Data provenance and blockchain: An approach in the context of health information systems
DOI:
https://doi.org/10.47909/978-9916-9331-4-5.111Keywords:
data provenance, blockchain, health information systems, electronic health record, personal health recordAbstract
The integration of data provenance and blockchain, in accordance with international health standards, was demonstrated to enhance patient data management through seamless integration with health information systems (HIS). This study built upon the findings of previous research conducted by the same authors, with the objective of conducting a more comprehensive and in-depth analysis. In terms of methodology, this research was a basic study characterized as a bibliographical and exploratory investigation with a qualitative approach. The analyses carried out, based on related work, focused on the relationships between the main applications of data provenance in conjunction with the intrinsic characteristics of blockchain technology. These aspects were examined in the context of HIS, which made it possible to identify the international data interoperability standards specifically adopted in electronic health records (EHRs) and personal health records (PHRs). The primary outcomes of this study included the identification of the relationships between the primary applications of data provenance and the characteristics of blockchain, with a particular focus on HIS. Additionally, the analysis of the literature on data provenance and blockchain technology led to the recognition of the main interoperability standards. This culminated in a reflective synthesis of the findings. A comprehensive analysis of the results, grounded in the identified fundamental elements, yielded significant insights into the integration of data provenance and blockchain technology within the HIS, particularly in the context of EHR and PHR.
Downloads
References
Al Jarullah, A., & El-Masri, S. (2012). Proposal of an architecture for the national integration of electronic health records: A semi-centralized approach. Studies in Health Technology and Informatics, 180, 917–921. https://doi.org/10.3233/978-1-61499-101-4-917
Allen, M. (2017). Bibliographic research. In The SAGE Encyclopedia of communication research methods. SAGE Publications. https://doi.org/10.4135/9781483381411.n37
Alvarez, S., Vazquez-Salceda, J., Kifor, T., Varga, L. Z., & Willmott, S. (2006). Applying provenance in distributed organ transplant management. In Provenance and annotation of data: International provenance and annotation workshop, IPAW 2006, Chicago, IL, USA, May 3–5, Revised Selected Papers (pp. 28–36). Springer Berlin Heidelberg. https://doi.org/10.1007/11890850_4
Andargolia, A. E., Scheepers, H., Rajendran, D., & Sohal, A. (2017). Health information systems evaluation frameworks: A systematic review. International Journal of Medical Informatics, 97, 195–209. https://doi.org/ 10.1016/j.ijmedinf.2016.10.008
Annas, G. J. (2003). HIPAA regulations: A new era of medical-record privacy? New England Journal of Medicine, 348(15), 1486. https://doi.org/10.1056/NEJMlim035027
Bakker, A. R. (1991). HIS, RIS, and PACS. Computerized Medical Imaging and Graphics, 15(3), 157–160. https://doi.org/10.1016/0895-6111(91)90004-F
Bansal, S. K. (2014). Towards a semantic extract-transform-load (ETL) framework for big data integration. In 2014 IEEE international congress on big data (pp. 522–529). IEEE. http://10.1109/BigData.Congress.2014.82
Bell, L., Buchanan, W. J., Cameron, J., & Lo, O. (2018). Applications of blockchain within healthcare. Blockchain in Healthcare Today, 1, 1–7. https://doi.org/10.30953/bhty.v1.8
Bernardini, A., Alonzi, M., Campioni, P., Vecchioli, A., & Marano, P. (2003). IHE: Integrating the Healthcare Enterprise, towards complete integration of healthcare information systems. Rays, 28(1), 83–93. https://pubmed.ncbi.nlm.nih.gov/14509182/
Blick, K. E. (1997). Decision-making laboratory computer systems as essential tools for achievement of total quality. Clinical Chemistry, 43(5), 908–912. https://doi.org/10.1093/clinchem/43.5.908
Boochever, S. S. (2004). HIS/RIS/PACS integration: Getting to the gold standard. Radiology Management, 26(3), 16–24. https://pubmed.ncbi.nlm.nih.gov/15259683/
Buneman, P., Khanna, S., & Wang-Chiew, T. (2001). Why and where: A characterization of data provenance. In J. Van den Bussche & V. Vianu (Eds.), ICDT 2001: International conference on database theory (pp. 316–330). Springer. https://doi.org/10.1007/3-540-44503-X_20
Cameron, G. (2003). Provenance and pragmatics [Workshop on Data Provenance and Annotation]. Edinburgh, UK.
