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Blockchain-Supported Health Registry: The Claim for a Personal Health Trajectory Traceability and How It Can Be Achieved

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Gerontechnology IV (IWoG 2021)

Abstract

The digitalization of health processes is a reality. Each time, there are more services and institutions generating and interacting with the health data of a patient. This put in manifest some deficiencies of actual health systems, such as the need for data no longer revolve around the institutions that generate them and start to revolve around the users or patients to whom they belong. Otherwise, patients will end up losing focus and control of their data, which is distributed among different information systems. To address this, many researchers around the world have proposed software solutions that integrate a patient’s data into a global view, even though it is still stored in a distributed way in the systems that generate it. However, the mere integration of data does not allow a patient to have real knowledge of the entire life cycle of her different records. To this end, data integration solutions must go a step further and convert the structure that maintains the overall view of a patient’s health, her Personal Health Trajectory, into a registry ensuring the traceability of the patient’s health. As a result, patients will have a real understanding of everything that surrounds their health data and true patient-centered healthcare systems will be one step closer.

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References

  1. Chen, L., Lee, W.K., Chang, C.C., Choo, K.K.R., Zhang, N.: Blockchain based searchable encryption for electronic health record sharing. Future Gener. Comput. Syst. 95, 420–429 (2019). https://doi.org/10.1016/J.FUTURE.2019.01.018

    Article  Google Scholar 

  2. Dubovitskaya, A., et al.: Intelligent health care data management using blockchain: current limitation and future research agenda. In: Gadepally, V., et al. (eds.) DMAH/Poly - 2019. LNCS, vol. 11721, pp. 277–288. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-33752-0_20

    Chapter  Google Scholar 

  3. Feng, H., Wang, X., Duan, Y., Zhang, J., Zhang, X.: Applying blockchain technology to improve agri-food traceability: a review of development methods, benefits and challenges. J. Clean. Prod. 260, 121031 (2020)

    Google Scholar 

  4. Flores-Martin, D., Rojo, J., Moguel, E., Berrocal, J., Murillo, J.M.: Smart nursing homes: self-management architecture based on iot and machine learning for rural areas. Wirel. Communi. Mob. Comput. 2021 (2021)

    Google Scholar 

  5. Galvez, J.F., Mejuto, J.C., Simal-Gandara, J.: Future challenges on the use of blockchain for food traceability analysis. TrAC Trends Anal. Chem. 107, 222–232 (2018)

    Article  Google Scholar 

  6. Gatouillat, A., Badr, Y., Massot, B., Sejdic, E.: Internet of medical things: a review of recent contributions dealing with cyber-physical systems in medicine. IEEE Internet Things J. 5(5), 3810–3822 (2018). https://doi.org/10.1109/JIOT.2018.2849014

    Article  Google Scholar 

  7. Gong, J., Lin, S., Li, J.: Research on personal health data provenance and right confirmation with smart contract. In: 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), vol. 1, pp. 1211–1216. IEEE (2019)

    Google Scholar 

  8. Helal, S., Jain, R.: Digital health-active and healthy living. Computer 52(11), 14–17 (2019)

    Article  Google Scholar 

  9. Henly, S.J., Wyman, J.F., Gaugler, J.E.: Health trajectory research: a call to action for nursing science. Nurs. Res. 60(3 SUPPL.) (2011). https://doi.org/10.1097/NNR.0b013e31821cc240

  10. Jalali, L., Huo, D., Oh, H., Tang, M., Pongpaichet, S., Jain, R.: Personicle: personal chronicle of life events. In: Workshop on Personal Data Analytics in the Internet of Things (PDA@ IOT) at the 40th International Conference on Very Large Databases (VLDB), Hangzhou, China (2014)

    Google Scholar 

  11. Kalra, D.: Electronic health record standards (2006)

    Google Scholar 

  12. Kassab, M., Defranco, J., Malas, T., Graciano Neto, V.V., Destefanis, G.: Blockchain: a panacea for electronic health records? In: Proceedings - 2019 IEEE/ACM 1st International Workshop on Software Engineering for Healthcare, SEH 2019, pp. 21–24. Institute of Electrical and Electronics Engineers Inc., May 2019

    Google Scholar 

  13. Kyazze, M., Wesson, J., Naude, K.: The design and implementation of a ubiquitous personal health record system for South Africa. Stud. Health Technol. Inform. 206, 29 (2014)

    Google Scholar 

  14. Li, H., Zhu, L., Shen, M., Gao, F., Tao, X., Liu, S.: Blockchain-based data preservation system for medical data. J. Med. Syst. 42(8), 1–13 (2018). https://doi.org/10.1007/S10916-018-0997-3

