Towards a blockchain based fall prediction model for aged care

Tharuka Rupasinghe, Frada Burstein, Carsten Rudolph, Steven Strange

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

Falls are one of the major health concerns for the elderly people. These falls often result in severe injuries which lead into huge medical expenses. Over the recent years, many ICT based fall detection and fall prevention solutions emerged to address the risk factors associated with falls. However, despite of these research studies, predicting the likelihood of falls still remains as a huge challenge in both medical and IT research domains. Data related to these risk factors being scattered among different healthcare providers can be attributed as a main reason for this challenge. This is further amplified by healthcare providers being reluctant to disseminate the data beyond their entities due to the security and privacy concerns. However, in recent years, blockchain has been proven as a promising technology to address the security and privacy challenges in healthcare data exchange as it provides a shared, immutable, and transparent audit trail for accessing data. Therefore, in this paper, we are going to propose a conceptual blockchain based fall prediction model leveraging smart contracts and FHIR (Fast Healthcare Interoperability Resources) standard to identify the elderly people who are at a higher risk of falling.

Original languageEnglish
Title of host publicationACSW'19 - Proceedings of the Australasian Computer Science Week Multiconference
Subtitle of host publicationSydney, NSW, Australia — January 29 - 31, 2019
EditorsYing Wang, Dale Patterson
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Number of pages10
ISBN (Electronic)9781450366038
DOIs
Publication statusPublished - 2019
EventAustralasian Computer Science Week Multiconference 2019 - Sydney, Australia
Duration: 29 Jan 201931 Jan 2019
http://www.acsw.org.au/

Conference

ConferenceAustralasian Computer Science Week Multiconference 2019
Abbreviated titleACSW 2019
CountryAustralia
CitySydney
Period29/01/1931/01/19
Internet address

Keywords

  • Blockchain Technology
  • Fall Prediction
  • Healthcare
  • Smart Contracts

Cite this

Rupasinghe, T., Burstein, F., Rudolph, C., & Strange, S. (2019). Towards a blockchain based fall prediction model for aged care. In Y. Wang, & D. Patterson (Eds.), ACSW'19 - Proceedings of the Australasian Computer Science Week Multiconference: Sydney, NSW, Australia — January 29 - 31, 2019 [32] New York NY USA: Association for Computing Machinery (ACM). https://doi.org/10.1145/3290688.3290736
Rupasinghe, Tharuka ; Burstein, Frada ; Rudolph, Carsten ; Strange, Steven. / Towards a blockchain based fall prediction model for aged care. ACSW'19 - Proceedings of the Australasian Computer Science Week Multiconference: Sydney, NSW, Australia — January 29 - 31, 2019. editor / Ying Wang ; Dale Patterson. New York NY USA : Association for Computing Machinery (ACM), 2019.
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abstract = "Falls are one of the major health concerns for the elderly people. These falls often result in severe injuries which lead into huge medical expenses. Over the recent years, many ICT based fall detection and fall prevention solutions emerged to address the risk factors associated with falls. However, despite of these research studies, predicting the likelihood of falls still remains as a huge challenge in both medical and IT research domains. Data related to these risk factors being scattered among different healthcare providers can be attributed as a main reason for this challenge. This is further amplified by healthcare providers being reluctant to disseminate the data beyond their entities due to the security and privacy concerns. However, in recent years, blockchain has been proven as a promising technology to address the security and privacy challenges in healthcare data exchange as it provides a shared, immutable, and transparent audit trail for accessing data. Therefore, in this paper, we are going to propose a conceptual blockchain based fall prediction model leveraging smart contracts and FHIR (Fast Healthcare Interoperability Resources) standard to identify the elderly people who are at a higher risk of falling.",
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Rupasinghe, T, Burstein, F, Rudolph, C & Strange, S 2019, Towards a blockchain based fall prediction model for aged care. in Y Wang & D Patterson (eds), ACSW'19 - Proceedings of the Australasian Computer Science Week Multiconference: Sydney, NSW, Australia — January 29 - 31, 2019., 32, Association for Computing Machinery (ACM), New York NY USA, Australasian Computer Science Week Multiconference 2019, Sydney, Australia, 29/01/19. https://doi.org/10.1145/3290688.3290736

Towards a blockchain based fall prediction model for aged care. / Rupasinghe, Tharuka; Burstein, Frada; Rudolph, Carsten; Strange, Steven.

ACSW'19 - Proceedings of the Australasian Computer Science Week Multiconference: Sydney, NSW, Australia — January 29 - 31, 2019. ed. / Ying Wang; Dale Patterson. New York NY USA : Association for Computing Machinery (ACM), 2019. 32.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

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N2 - Falls are one of the major health concerns for the elderly people. These falls often result in severe injuries which lead into huge medical expenses. Over the recent years, many ICT based fall detection and fall prevention solutions emerged to address the risk factors associated with falls. However, despite of these research studies, predicting the likelihood of falls still remains as a huge challenge in both medical and IT research domains. Data related to these risk factors being scattered among different healthcare providers can be attributed as a main reason for this challenge. This is further amplified by healthcare providers being reluctant to disseminate the data beyond their entities due to the security and privacy concerns. However, in recent years, blockchain has been proven as a promising technology to address the security and privacy challenges in healthcare data exchange as it provides a shared, immutable, and transparent audit trail for accessing data. Therefore, in this paper, we are going to propose a conceptual blockchain based fall prediction model leveraging smart contracts and FHIR (Fast Healthcare Interoperability Resources) standard to identify the elderly people who are at a higher risk of falling.

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Rupasinghe T, Burstein F, Rudolph C, Strange S. Towards a blockchain based fall prediction model for aged care. In Wang Y, Patterson D, editors, ACSW'19 - Proceedings of the Australasian Computer Science Week Multiconference: Sydney, NSW, Australia — January 29 - 31, 2019. New York NY USA: Association for Computing Machinery (ACM). 2019. 32 https://doi.org/10.1145/3290688.3290736