Connecting Basic Research and Healthcare Big Data

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Elsevier Health Analytics WHS 2015 Big Data in Health Connecting Basic Research and Healthcare Big Data Olaf Lodbrok Managing Director Elsevier Health Analytics o.lodbrok@elsevier.com t +49 89 5383 600 m +49 174 344 1056 October 11, 2015

Elsevier Health Analytics WHS 2015 Big Data in Health 2 Big Data will transform healthcare Elsevier Health Analytics helping to improve patient outcomes we apply big data mining methods and technology to medicine and healthcare our customers are sickness funds (statutory health insurance), providers, and industry we are granted access to ca.10% of the German population's routine healthcare (claims) data* data security privacy is our highest priority to improve patient outcomes * under tight regulatory approval and oversight; access through partnership with 80 German sickness funds.

Elsevier Health Analytics WHS 2015 Big Data in Health 1 Paradigm Data in healthcare highly diverse and extremely fragmented 3 insurers providers researchers patients apps app data omics clinical research EHR claims data ontology graph metadata formats gene DBs protein DBs drug, DDI & ADR DBs abstracts publications

Elsevier Health Analytics WHS 2015 Big Data in Health 4 Paradigm 2 Data privacy extremely difficult in big data privacy risk of transparency local data, not shared data co-located (big data) 100% secure anonymization longitudinally linked data k-anonymity, l-diversity, database implemented routine data provided under statutory constraints additional information (lab, clinical, apps, genomic) trials, embedded cohorts security information governance credibility patient consent

Elsevier Health Analytics WHS 2015 Big Data in Health 5 Conclusion 3 Colocate data for scientific research in health: Next Generation Analytic System key big data in health research needs Elsevier contribution Open Source solution, e.g. knowledge graphs Elsevier Medical Graph text mining Elsevier Text Mining large corpus of scientific publications, guidelines Science Direct Clinical Key analytic workbench (at choice of researcher) R, Scala, Java, Python, SQL, MLlib, Deep Learing, GraphX big data processing system (> Petabytes) Spark big data storage system (> Petabytes) HDFS insurers providers researchers app data omics patients apps gene DBs protein DBs data access & security controls collaboration accross inst's data (size, linked, breadth & depth) data refinery (ingestion & normalization, ontology) Elsevier Research Management 6 million patient data sets EMMeT, Emtree, Gold Standard clinical research EHR claims data ontology graph metadata formats drug, DDI & ADR DBs abstracts publications trust center, patient data anonymization ISO 27001 secure datacenter, elastic cloud information governance

Elsevier Health Analytics WHS 2015 Big Data in Health 6 Our vision: the Elsevier Medical Graph to predict individual patients' disease progression and offer treatment options for a broad range of indications Elsevier Medical Graph Complete, automated extraction of all information and representation as a weighted, directed graph. Shows probability of disease progression for all indications. Health managers or medical staff can send patient individual data to the Medical Graph and receive probabilities (of progression), clarifying questions, recommended tests, guideline recommendations and EBM treatment options.

Elsevier Health Analytics WHS 2015 Big Data in Health 7 Elsevier leading to support research and collaboration, publish and store data and methods, software Mendeley Data data.mendeley.com Elsevier Data in Brief Computer Methods and Programs in Biomedicine Original Software Publications: Software X Neurocomputung Research Data Repository Put your research data online today, so it can be cited, shared and secure. Share and reuse datasets by publishing data articles that: thoroughly describe the data, facilitating reproducibility make the data easier to find Computing methods and software for all aspects of biomedical research and medical practice Software or code in full all metadata needed by interested readers and users peer reviewed body of work for citation and indexing copy posted to GitHub