Data Integration Techniques For Healthcare ? A Comprehensive Survey
DOI:
https://doi.org/10.26438/ijcse/v8i8.2329Keywords:
Data integration, Big Data, Data Integration MethodsAbstract
Data is the most valuable asset. As a strategy, integration is the first step towards transforming data into meaningful and valuable information. Data integration provides the ability to manipulate data transparently across multiple data sources. Healthcare sector in particular has been hindered by the diversity of the biomedical data. A framework to unify the sources of such diverse data can facilitate diagnosis and plan for treatment. According to Experian, 66% of companies lack a centralised approach to data resulting in data silos. The data integration market is expected to grow annually at the rate of 12.5% since 2018. This paper discusses the need for data integration, the challenges in implementing a data integration framework, various approaches for data integration, their strength and weakness. The research directions which act as additional add-on or improvements to the existing system have been discussed.
References
[1] Rohini R. Rao, Krishnamoorthi Makkithaya and Neha Gupta, " Ontology based semantic representation for Public Health data integration", International Conference on Contemporary Computing and Informatics (IC3I), 4799-6629, IEEE 2014.
[2] Samir Tartir, I. Budak Arpinar and Amit P. Sheth , "Ontology evaluation and validation", Theory and Applications of Ontology: Computer Applications, pp. 115-130, 2010.
[3] ArifKurniadi and RetnoAstuti, "Patient Clinical Data Integration In Integrated Electronic Medical Record System for Health Care Facilities in Indonesia," Jurnal Kesehatan Masyarakat, Vol. 13-2, No. 11/2017, pp. 239-246.
[4] Jesus Peral, Antonio Ferrandez, David Gil, Rafael Munoz-Terol, and Higinio Mora, "An Ontology-Oriented Architecture for dealing with Heterogeneous Data applied to Telemedicine Systems", IEEE Access PP(99):1-1, July 2018.
[5] Shuxia Ren, Xu Lu and Teng Wang, "Application of Ontology in Medical Heterogeneous Data Integration", 3rd International Conference on Big Data Analysis, 978-1-5386-4794, IEEE, 2018
[6] IBM Corporation. The India cure: Remedying the challenges of the healthcare landscape. Somers, NY: IBM Institute for Business Value, 2017
[7] SamanehMadanian, Dave T Parry, David Airehrour and Marianne Cherrington, "mHealth and big-data integration: promises for healthcare system in India", BMJ Health Care Inform: 10.1136/bmjhci-2019-100071, september 2019.
[8] U. S. Mudunuri et al., "Knowledge and theme discovery across very large biological data sets using distributed queries: A prototype combining unstructured and structured data,`` PLoS One, Vol. 8, No. 2, 2013.
[9] S. Ceri, A. Kaitoua, M. Masseroli, P. Pinoli, and F. Venco, ``Data management for next generation genomic computing,`` In the Proceedings of the 19th International Conference on Extending Database, pp. 485-490,2016.
[10] R. Bellazzi, A. Dagliati, L. Sacchi, and D. Segagni, ``Big data technologies,`` Journal of Diabetes Science and Technology, Vol. 9, No. 5, pp. 1119_1125, 2015.
[11] Harshana Liyanage, Paul Krause and Simon de Lusignan, "Using ontologies to improve semantic interoperability in health data," Journal of Innovation in Health Informatics, Vol. 22, No. 2, 2015.
[12] Wei-Po Lee, Jhih-Yuan Huang, Hsuan-Hao Chang,King-Teh Lee, And Chao-Ti Lai, "Predicting Drug Side Effects Using Data Analytics and the Integration of Multiple Data Sources," IEEE Access. 2169-3536, Vol. 5, 2017.
[13] David A et al., "A Large-Scale Clinical Validation of an Integrated Monitoring System in the Emergency Department," IEEE Journal of Biomedical and Health Informatics, Vol. 17, No. 4, 2013.
[14] Hua Min, Frank J. Manion, Elizabeth Goralczyk, Yu-Ning Wong, Eric Ross and Robert Beck J, "Integration of Prostate Cancer Clinical Data using an Ontology," Journal of Biomedical Informatics, Vol. 42, No. 06, pp.1035-1045, 2009.
[15] Mathias Brochhausen et al., "The ACGT Master Ontology and its applications " Towards an ontology-driven cancer research and management system," Journal of Biomedical Informatics, Vol. 44, No. 10, pp.8"25, 2010.
[16] X. L. Dong and F. Naumann, ``Data fusion,`` VLDB Endowment, Vol. 2, No. 2, pp. 1654-1655, 2009.
[17] W. Liu and E. Park, ``Big data as an e-health service,``, International Conference on Computing, Networking and Communications (ICNC), pp. 982-988, 2014.
[18] A. Hasnain et al., "Biofed: Federated query processing over life sciences linked open data,`` Journal 0f Biomedical Semantics, Vol. 8, No. 1, p. 13, 2017.
[19] S. Ceri, A. Kaitoua, M. Masseroli, P. Pinoli, and F. Venco, ``Data management for next generation genomic computing,`` In the Proceedings of 19th International Conference on Extending Database, pp. 485-490, 2016.
[20] Buccella A, Cechich A and Brisaboa NR, "An ontology approach to data integration." Journal of Computer Science and Technology, Vol. 3, No. 2, pp. 62"68, 2003.
[21] Levy AY, Rajaraman A and Ordille JJ, "Querying heterogeneous information sources using source descriptions," In the Proceedings of the twenty-second international conference on very large data bases (VLDB"96). Mumbai, India; 1996
[22] E. Mezghani, E. Exposito, K. Drira, M. D. Silveira, and C. Pruski, "A semantic big data platform for integrating heterogeneous wearable data in healthcare,`` Journal of Medical Systems, Vol. 39, No. 12, p. 185, 2015.
[23] H. Kondylakis et al., "iManageCancer: Developing a platform for Empowering patients and strengthening self-management in cancer diseases,`` In the Proceedings of the IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS), pp. 755-760, 2017.
[24] M. Poulymenopoulou, D. Papakonstantinou, and F. Malamateniou, "A health analytics semantic ETL service for obesity surveillance,`` Studies Health Technology and Informatics, Vol. 210, pp. 840-844, 2015.
[25] A. Bahga and V. K. Madisetti, "A cloud-based approach for interoperable electronic health records (EHRs),`` IEEE Journal of Biomedical and Health Informatics, Vol. 17, No. 5, pp. 894-906, 2013.
[26] Carol I and Kumar SBR. "Conflict resolution and duplicate elimination in heterogeneous datasets using unified data retrieval techniques," Indian Journal of Science and Technology, Vol. 8, No. 22, pp.1-6 2015.
[27] Khazalah F, Malik Z and Rezgui A, "Automated conflict resolution in collaborative data sharing systems using community feedbacks," Information Sciences, Vol. 298, pp. 407-424, 2015.
[28] Weiguo F, Lu H, Madnick SE and Cheung D, "Discovering and reconciling value conflicts for numerical data integration," Information Systems, Vol. 26, No. 8, pp. 635-656, 2001.
[29] Ramkumar T, Hariharan S and Selvamuthukumaran S, "A survey on mining multiple data sources," Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, Vol. 3, No. 1, pp. 1-11, 2013.
[30] Ramkumar T, Srinivasan R and Hariharan S, "Synthesizing global association rules from different data sources based on desired interestingness metrics," The International Journal of Information Technology and Decision Making, Vol. 13, No. 3, pp. 473-495, 2014.
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