Stroke Care and the Role of Big Data in Healthcare and Stroke

Lidong Wang; Cheryl Ann Alexander

doi:doi:10.11648/j.rs.20160101.13

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Stroke Care and the Role of Big Data in Healthcare and Stroke

Lidong Wang, Cheryl Ann Alexander

Published in Rehabilitation Science (Volume 1, Issue 1)

Received: 11 September 2016 Accepted: 30 September 2016 Published: 25 November 2016

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Abstract

Theoretically current electronic health data can now be securely linked on an unprecedented scale, potentially illuminating how diseases manifest and which treatments are best applied in the real world. Increasing volumes of information on real-time, actual patient experiences are now contained on social media and patient portal websites. Innovations and insight into the health care for individuals and entire populations can be gained when information from health monitors, genomic data, and clinical trial data is merged. In other words, we now have the theoretical technology to accumulate, store, convert, access, and evaluate massive amounts of data at a modest cost. Performance and clinical data from health care facilities, including clinics and hospitals, clinical research data by industry, and academic data from patient populations and the general public which may be generated through social media and/or other sources is included in big data. Just as access to sizable datasets evolves and becomes easier, analytical mistakes may occur more often and be easier to make lest rigorous standards and governance controls are employed. Indeed, it is more likely that improved analytics will also introduce us to at least a few more uncomfortable insights into the negligible value of some medicines. It is also noteworthy to mention that one common error is the assumption that the value of big data is within the data itself—its volume, accuracy, accessibility, “linkability,” etc. Unfortunately, despite the importance of the information, or the “bigger” the data, the greater the likelihood that this does not hold true. This review paper examines the relationship of big data to stroke care in a variety of stroke-related issues including: big data in stroke care, big data and visual analytics, big data in telecardiology, and some challenges and indications for future research.

Published in	Rehabilitation Science (Volume 1, Issue 1)
DOI	10.11648/j.rs.20160101.13
Page(s)	16-24
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Stroke, Big Data, Hypertension, Telecardiology, Electronic Medical Record (EMR), Electronic Health Record (EHR), Big Data Analytics, Machine Learning, Data Mining

References

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[15]	Denham, E. (2016). Speech to the big data surveillance plenary research workshop, information and privacy commissioner for BC, May 12.
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APA Style

Lidong Wang, Cheryl Ann Alexander. (2016). Stroke Care and the Role of Big Data in Healthcare and Stroke. Rehabilitation Science, 1(1), 16-24. https://doi.org/10.11648/j.rs.20160101.13

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ACS Style

Lidong Wang; Cheryl Ann Alexander. Stroke Care and the Role of Big Data in Healthcare and Stroke. Rehabil. Sci. 2016, 1(1), 16-24. doi: 10.11648/j.rs.20160101.13

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AMA Style

Lidong Wang, Cheryl Ann Alexander. Stroke Care and the Role of Big Data in Healthcare and Stroke. Rehabil Sci. 2016;1(1):16-24. doi: 10.11648/j.rs.20160101.13

