Ubiquitous Health Profile (UHPr): a big data curation platform for supporting health data interoperability

The lack of Interoperable healthcare data presents a major challenge, towards achieving ubiquitous health care. The plethora of diverse medical standards, rather than common standards, is widening the gap of interoperability. While many organizations are working towards a standardized solution, there is a need for an alternate strategy, which can intelligently mediate amongst a variety of medical systems, not complying with any mainstream healthcare standards while utilizing the benefits of several standard merging initiates, to eventually create digital health personas. The existence and efficiency of such a platform is dependent upon the underlying storage and processing engine, which can acquire, manage and retrieve the relevant medical data. In this paper, we present the Ubiquitous Health Profile (UHPr), a multi-dimensional data storage solution in a semi-structured data curation engine, which provides foundational support for archiving heterogeneous medical data and achieving partial data interoperability in the healthcare domain. Additionally, we present the evaluation results of this proposed platform in terms of its timeliness, accuracy, and scalability. Our results indicate that the UHPr is able to retrieve an error free comprehensive medical profile of a single patient, from a set of slightly over 116.5 million serialized medical fragments for 390,101 patients while maintaining a good scalablity ratio between amount of data and its retrieval speed.

[1]  Charles F. Bearden,et al.  A Nondegenerate Code of Deleterious Variants in Mendelian Loci Contributes to Complex Disease Risk , 2013, Cell.

[2]  Heather J. Ruskin,et al.  EpiGeNet: A Graph Database of Interdependencies Between Genetic and Epigenetic Events in Colorectal Cancer , 2017, J. Comput. Biol..

[3]  Farhaan Mirza,et al.  A review on IoT healthcare monitoring applications and a vision for transforming sensor data into real-time clinical feedback , 2017, 2017 IEEE 21st International Conference on Computer Supported Cooperative Work in Design (CSCWD).

[4]  D Kalra,et al.  Electronic health records: new opportunities for clinical research , 2013, Journal of internal medicine.

[5]  Nicolaus Henke,et al.  The age of analytics: competing in a data-driven world , 2016 .

[6]  Sungyoung Lee,et al.  Reconciliation of SNOMED CT and domain clinical model for interoperable medical knowledge creation , 2017, 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[7]  John Lane,et al.  IEEE Standard Computer Dictionary: Compilation of IEEE Standard Computer Glossaries , 1991 .

[8]  Janne Lahtiranta,et al.  Mediator – enabler for successful digital health care , 2017 .

[9]  Richard E Gliklich,et al.  21st Century Patient Registries: Registries for Evaluating Patient Outcomes: A User’s Guide: 3rd Edition, Addendum , 2018 .

[10]  Diego Boscá,et al.  Interoperability of clinical decision-support systems and electronic health records using archetypes: A case study in clinical trial eligibility , 2013, J. Biomed. Informatics.

[11]  Yannis Ioannidis,et al.  Interoperability via Mapping Objects , 2001 .

[12]  Patricia C. Dykes,et al.  Care coordination gaps due to lack of interoperability in the United States: a qualitative study and literature review , 2016, BMC Health Services Research.

[13]  Catherine Havasi,et al.  ConceptNet 5.5: An Open Multilingual Graph of General Knowledge , 2016, AAAI.

[14]  S. Sivachandiran,et al.  A survey on security attacks in electronic healthcare systems , 2017, 2017 International Conference on Communication and Signal Processing (ICCSP).

[15]  Gregory Zacharewicz,et al.  An ontology-driven framework towards building enterprise semantic information layer , 2013, Adv. Eng. Informatics.

[16]  Sungyoung Lee,et al.  Recommendation Statements Identification in Clinical Practice Guidelines Using Heuristic Patterns , 2018, 2018 19th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD).

[17]  Ishwarappa,et al.  A Brief Introduction on Big Data 5Vs Characteristics and Hadoop Technology , 2015 .