Cesnik, B., & Kidd, M. R. (2010). History of health informatics: A global perspective. Studies in Health Technology and Informatics, 151, 3–8. https://doi.org/10.3233/978-1-60750-476-4-3
Coimbra, F. S., & Dias, T. M. R. (2021). Use of open data to analyze the publication of articles in scientific events. Iberoamerican Journal of Science Measurement and Communication, 1(3), 1–13. https://doi.org/10.47909/ijsmc.123
Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: Management, analysis and future prospects. Journal of Big Data, 6(1), 1–25. https://doi.org/10.1186/s40537-019-0217-0
Dehnavieh, R., Haghdoost, A., Khosravi, A., Hoseinabadi, F., Rahimi, H., Poursheikhali, A., Shafiee, G., Gholami, H., Abadi, M. B. H., Noori, R., & Mehrolhassani, M. H. (2018). The District Health Information System (DHIS2): A literature review and meta-synthesis of its strengths and operational challenges based on the experiences of 11 countries. Health Information Management Journal, 48(2), 62–75. https://doi.org/10.1177/1833358318777713
Deloitte. (2018). Breaking blockchain open: Deloitte’s 2018 global blockchain survey (Report No. 48). Deloitte Insights. https://doi.org/10.1002/ejoc.201200111
Dolin, R. H., Alschuler, L., Beebe, C., Biron, P. V., Boyer, S. L., Essin, D., & Mattison, J. E. (2001). The HL7 clinical document architecture. Journal of the American Medical Informatics Association, 8(6), 552–569. https://doi.org/10.1136/jamia.2001.0080552
Engelhardt, M. A. (2017). Hitching healthcare to the chain: An introduction to blockchain technology in the healthcare sector. Technology Innovation Management Review, 7(10), 22–34. http://doi.org/10.22215/timreview/1111
Foster, I. T., Vöckler, J.-S., Wilde, M., & Zhao, Y. (2003). The virtual data grid: A new model and architecture for data-intensive collaboration. In 15th International conference on scientific and statistical database management (SSDBM), Cambridge, MA, USA. https://www.cidrdb.org/cidr2003/program/p18.pdf
Freire, J., Silva, C. T., Callahan, S. P., Santos, E., Scheidegger, C. E., & Vo, H. T. (2008). Provenance for computational tasks: A survey. Journal of Computing Science and Engineering, 10(3), 11–21. https://doi.org/10.1109/MCSE.2008.79
Friedman, C., Rubin, J., Brown, J., Buntin, M., Corn, M., Etheredge, L., Gunter, C., Musen, M., Platt, R., Stead, W., Sullivan, K., & Van Houweling, D. (2015). Toward a science of learning systems: A research agenda for the high-functioning learning health system. Journal of the American Medical Informatics Association, 22(1), 43–50. https://doi.org/10.1136/amiajnl-2014-002977
Galhardas, H., Florescu, D., Shasha, D., Simon, E., & Saita, C. A. (2001). Improving data cleaning quality using a data lineage facility. In Proceedings of the international workshop on design and management of data warehouses (DMDW), Interlaken, Switzerland (pp. 1–13). http://ceur-ws.org/Vol-39/paper3.pdf
Gil, Y., & Miles, S. (2013). PROV model primer [W3C Working Draft]. W3C. https://www.w3.org/TR/prov-primer/
Goble, C. (2002). Position statement: Musings on provenance, workflow and (Semantic Web) annotations for bioinformatics [Workshop on Data Derivation and Provenance]. Chicago, IL, USA.
