Temporal trends of multiple sclerosis disease activity: Electronic health records indicators

Liang Liang; Nicole Kim; Jue Hou; Tianrun Cai; Kumar Dahal; Chen Lin; Sean Finan; Guergana Savovoa; Mattia Rosso; Mariann Polgar-Tucsanyi; Howard Weiner; Tanuja Chitnis; Tianxi Cai; Zongqi Xia

doi:10.1016/j.msard.2021.103333

Temporal trends of multiple sclerosis disease activity: Electronic health records indicators

Liang Liang, Nicole Kim, Jue Hou, Tianrun Cai, Kumar Dahal, Chen Lin, Sean Finan, Guergana Savovoa, Mattia Rosso, Mariann Polgar-Tucsanyi, Howard Weiner, Tanuja Chitnis, Tianxi Cai, Zongqi Xia

Biostatistics

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

Background: Long-term data on multiple sclerosis (MS) inflammatory disease activity are limited. We examined electronic health records (EHR) indicators of disease activity in people with MS. Methods: We analyzed prospectively collected research registry data and linked EHR data in a clinic-based cohort from 2000 to 2016. We used the trend of the yearly incident relapse rate from the registry data as benchmark. We then calculated the temporal trends of potentially relevant EHR measures, including mean count of the MS diagnostic code, mentions of MS-related concepts, MS-related health utilizations and selected prescriptions. Results: 1,555 MS patients had both registry and EHR data. Between 2000 and 2016, the registry data showed a declining trend in the yearly incident relapse rate, parallel to an increasing trend of DMT usage. Among the EHR measures, covariate-adjusted frequency of diagnostic code of MS, procedure codes of MS-related imaging studies and emergency room visits, and electronic prescription for steroids declined over time, mirroring the temporal trend of the benchmark yearly incident relapse rate. Conclusion: This study highlights EHR indicators of MS relapse that could enable large-scale examination of long-term disease activities or inform individual patient monitoring in clinical settings where EHR data are available.

Original language	English (US)
Article number	103333
Journal	Multiple Sclerosis and Related Disorders
Volume	57
DOIs	https://doi.org/10.1016/j.msard.2021.103333
State	Published - Jan 2022

Bibliographical note

Funding Information:
We thank all Brigham MS Clinic neurologists who contributed to the study through patient examination and data collection as well as all research participants for their time and efforts. We thank Andrew Cagan and Vivian Gainer for providing technical assistance with the EHR data.

Publisher Copyright:
© 2021 Elsevier B.V.

Keywords

Disease activity
Electronic health records
Electronic medical records
Multiple sclerosis
Relapse

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10.1016/j.msard.2021.103333

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@article{d2b786edcfbb46e9b349f4721b210c1c,

title = "Temporal trends of multiple sclerosis disease activity: Electronic health records indicators",

abstract = "Background: Long-term data on multiple sclerosis (MS) inflammatory disease activity are limited. We examined electronic health records (EHR) indicators of disease activity in people with MS. Methods: We analyzed prospectively collected research registry data and linked EHR data in a clinic-based cohort from 2000 to 2016. We used the trend of the yearly incident relapse rate from the registry data as benchmark. We then calculated the temporal trends of potentially relevant EHR measures, including mean count of the MS diagnostic code, mentions of MS-related concepts, MS-related health utilizations and selected prescriptions. Results: 1,555 MS patients had both registry and EHR data. Between 2000 and 2016, the registry data showed a declining trend in the yearly incident relapse rate, parallel to an increasing trend of DMT usage. Among the EHR measures, covariate-adjusted frequency of diagnostic code of MS, procedure codes of MS-related imaging studies and emergency room visits, and electronic prescription for steroids declined over time, mirroring the temporal trend of the benchmark yearly incident relapse rate. Conclusion: This study highlights EHR indicators of MS relapse that could enable large-scale examination of long-term disease activities or inform individual patient monitoring in clinical settings where EHR data are available.",

keywords = "Disease activity, Electronic health records, Electronic medical records, Multiple sclerosis, Relapse",

author = "Liang Liang and Nicole Kim and Jue Hou and Tianrun Cai and Kumar Dahal and Chen Lin and Sean Finan and Guergana Savovoa and Mattia Rosso and Mariann Polgar-Tucsanyi and Howard Weiner and Tanuja Chitnis and Tianxi Cai and Zongqi Xia",