[18]  Xinyu Wu,et al.  Quality assessment of systematic reviews on total hip or knee arthroplasty using mod-AMSTAR , 2018, BMC Medical Research Methodology.

[19]  Stephen P Gardner,et al.  Ontologies and semantic data integration. , 2005, Drug discovery today.

[20]  Michael Lane,et al.  An evaluation of NoSQL databases for EHR systems , 2014 .

[21]  Peter W. Eklund,et al.  The Health Service Bus: An Architecture and Case Study in Achieving Interoperability in Healthcare , 2010, MedInfo.

[22]  Yi Guo,et al.  An ontology-guided semantic data integration framework to support integrative data analysis of cancer survival , 2018, BMC Medical Informatics and Decision Making.

[23]  C. Morrison,et al.  Hormonal Contraception and the Risk of HIV Acquisition: An Individual Participant Data Meta-analysis , 2015, PLoS medicine.

[24]  R Haux,et al.  Confluence of Disciplines in Health Informatics: an International Perspective , 2011, Methods of Information in Medicine.

[25]  Hugo Liu,et al.  ConceptNet — A Practical Commonsense Reasoning Tool-Kit , 2004 .

[26]  Tim Berners-Lee,et al.  Linked Data - The Story So Far , 2009, Int. J. Semantic Web Inf. Syst..

[27]  Wanasanan Thongsongkrit,et al.  Web Services Description Language (WSDL) , 2014, Encyclopedia of Social Network Analysis and Mining.

[28]  Jesualdo Tomás Fernández-Breis,et al.  LinkEHR-Ed: A multi-reference model archetype editor based on formal semantics , 2009, Int. J. Medical Informatics.

[29]  Boopala Krishnan N,et al.  Real Time Internet Application with distributed flow environment for medical IoT , 2015, 2015 International Conference on Green Computing and Internet of Things (ICGCIoT).

[30]  Sarah Zribi,et al.  Supporting interoperability of collaborative networks through engineering of a service-based Mediation Information System (MISE 2.0) , 2015, Enterp. Inf. Syst..

[31]  HaiqiAhmed Open source EMR software , 2014 .

[32]  D. Boyd,et al.  Six Provocations for Big Data , 2011 .

[33]  Girdhar Gopal,et al.  An Efficient Approach for Storing and Accessing Small Files with Big Data Technology , 2016 .

[34]  Lars-Erik Axelsson,et al.  Identify User Profiles in Information Systems with Unknown Users : A database modelling approach , 2006 .

[35]  J. Grossman,et al.  Building a Better Delivery System: A New Engineering/Health Care Partnership , 2005 .

[36]  Christel Daniel-Le Bozec,et al.  Using electronic health records for clinical research: The case of the EHR4CR project , 2015, J. Biomed. Informatics.

[37]  P. Elliott,et al.  UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age , 2015, PLoS medicine.

[38]  Pasquale Pagano,et al.  Data Interoperability , 2013, Data Sci. J..

[39]  Dipak Kalra,et al.  Data Resource Profile: Cardiovascular disease research using linked bespoke studies and electronic health records (CALIBER) , 2012, International journal of epidemiology.

[40]  Jeffrey Nielson,et al.  Fast Healthcare Interoperability Resources (FIHR) , 2016 .

[41]  Jingquan Li,et al.  A Service-Oriented Approach to Interoperable and Secure Personal Health Record Systems , 2017, 2017 IEEE Symposium on Service-Oriented System Engineering (SOSE).

[42]  Arnon Rosenthal,et al.  Data Interoperability: Standardization or Mediation , 1996 .

[43]  Iakovos S. Venieris,et al.  An Event-driven Health Service Bus , 2015 .

[44]  Christina Athanasopoulou,et al.  Internet use, eHealth literacy and attitudes toward computer/internet among people with schizophrenia spectrum disorders: a cross-sectional study in two distant European regions , 2017, BMC Medical Informatics and Decision Making.

[45]  Boonserm Kulvatunyou,et al.  Semantic mediation for standard-based B2B interoperability , 2010, IEEE Internet Computing.