Gong, J., Lin, S., & Li, J. (2019). Research on personal health data provenance and right confirmation with smart contract. In IEEE 4th advanced information technology, electronic and automation control conference (IAEAC). https://doi.org/10.1109/IAEAC47372.2019.8997930
Gontijo, M. C. A., Hamanaka, R. Y., & de Araujo, R. F. (2021). Research data management: A bibliometric and altmetric study based on Dimensions. Iberoamerican Journal of Science Measurement and Communication, 1(3), 1–19. https://doi.org/10.47909/ijsmc.120
Greenspan, G. (2016). Four genuine blockchain use cases [Technical report]. MultiChain. https://www.multichain.com/blog/2016/05
Greenwood, M., Goble, C., Stevens, R., Zhao, J., Addis, M., Marvin, D., Moreau, L., & Oinn, T. (2003). Provenance of e-science experiments: Experience from bioinformatics. In Proceedings of the UK OST e-science second all hands meeting, Nottingham, UK. https://eprints.soton.ac.uk/258895/1/prov-all-hands.pdf
Griggs, K. N., Ossipova, O., Kohlios, C. P., Baccarini, A. N., Howson, E. A., & Hayajneh, T. (2018). Healthcare blockchain system using smart contracts for secure automated remote patient monitoring. Journal of Medical Systems, 42(7), 130. https://doi.org/10.1007/s10916-018-0982-x
Gropper, A. (2016). Powering the physician-patient relationship with HIE of one blockchain health IT [ONC/NIST Use of Blockchain for Healthcare and Research Workshop]. Gaithersburg, MD. https://www.healthit.gov/sites/default/files/7-29-poweringthephysician-patientrelationshipwithblockchainhealthit.pdf
Groth, P., & Moreau, L. (2013). PROV-overview: An overview of the PROV family of documents. W3C. https://www.w3.org/TR/prov-overview/
Hallingberg, B., Turley, R., Segrott, J., Wight, D., Craig, P., Moore, L., Murphy, S., Robling. M., Simpson, S. A., & Moore, G. (2018). Exploratory studies to decide whether and how to proceed with full-scale evaluations of public health interventions: A systematic review of guidance. Pilot and Feasibility Studies, 4, 104. https://doi.org/10.1186/s40814-018-0290-8
Hasselgren, A., Kralevska, K., Gligoroski, D., Pedersen, S. A., & Faxvaag, A. (2020). Blockchain in healthcare and health sciences: A scoping review. International Journal of Medical Informatics, 134, Article 104040. https://doi.org/10.1016/j.ijmedinf.2019.104040
Haux, R. (2006). Health information systems—Past, present, future. International Journal of Medical Informatics, 75(3–4), 268–281. https://doi.org/10.1016/j.ijmedinf.2005.08.002
HL7 International. (n.d.). Fast healthcare interoperability resources release (STU). http://fhir.hl7.org
Hoerbst, A., & Ammenwerth, E. (2010). Electronic health records. Methods of Information in Medicine, 49(4), 320–336. https://doi.org/10.3414/me10-01-0038
Honeyman, J. C. (1999). Information systems integration in radiology. Journal of Digital Imaging, 12(Suppl 1), 218–219. http://doi: 10.1007/BF03168810
Huang, H. K. (2019). PACS-based multimedia imaging informatics: Basic principles and applications (3rd ed.). John Wiley & Sons. https://doi.org/10.2345/i0899-8205-40-2-125.1
Ismail, A., Jamil, A. T., Rahman, A. F. A., Bakar, J. M. A., Saad, N. M., & Saadi, H. (2010). The implementation of Hospital Information System (HIS) in tertiary hospitals in Malaysia: A qualitative study. Malaysian Journal of Public Health Medicine, 10(2), 16–24.
