sources

AU - Lindemann, Elizabeth A.

AU - Chen, Elizabeth S.

AU - Rajamani, Sripriya

AU - Manohar, Nivedha

AU - Wang, Yan

AU - Melton, Genevieve B.

PY - 2017

Y1 - 2017

N2 - There has been increasing recognition of the key role of social determinants like occupation on health. Given the relatively poor understanding of occupation information in electronic health records (EHRs), we sought to characterize occupation information within free-text clinical document sources. From six distinct clinical sources, 868 total occupation-related sentences were identified for the study corpus. Building off approaches from previous studies, refined annotation guidelines were created using the National Institute for Occupational Safety and Health Occupational Data for Health data model with elements added to increase granularity. Our corpus generated 2,005 total annotations representing 39 of 41 entity types from the enhanced data model. Highest frequency entities were: Occupation Description (17.7%); Employment Status - Not Specified (12.5%); Employer Name (11.0%); Subject (9.8%); Industry Description (6.2%). Our findings support the value of standardizing entry of EHR occupation information to improve data quality for improved patient care and secondary uses of this information.

AB - There has been increasing recognition of the key role of social determinants like occupation on health. Given the relatively poor understanding of occupation information in electronic health records (EHRs), we sought to characterize occupation information within free-text clinical document sources. From six distinct clinical sources, 868 total occupation-related sentences were identified for the study corpus. Building off approaches from previous studies, refined annotation guidelines were created using the National Institute for Occupational Safety and Health Occupational Data for Health data model with elements added to increase granularity. Our corpus generated 2,005 total annotations representing 39 of 41 entity types from the enhanced data model. Highest frequency entities were: Occupation Description (17.7%); Employment Status - Not Specified (12.5%); Employer Name (11.0%); Subject (9.8%); Industry Description (6.2%). Our findings support the value of standardizing entry of EHR occupation information to improve data quality for improved patient care and secondary uses of this information.

KW - Electronic health records

KW - Occupations

KW - Social determinants of health

UR - http://www.scopus.com/inward/record.url?scp=85040509212&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85040509212&partnerID=8YFLogxK

U2 - 10.3233/978-1-61499-830-3-486

DO - 10.3233/978-1-61499-830-3-486

M3 - Conference contribution

C2 - 29295142

AN - SCOPUS:85040509212

T3 - Studies in Health Technology and Informatics

SP - 486

EP - 490

BT - MEDINFO 2017

A2 - Dongsheng, Zhao

A2 - Gundlapalli, Adi V.

A2 - Marie-Christine, Jaulent

PB - IOS Press

T2 - 16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017

Y2 - 21 August 2017 through 25 August 2017

ER -

Assessing the representation of occupation information in free-text clinical documents across multiple sources

Abstract

Publication series

Other

Bibliographical note

Keywords

UN SDGs

Access

OpenUrl availability

Other files and links

Fingerprint

Cite this