[46]  N. Dreyer,et al.  Registries for Evaluating Patient Outcomes: A User’s Guide , 2010 .

[47]  Thomas J. S. Durant,et al.  Evaluation of relational and NoSQL database architectures to manage genomic annotations , 2016, J. Biomed. Informatics.

[48]  Catalina Martínez-Costa,et al.  Using the ResearchEHR platform to facilitate the practical application of the EHR standards , 2012, J. Biomed. Informatics.

[49]  Uri Kartoun,et al.  A Methodology to Generate Virtual Patient Repositories , 2016, ArXiv.

[50]  Tim Shaw,et al.  Impact of digital health on the safety and quality of health care , 2018 .

[51]  L. Coventry,et al.  Cybersecurity in healthcare: A narrative review of trends, threats and ways forward. , 2018, Maturitas.

[52]  De MoorGeorges,et al.  Using electronic health records for clinical research , 2015 .

[53]  Regina Dunlea,et al.  Simple Object Access Protocol (SOAP) , 2005 .

[54]  Mario Pascual,et al.  Examining database persistence of ISO/EN 13606 standardized electronic health record extracts: relational vs. NoSQL approaches , 2017, BMC Medical Informatics and Decision Making.

[55]  Paulo Sérgio Almeida,et al.  ID generation in mobile environments , 2006 .

[56]  MarcosMar,et al.  Interoperability of clinical decision-support systems and electronic health records using archetypes , 2013 .

[57]  Maria C Sanchez-Gomez,et al.  Evaluating Data Quality of Newborn Hearing Screening. , 2019, Journal of early hearing detection and intervention.

[58]  Diego Calvanese,et al.  Ontop: Answering SPARQL queries over relational databases , 2016, Semantic Web.

[59]  Maria Fazio,et al.  An OAIS-Based Hospital Information System on the Cloud: Analysis of a NoSQL Column-Oriented Approach , 2018, IEEE Journal of Biomedical and Health Informatics.

[60]  Catalina Martínez-Costa,et al.  Clinical data interoperability based on archetype transformation , 2011, J. Biomed. Informatics.

[61]  Vivek Verma,et al.  Interoperable End-to-End Remote Patient Monitoring Platform Based on IEEE 11073 PHD and ZigBee Health Care Profile , 2018, IEEE Transactions on Biomedical Engineering.

[62]  Sungyoung Lee,et al.  Semantic Bridge for Resolving Healthcare Data Interoperability , 2020, 2020 International Conference on Information Networking (ICOIN).

[63]  Sungyoung Lee,et al.  Resolving data interoperability in ubiquitous health profile using semi-structured storage and processing , 2019, SAC.

[64]  B. B. Zaidan,et al.  Open source EMR software: Profiling, insights and hands-on analysis , 2014, Comput. Methods Programs Biomed..

[65]  Reid Berryman,et al.  Data Interoperability and Information Security in Healthcare , 2013 .

[66]  Parth Gohil,et al.  Efficient Ways to Improve the Performance of HDFS for Small Files , 2014 .

[67]  Ferreira,et al.  Enabling agents to retrieve openEHR- based health data through implementing HL7 communication with departmental information systems , 2012 .

[68]  Dimitrios Zikos,et al.  CDSS-RM: a clinical decision support system reference model , 2018, BMC Medical Research Methodology.

[69]  Lena Wiese,et al.  Efficient In-Database Patient Similarity Analysis for Personalized Medical Decision Support Systems , 2018, Big Data Res..

[70]  Jenny C. Taylor,et al.  Are whole-exome and whole-genome sequencing approaches cost-effective? A systematic review of the literature , 2018, Genetics in Medicine.

[71]  Spiros C. Denaxas,et al.  Big data from electronic health records for early and late translational cardiovascular research: challenges and potential , 2017, European heart journal.

[72]  Bertalan Meskó,et al.  The role of artificial intelligence in precision medicine , 2017 .