Jagadish, H. V., & Olken, F. (2004). Database management for life sciences research. ACM SIGMOD Record, 33(2), 15–20. https://doi.org/10.1145/1024694.1024697
Kho, W. (2018). Blockchain revolution in healthcare: The era of patient-centred dental information system. International Journal of Oral Biology, 43(1), 1–3. https://doi.org/10.11620/IJOB.2018.43.1.001
Kohlbacher, O., Mansmann, U., Bauer, B., Kuhn, K., & Prasser, F. (2018). Data Integration for Future Medicine (DIFUTURE): An architectural and methodological overview. Methods of Information in Medicine, 57(S01), e43–e50. https://doi.org/10.3414/ME17-02-0022
Korhonen, I., Pärkkä, J., & van Gils, M. (2003). Health monitoring in the home of the future. IEEE Engineering in Medicine and Biology Magazine, 22(3), 66–73. https://doi.org/10.1109/MEMB.2003.1213628
Law, M. Y., & Zhou, Z. (2003). New direction in PACS education and training. Computerized Medical Imaging and Graphics, 27(2–3), 147–156. https://doi.org/10.1016/S0895-6111(02)00088-5
Leeming, G., Ainsworth, J., & Clifton, D. A. (2019). Blockchain in health care: Hype, trust, and digital health. The Lancet, 393(10190), 2476–2477. https://doi.org/10.1016/S0140-6736(19)30948-1
Li, Q., Labrinidis, A., & Chrysanthis, P. K. (2008). User-centric annotation management for biological data. In Provenance and annotation of data and processes: second international provenance and annotation workshop, IPAW 2008, Salt Lake City, UT, USA, June 17–18, Revised Selected Papers (pp. 54–61). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-89965-5_7
Liang, X., Zhao, J., Shetty, S., Liu, J., & Li, D. (2017). Integrating blockchain for data sharing and collaboration in mobile healthcare applications. In 2017 IEEE 28th annual international symposium on personal, indoor, and mobile radio communications (PIMRC), Montreal, QC, Canada (pp. 1–25). IEEE. https://doi.org/10.1109/PIMRC.2017.8292361
Liu, L. S., Shih, P. C., & Hayes, G. (2011). Barriers to the adoption and use of personal health record systems. Proceedings of the iConference, 363–370. https://doi.org/10.1145/1940761.1940811
Macedo, D. D. J., de Von Wangenheim, A., & de Dantas, M. A. R. (2015). A data storage approach for large-scale distributed medical systems. In 2015 Ninth international conference on complex, intelligent, and software intensive systems (pp. 486–490). https://doi.org/10.1109/CISIS.2015.88
Macedo, D. D., de Araújo, G. M., de Dutra, M. L., Dutra, S. T., & Lezana, Á. G. (2019). Toward an efficient healthcare Cloud IoT architecture by using a game theory approach. Concurrent Engineering, 27(3), 189–200. https://doi.org/10.1177/1063293X19844548
Margheri, A., Massi, M., Miladi, A., Sassone, V., & Rosenzweig, A. J. (2020). Decentralised provenance for healthcare data. International Journal of Medical Informatics, 141, Article 104197. https://doi.org/10.1016/j.ijmedinf.2020.104197
Massi, M., Miladi, A., Margheri, A., Sassone, V., & Rosenzweig, J. (2018). Using PROV and blockchain to achieve health data provenance [Technical Report]. University of Southampton. https://eprints.soton.ac.uk/421292/1/PROV_BC_Healthcare.pdf
McCusker, K., & Gunaydin, S. (2015). Research using qualitative, quantitative or mixed methods and choice based on the research. Perfusion, 30(7), 537–542. https://doi.org/10.1177/0267659114559116
Mildenberger, P., Eichelberg, M., & Martin, E. (2002). Introduction to the DICOM standard. European Radiology, 12(4), 920–927. http://doi: 10.1007/s003300101100
Miles, S., Groth, P., Branco, M., & Moreau, L. (2005). The requirements of recording and using provenance in eScience experiments [Technical Report]. Electronics and Computer Science, University of Southampton, UK. https://eprints.soton.ac.uk/260269/1/pasoa04requirements.pdf
Monteil, C. (2019). Blockchain and health. In Digital medicine (pp. 41–47). Springer. https://doi.org/10.1007/978-3-319-98216-8_4
Moreau, L. (2006). Usage of “provenance”: A tower of Babel [Position paper]. Microsoft Life Cycle Seminar, Mountain View, CA. https://eprints.soton.ac.uk/409382/
Moreau, L., Clifford, B., Freire, J., Futrelle, J., Gil, Y., Groth, P., & Van den Bussche, J. (2011). The open provenance model core specification (v1.1). Future Generation Computer Systems, 27(6), 743–756. https://doi.org/10.1016/j.future.2010.07.005
Moreau, L., & Groth, P. (2013). Provenance: An introduction to PROV. Morgan & Claypool. https://doi.org/10.2200/s00528ed1v01y201308wbe007
Moreau, L., Kwasnikowska, N., & Van den Bussche, J. (2009). The foundations of the open provenance model. University of Southampton. https://eprints.soton.ac.uk/267282/1/fopm.pdf
Nadkarni, P. M., Marenco, L., & Brandt, C. (2012). Clinical research information systems. In Health informatics (pp. 135–154). Springer. https://doi.org/10.1007/978-1-84882-448-5_8
Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. National Intelligence Council. https://fas.org/irp/nic/disruptive.pdf.