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@article{10.11648/j.rs.20160101.13,
  author = {Lidong Wang and Cheryl Ann Alexander},
  title = {Stroke Care and the Role of Big Data in Healthcare and Stroke},
  journal = {Rehabilitation Science},
  volume = {1},
  number = {1},
  pages = {16-24},
  doi = {10.11648/j.rs.20160101.13},
  url = {https://doi.org/10.11648/j.rs.20160101.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.rs.20160101.13},
  abstract = {Theoretically current electronic health data can now be securely linked on an unprecedented scale, potentially illuminating how diseases manifest and which treatments are best applied in the real world. Increasing volumes of information on real-time, actual patient experiences are now contained on social media and patient portal websites. Innovations and insight into the health care for individuals and entire populations can be gained when information from health monitors, genomic data, and clinical trial data is merged. In other words, we now have the theoretical technology to accumulate, store, convert, access, and evaluate massive amounts of data at a modest cost. Performance and clinical data from health care facilities, including clinics and hospitals, clinical research data by industry, and academic data from patient populations and the general public which may be generated through social media and/or other sources is included in big data. Just as access to sizable datasets evolves and becomes easier, analytical mistakes may occur more often and be easier to make lest rigorous standards and governance controls are employed. Indeed, it is more likely that improved analytics will also introduce us to at least a few more uncomfortable insights into the negligible value of some medicines. It is also noteworthy to mention that one common error is the assumption that the value of big data is within the data itself—its volume, accuracy, accessibility, “linkability,” etc. Unfortunately, despite the importance of the information, or the “bigger” the data, the greater the likelihood that this does not hold true. This review paper examines the relationship of big data to stroke care in a variety of stroke-related issues including: big data in stroke care, big data and visual analytics, big data in telecardiology, and some challenges and indications for future research.},
 year = {2016}
}

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TY  - JOUR
T1  - Stroke Care and the Role of Big Data in Healthcare and Stroke
AU  - Lidong Wang
AU  - Cheryl Ann Alexander
Y1  - 2016/11/25
PY  - 2016
N1  - https://doi.org/10.11648/j.rs.20160101.13
DO  - 10.11648/j.rs.20160101.13
T2  - Rehabilitation Science
JF  - Rehabilitation Science
JO  - Rehabilitation Science
SP  - 16
EP  - 24
PB  - Science Publishing Group
SN  - 2637-594X
UR  - https://doi.org/10.11648/j.rs.20160101.13
AB  - Theoretically current electronic health data can now be securely linked on an unprecedented scale, potentially illuminating how diseases manifest and which treatments are best applied in the real world. Increasing volumes of information on real-time, actual patient experiences are now contained on social media and patient portal websites. Innovations and insight into the health care for individuals and entire populations can be gained when information from health monitors, genomic data, and clinical trial data is merged. In other words, we now have the theoretical technology to accumulate, store, convert, access, and evaluate massive amounts of data at a modest cost. Performance and clinical data from health care facilities, including clinics and hospitals, clinical research data by industry, and academic data from patient populations and the general public which may be generated through social media and/or other sources is included in big data. Just as access to sizable datasets evolves and becomes easier, analytical mistakes may occur more often and be easier to make lest rigorous standards and governance controls are employed. Indeed, it is more likely that improved analytics will also introduce us to at least a few more uncomfortable insights into the negligible value of some medicines. It is also noteworthy to mention that one common error is the assumption that the value of big data is within the data itself—its volume, accuracy, accessibility, “linkability,” etc. Unfortunately, despite the importance of the information, or the “bigger” the data, the greater the likelihood that this does not hold true. This review paper examines the relationship of big data to stroke care in a variety of stroke-related issues including: big data in stroke care, big data and visual analytics, big data in telecardiology, and some challenges and indications for future research.
VL  - 1
IS  - 1
ER  -

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Author Information

Lidong Wang

Department of Engineering Technology, Mississippi Valley State University, Itta Bena, USA
Cheryl Ann Alexander

Technology and Healthcare Solutions, Incorporated, Itta Bena, USA

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Plain Text BibTeX RIS

APA Style

Lidong Wang, Cheryl Ann Alexander. (2016). Stroke Care and the Role of Big Data in Healthcare and Stroke. Rehabilitation Science, 1(1), 16-24. https://doi.org/10.11648/j.rs.20160101.13

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ACS Style

Lidong Wang; Cheryl Ann Alexander. Stroke Care and the Role of Big Data in Healthcare and Stroke. Rehabil. Sci. 2016, 1(1), 16-24. doi: 10.11648/j.rs.20160101.13

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AMA Style

Lidong Wang, Cheryl Ann Alexander. Stroke Care and the Role of Big Data in Healthcare and Stroke. Rehabil Sci. 2016;1(1):16-24. doi: 10.11648/j.rs.20160101.13