note = "Funding Information: We thank all Brigham MS Clinic neurologists who contributed to the study through patient examination and data collection as well as all research participants for their time and efforts. We thank Andrew Cagan and Vivian Gainer for providing technical assistance with the EHR data. Publisher Copyright: {\textcopyright} 2021 Elsevier B.V.",

year = "2022",

month = jan,

doi = "10.1016/j.msard.2021.103333",

language = "English (US)",

volume = "57",

journal = "Multiple Sclerosis and Related Disorders",

issn = "2211-0348",

publisher = "Elsevier B.V.",

}

TY - JOUR

T1 - Temporal trends of multiple sclerosis disease activity

T2 - Electronic health records indicators

AU - Liang, Liang

AU - Kim, Nicole

AU - Hou, Jue

AU - Cai, Tianrun

AU - Dahal, Kumar

AU - Lin, Chen

AU - Finan, Sean

AU - Savovoa, Guergana

AU - Rosso, Mattia

AU - Polgar-Tucsanyi, Mariann

AU - Weiner, Howard

AU - Chitnis, Tanuja

AU - Cai, Tianxi

AU - Xia, Zongqi

N1 - Funding Information: We thank all Brigham MS Clinic neurologists who contributed to the study through patient examination and data collection as well as all research participants for their time and efforts. We thank Andrew Cagan and Vivian Gainer for providing technical assistance with the EHR data. Publisher Copyright: © 2021 Elsevier B.V.

PY - 2022/1

Y1 - 2022/1

N2 - Background: Long-term data on multiple sclerosis (MS) inflammatory disease activity are limited. We examined electronic health records (EHR) indicators of disease activity in people with MS. Methods: We analyzed prospectively collected research registry data and linked EHR data in a clinic-based cohort from 2000 to 2016. We used the trend of the yearly incident relapse rate from the registry data as benchmark. We then calculated the temporal trends of potentially relevant EHR measures, including mean count of the MS diagnostic code, mentions of MS-related concepts, MS-related health utilizations and selected prescriptions. Results: 1,555 MS patients had both registry and EHR data. Between 2000 and 2016, the registry data showed a declining trend in the yearly incident relapse rate, parallel to an increasing trend of DMT usage. Among the EHR measures, covariate-adjusted frequency of diagnostic code of MS, procedure codes of MS-related imaging studies and emergency room visits, and electronic prescription for steroids declined over time, mirroring the temporal trend of the benchmark yearly incident relapse rate. Conclusion: This study highlights EHR indicators of MS relapse that could enable large-scale examination of long-term disease activities or inform individual patient monitoring in clinical settings where EHR data are available.

AB - Background: Long-term data on multiple sclerosis (MS) inflammatory disease activity are limited. We examined electronic health records (EHR) indicators of disease activity in people with MS. Methods: We analyzed prospectively collected research registry data and linked EHR data in a clinic-based cohort from 2000 to 2016. We used the trend of the yearly incident relapse rate from the registry data as benchmark. We then calculated the temporal trends of potentially relevant EHR measures, including mean count of the MS diagnostic code, mentions of MS-related concepts, MS-related health utilizations and selected prescriptions. Results: 1,555 MS patients had both registry and EHR data. Between 2000 and 2016, the registry data showed a declining trend in the yearly incident relapse rate, parallel to an increasing trend of DMT usage. Among the EHR measures, covariate-adjusted frequency of diagnostic code of MS, procedure codes of MS-related imaging studies and emergency room visits, and electronic prescription for steroids declined over time, mirroring the temporal trend of the benchmark yearly incident relapse rate. Conclusion: This study highlights EHR indicators of MS relapse that could enable large-scale examination of long-term disease activities or inform individual patient monitoring in clinical settings where EHR data are available.

KW - Disease activity

KW - Electronic health records

KW - Electronic medical records

KW - Multiple sclerosis

KW - Relapse

UR - https://www.scopus.com/pages/publications/85118353547

UR - https://www.scopus.com/inward/citedby.url?scp=85118353547&partnerID=8YFLogxK

U2 - 10.1016/j.msard.2021.103333

DO - 10.1016/j.msard.2021.103333

M3 - Article

C2 - 35158446

AN - SCOPUS:85118353547

SN - 2211-0348

VL - 57

JO - Multiple Sclerosis and Related Disorders

JF - Multiple Sclerosis and Related Disorders

M1 - 103333

ER -

Temporal trends of multiple sclerosis disease activity: Electronic health records indicators

Abstract

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