Noumeir, R., & Renaud, B. (2010). IHE cross-enterprise document sharing for imaging: Interoperability testing software. Source Code for Biology and Medicine, 5(1), 1–15. https://doi.org/10.1186/1751-0473-5-9
Oosterwijk, H. (2002). DICOM basics (2nd ed.). Otech.
Open Provenance Model (OPM). (2010). Open Provenance Model (OPM) specifications. https://openprovenance.org/opm/old-index.html
Pearson, D. (2002). Presentation on grid data requirements scoping metadata & provenance [Workshop on Data Derivation and Provenance], Chicago, IL, USA.
Peterson, K., Deeduvanu, R., Kanjamala, P., & Boles, K. (2016). A blockchain-based approach to health information exchange networks. U.S. Department of Health and Human Services. https://www.healthit.gov/sites/default/files/12-55-blockchain-based-approach-final.pdf
Puel, A., Wangenheim, A. V., Meurer, M. I., & de Macedo, D. D. J. (2014). BUCOMAX: Collaborative multimedia platform for real-time manipulation and visualization of bucomaxillofacial diagnostic images. In 2014 IEEE 27th international symposium on computer-based medical systems (pp. 392–395). https://doi.org/10.1109/CBMS.2014.12
Randall, D., Goel, P., & Abujamra, R. (2017). Blockchain applications and use cases in health information technology. Journal of Health & Medical Informatics, 8(3), 1–17. https://doi.org/10.4172/2157-7420.1000276
Rayhman, M. A., Hossain, M. S., Islam, M. S., Alrajeh, N. A., & Muhammad, G. (2020). Secure and provenance enhanced internet of health things framework: A blockchain managed federated learning approach. IEEE Access, 8, 205071–205087. https://doi.org/10.1109/ACCESS.2020.3037474
Robertson, A., Cresswell, K., Takian, A., Petrakaki, D., Crowe, S., Cornford, T., Barber, N., Avery, A., Fernando, B., Jacklin, A., Prescott, R., Klecun, E., Paton, J., Lichtner, V., Quinn, C., Ali, M., Morrison, Z., Jani, Y., Waring, J., Marsden, K., & Sheikh, A. (2010). Implementation and adoption of nationwide electronic health records in secondary care in England: Qualitative analysis of interim results from a prospective national evaluation. BMJ, 341, Article c4564. https://doi.org/10.1136/bmj.c4564
Roehrs, A., da Costa, C. A., & da Righi, R. R. (2017). OmniPHR: A distributed architecture model to integrate personal health records. Journal of Biomedical Informatics, 71, 70–81. https://doi.org/10.1016/j.jbi.2017.05.012
Samuel, A. M., & Garcia-Constantino, M. (2022). User-centred prototype to support wellbeing and isolation of software developers using smartwatches. Advances in Notes in Information Science, 1, 140–151. https://doi.org/10.47909/anis.978-9916-9760-0-5.125
Samuel, R. E. (2016). A layered architectural approach to understanding distributed cryptographic ledgers. Issues in Information Systems, 17(IV), 222–226. https://doi.org/10.48009/4_iis_2016_222-226
Schauz, D. (2014). What is basic research? Insights from historical semantics. Minerva, 52(3), 273–328. https://doi.org/10.1007/s11024-014-9255-0
Sembay, M. J., de Macedo, D. D. J., & Dutra, M. L. (2021). A proposed approach for provenance data gathering. Mobile Networks and Applications, 26(1), 304–318. https://doi.org/10.1007/s11036-020-01648-7
Sembay, M. J., de Macedo, D. D. J., Júnior, L. P., Braga, R. M. M., & Sarasa-Cabezuelo, A. (2023). Provenance data management in health information systems: A systematic literature review. Journal of Personalized Medicine, 13(6), 991. https://doi.org/10.3390/jpm13060991
Sembay, M. J., de Macedo, D. D. J., & Marquez Filho, A. A. G. (2022). Identification of the relationships between data provenance and blockchain as a contributing factor for health information systems. In Proceedings of data and information in online environments: third eai international conference, DIONE 2022 (pp. 258–272). Springer Nature Switzerland. http://doi.org/10.1007/978-3-031-22324-2_20
