A Methodology to Perform Semi-automatic Distributed EHR Database Queries

The proliferation of electronic health databases has resulted in the existence of a wide collection of diversified clinical digital data. These data are fragmented over dispersed databases in different clinical silos around the world. The exploration of these electronic health records (EHRs) is essential for clinical and pharmaceutical research and, therefore, solutions for secure sharing of information across different databases are needed. Although several partial solutions have been proposed over the years, data sharing and integration has been hindered by many ethical, legal and social issues. In this paper, we present a methodology to perform semiautomatic queries over longitudinal clinical data repositories, where every data custodian maintains full control of data.

[1]  Simone Pringle,et al.  Interoperability of electronic health records and personal health records: key interoperability issues associated with information exchange. , 2009, Journal of healthcare information management : JHIM.

[2]  Amardeep Thind,et al.  Investigating concordance in diabetes diagnosis between primary care charts (electronic medical records) and health administrative data: a retrospective cohort study , 2010, BMC health services research.

[3]  W. Hersh Adding value to the electronic health record through secondary use of data for quality assurance, research, and surveillance. , 2007, The American journal of managed care.

[4]  J. Lei,et al.  Combining multiple healthcare databases for postmarketing drug and vaccine safety surveillance: why and how? , 2014, Journal of internal medicine.

[5]  Christian Ohmann,et al.  Meeting the Challenges of Patient Recruitment , 2007, International Journal of Pharmaceutical Medicine.

[6]  Christel Daniel-Le Bozec,et al.  Cross border semantic interoperability for clinical research: the EHR4CR semantic resources and services , 2016, CRI.

[7]  Serguei V. S. Pakhomov,et al.  Electronic medical records for clinical research: application to the identification of heart failure. , 2007, The American journal of managed care.

[8]  C. Mann,et al.  Observational research methods. Research design II: cohort, cross sectional, and case-control studies , 2003, Emergency medicine journal : EMJ.

[9]  A. Sinclair,et al.  New estimates of the burden of acute community-acquired infections among older people with diabetes mellitus: a retrospective cohort study using linked electronic health records , 2014, Diabetic medicine : a journal of the British Diabetic Association.

[10]  Hans-Ulrich Prokosch,et al.  Employing Computers for the Recruitment into Clinical Trials: A Comprehensive Systematic Review , 2014, Journal of medical Internet research.

[11]  Griffin M. Weber,et al.  Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2) , 2010, J. Am. Medical Informatics Assoc..

[12]  M. Dugas,et al.  A European inventory of common electronic health record data elements for clinical trial feasibility , 2014, Trials.

[13]  Charles Safran,et al.  Toward a national framework for the secondary use of health data: an American Medical Informatics Association White Paper. , 2007, Journal of the American Medical Informatics Association : JAMIA.

[14]  Pedro Lopes,et al.  Challenges and Opportunities for Exploring Patient-Level Data , 2015, BioMed research international.

[15]  Douglas MacFadden,et al.  SHRINE: Enabling Nationally Scalable Multi-Site Disease Studies , 2013, PloS one.

[16]  Hyeon-Eui Kim,et al.  Identifying Appropriate Reference Data Models for Comparative Effectiveness Research (CER) Studies Based on Data from Clinical Information Systems , 2013, Medical care.

[17]  S. Reisner,et al.  Mental health of transgender youth in care at an adolescent urban community health center: a matched retrospective cohort study. , 2015, The Journal of adolescent health : official publication of the Society for Adolescent Medicine.

[18]  Roy Pardee,et al.  The HMO Research Network Virtual Data Warehouse: A Public Data Model to Support Collaboration , 2014, EGEMS.

[19]  M. Crossley,et al.  Observational Research Methods , 1987 .

[20]  A. Michael Froomkin,et al.  Ethical, legal and social issues for personal health records and applications , 2010, J. Biomed. Informatics.

[21]  Douglas MacFadden,et al.  Application of Information Technology The Shared Health Research Information Network ( SHRINE ) : A Prototype Federated Query Tool for Clinical Data Repositories , 2014 .

[22]  Christoph U. Lehmann,et al.  Clinical Data Reuse or Secondary Use: Current Status and Potential Future Progress. , 2017, Yearbook of medical informatics.

[23]  Richard Platt,et al.  The U.S. Food and Drug Administration's Mini‐Sentinel Program , 2012 .

[24]  Catherine Tucker,et al.  Health Information Exchange, System Size and Information Silos , 2013, Journal of health economics.

[25]  José Luís Oliveira,et al.  Architecture to Summarize Patient-Level Data Across Borders and Countries , 2015, MedInfo.

[26]  Jae-Wook Song,et al.  Observational Studies: Cohort and Case-Control Studies , 2010, Plastic and reconstructive surgery.

[27]  Yu-Chuan Li,et al.  Observational Health Data Sciences and Informatics (OHDSI): Opportunities for Observational Researchers , 2015, MedInfo.

[28]  Deborah H. Batson,et al.  Data model considerations for clinical effectiveness researchers. , 2012, Medical care.