    Article  Google Scholar 

  15. Philip, N., et al.: Design of a restful middleware to enable a web of medical things. In: 2014 MOBIHEALTH, pp. 361–364, November 2014. https://doi.org/10.1109/MOBIHEALTH.2014.7015986

  16. Roehrs, A., Da Costa, C.A., da Rosa Righi, R., De Oliveira, K.S.F.: Personal health records: a systematic literature review. J. Med. Internet Res. 19(1), e13 (2017). https://doi.org/10.2196/jmir.5876, http://www.jmir.org/2017/1/e13/

  17. Roehrs, A., da Costa, C.A., da Rosa Righi, R.: OmniPHR: a distributed architecture model to integrate personal health records. J. Biomed. Inform. 71, 70–81 (2017). https://doi.org/10.1016/j.jbi.2017.05.012

    Article  Google Scholar 

  18. Rojo, J., Hernandez, J., Murillo, J.M., Garcia-Alonso, J.: Blockchains’ federation for integrating distributed health data using a patient-centered approach. In: 2021 IEEE/ACM 3rd International Workshop on Software Engineering for Healthcare (SEH), vol. 1, pp. 52–59. IEEE Computer Society, Los Alamitos, June 2021. https://doi.org/10.1109/SEH52539.2021.00016, https://doi.ieeecomputersociety.org/10.1109/SEH52539.2021.00016

  19. Rojo, J., Flores-Martin, D., Garcia-Alonso, J., Murillo, J.M., Berrocal, J.: Automating the interactions among IoT devices using neural networks. In: 2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), pp. 1–6. IEEE (2020)

    Google Scholar 

  20. Rojo, J., Hernandez, J., Murillo, J.M.: A personal health trajectory API: addressing problems in health institution-oriented systems. In: Bielikova, M., Mikkonen, T., Pautasso, C. (eds.) ICWE 2020. LNCS, vol. 12128, pp. 519–524. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-50578-3_37

    Chapter  Google Scholar 

  21. Rojo, J., Moguel, E., Fonseca, C., Lopes, M., Garcia-Alonso, J., Hernandez, J.: Time series forecasting to predict the evolution of the functional profile of the elderly persons. In: García-Alonso, J., Fonseca, C. (eds.) IWoG 2020. LNB, pp. 11–22. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-72567-9_2

    Chapter  Google Scholar 

  22. Helou, S., Abou-Khalil, V., El Helou, E., Kiyono, K.: Factors related to personal health data sharing: data usefulness, sensitivity and anonymity. Stud. Health Technol. Inform. 281, 1051–1055 (2021). https://doi.org/10.3233/SHTI210345, https://pubmed.ncbi.nlm.nih.gov/34042839/

  23. Spil, T., Klein, R.: Personal health records success; why google health failed and what does that mean for Microsoft HealthVault? In: Proceedings of the Annual Hawaii International Conference on System Sciences, pp. 2818–2827. IEEE Computer Society (2014). https://doi.org/10.1109/HICSS.2014.353

  24. Zhang, Y., Qiu, M., Tsai, C.W., Hassan, M., Alamri, A.: Health-CPS: healthcare cyber-physical system assisted by cloud and big data. IEEE Syst. J. 11, 1–8 (2015). https://doi.org/10.1109/JSYST.2015.2460747

    Article  Google Scholar 

  25. Zhang, Y., Li, J., Zheng, D., Chen, X., Li, H.: Towards privacy protection and malicious behavior traceability in smart health. Pers. Ubiquit. Comput. 21(5), 815–830 (2017). https://doi.org/10.1007/s00779-017-1047-8

    Article  Google Scholar 

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Acknowledgements

This work was supported by the projects 0499_4IE_PLUS_4_E (Interreg V-A España-Portugal 2014-2020) and RTI2018-094591-B-I00 (MCIU/AEI/FEDER, UE), the FPU19/03965 grant, the Department of Economy and Infrastructure of the Government of Extremadura (GR18112, IB18030), and the European Regional Development Fund.

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Correspondence to Javier Rojo .

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Rojo, J., Hernández, J., Helal, S., Murillo, J.M., García-Alonso, J. (2022). Blockchain-Supported Health Registry: The Claim for a Personal Health Trajectory Traceability and How It Can Be Achieved. In: García-Alonso, J., Fonseca, C. (eds) Gerontechnology IV. IWoG 2021. Lecture Notes in Bioengineering. Springer, Cham. https://doi.org/10.1007/978-3-030-97524-1_3

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  • DOI: https://doi.org/10.1007/978-3-030-97524-1_3

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