Sembay, M. J., & Macedo, D. D. J. (2022). Health information systems: proposal of a provenance data management methodinthe instantiation of the W3C PROV-DM model. Advances in Notes in Information Science, 2, 101. ColNes Publishing. https://doi.org/10.47909/anis.978-9916-9760-3-6.101
Sembay, M. J., Macedo, D. D., & Dutra, M. L. (2020). A method for collecting provenance data: A case study in a Brazilian hemotherapy center. In Proceedings of the 1st EAI international conference on data and information in online environments (DIONE 2020) (pp. 1–14). EAI. https://doi.org/10.1007/978-3-030-50072-6_8
Silva, P. P. da, Silva, D., McGuinness, D. L., & McCool, R. (2003). Knowledge provenance infrastructure. IEEE Data Engineering Bulletin, 26(4), 26–32. https://dspace.rpi.edu/items/cd532a33-7392-4046-a4a2-c71679ec66eb
Simmhan, Y. L., Plale, B., & Gannon, D. (2005). A survey of data provenance techniques [Technical Report No. TR-618]. Computer Science Department, Indiana University. https://legacy.cs.indiana.edu/ftp/techreports/TR618.pdf
Sligo, J., Gauld, R., Roberts, V., & Villac, L. (2017). A literature review for large-scale health information system project planning, implementation and evaluation. International Journal of Medical Informatics, 97, 86–97. https://doi.org/10.1016/j.ijmedinf.2016.09.007
Sultan, K., Ruhi, U., & Lakhani, R. (2018). Conceptualizing blockchains: Characteristics & applications. arXiv. https://arxiv.org/abs/1806.03693
Swan, M. (2015). Blockchain: Blueprint for a new economy. O’Reilly Media.
Tan, W. C. (2008). Provenance in databases: Past, current, and future. IEEE Data Engineering Bulletin, 30(4), 3–12. https://scispace.com/pdf/provenance-in-databases-past-current-and-future-ymbe17g99v.pdf
Tian, F. (2016). An agri-food supply chain traceability system for China based on RFID & blockchain technology. In 13th International conference on service systems and service management (ICSSSM) (pp. 1–6). IEEE. https://doi.org/10.1109/ICSSSM.2016.7538424
Weerakoon, B. S., & Chandrasiri, N. R. (2023). Knowledge and utilisation of information and communication technology among radiographers in a lower-middle-income country. Radiography, 29(1), 227–233. https://doi.org/10.1016/j.radi.2022.11.013
Werder, K., Ramesh, B., & Zhang, R. (2022). Establishing data provenance for responsible artificial intelligence systems. ACM Transactions on Management Information Systems (TMIS), 13(2), 1–23. https://doi.org/10.1145/3503488
World Health Organization (WHO). (2004). Developing health management information systems: A practical guide for developing countries. World Health Organization Regional Office for the Western Pacific. https://iris.wpro.who.int/handle/10665.1/5498.
World Health Organization (WHO). (2008). Framework and standards for country health information systems (2nd ed.). https://www.who.int/healthinfo/country_monitoring_evaluation/who-hmn-framework-standards-chi.pdf.
Zhang, J., Sun, J., & Stahl, J. N. (2003). PACS and web-based image distribution and display. Computerized Medical Imaging and Graphics, 27(2–3), 197–206. https://doi.org/10.1016/S0895-6111(02)00074-5
Zhang, P., White, J., Schmidt, D. C., & Lenz, G. (2017). Blockchain technology use cases in healthcare. Advances in Computers, 111, 1–41. https:// doi.org/10.1016/bs.adcom.2018.03.006
Zhang, P., White, J., Schmidt, D. C., Lenz, G., & Rosenbloom, S. T. (2018). FHIRChain: Applying blockchain to securely and scalably share clinical data. Computational and Structural Biotechnology Journal, 16, 267–278. https://doi.org/10.1016/j.csbj.2018.07.004
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Márcio José Sembay, Douglas Dyllon Jeronimo de Macedo, Alexandre Augusto Gimenes Marquez Filho

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0) which permits copying and redistributing the material in any medium or format, adapting, transforming and building upon the material as long as the license terms are followed.