Copy | Download

@article{10.11648/j.rs.20160101.13,
  author = {Lidong Wang and Cheryl Ann Alexander},
  title = {Stroke Care and the Role of Big Data in Healthcare and Stroke},
  journal = {Rehabilitation Science},
  volume = {1},
  number = {1},
  pages = {16-24},
  doi = {10.11648/j.rs.20160101.13},
  url = {https://doi.org/10.11648/j.rs.20160101.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.rs.20160101.13},
  abstract = {Theoretically current electronic health data can now be securely linked on an unprecedented scale, potentially illuminating how diseases manifest and which treatments are best applied in the real world. Increasing volumes of information on real-time, actual patient experiences are now contained on social media and patient portal websites. Innovations and insight into the health care for individuals and entire populations can be gained when information from health monitors, genomic data, and clinical trial data is merged. In other words, we now have the theoretical technology to accumulate, store, convert, access, and evaluate massive amounts of data at a modest cost. Performance and clinical data from health care facilities, including clinics and hospitals, clinical research data by industry, and academic data from patient populations and the general public which may be generated through social media and/or other sources is included in big data. Just as access to sizable datasets evolves and becomes easier, analytical mistakes may occur more often and be easier to make lest rigorous standards and governance controls are employed. Indeed, it is more likely that improved analytics will also introduce us to at least a few more uncomfortable insights into the negligible value of some medicines. It is also noteworthy to mention that one common error is the assumption that the value of big data is within the data itself—its volume, accuracy, accessibility, “linkability,” etc. Unfortunately, despite the importance of the information, or the “bigger” the data, the greater the likelihood that this does not hold true. This review paper examines the relationship of big data to stroke care in a variety of stroke-related issues including: big data in stroke care, big data and visual analytics, big data in telecardiology, and some challenges and indications for future research.},
 year = {2016}
}

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TY  - JOUR
T1  - Stroke Care and the Role of Big Data in Healthcare and Stroke
AU  - Lidong Wang
AU  - Cheryl Ann Alexander
Y1  - 2016/11/25
PY  - 2016
N1  - https://doi.org/10.11648/j.rs.20160101.13
DO  - 10.11648/j.rs.20160101.13
T2  - Rehabilitation Science
JF  - Rehabilitation Science
JO  - Rehabilitation Science
SP  - 16
EP  - 24
PB  - Science Publishing Group
SN  - 2637-594X
UR  - https://doi.org/10.11648/j.rs.20160101.13
AB  - Theoretically current electronic health data can now be securely linked on an unprecedented scale, potentially illuminating how diseases manifest and which treatments are best applied in the real world. Increasing volumes of information on real-time, actual patient experiences are now contained on social media and patient portal websites. Innovations and insight into the health care for individuals and entire populations can be gained when information from health monitors, genomic data, and clinical trial data is merged. In other words, we now have the theoretical technology to accumulate, store, convert, access, and evaluate massive amounts of data at a modest cost. Performance and clinical data from health care facilities, including clinics and hospitals, clinical research data by industry, and academic data from patient populations and the general public which may be generated through social media and/or other sources is included in big data. Just as access to sizable datasets evolves and becomes easier, analytical mistakes may occur more often and be easier to make lest rigorous standards and governance controls are employed. Indeed, it is more likely that improved analytics will also introduce us to at least a few more uncomfortable insights into the negligible value of some medicines. It is also noteworthy to mention that one common error is the assumption that the value of big data is within the data itself—its volume, accuracy, accessibility, “linkability,” etc. Unfortunately, despite the importance of the information, or the “bigger” the data, the greater the likelihood that this does not hold true. This review paper examines the relationship of big data to stroke care in a variety of stroke-related issues including: big data in stroke care, big data and visual analytics, big data in telecardiology, and some challenges and indications for future research.
VL  - 1
IS  - 1
ER  -

Copy | Download