Using patient lists to add value to integrated data repositories

Patient lists are project-specific sets of patients that can be queried in integrated data repositories (IDR's). By allowing a set of patients to be an addition to the qualifying conditions of a query, returned results will refer to, and only to, that set of patients. We report a variety of use cases for such lists, including: restricting retrospective chart review to a defined set of patients; following a set of patients for practice management purposes; distributing "honest-brokered" (deidentified) data; adding phenotypes to biosamples; and enhancing the content of study or registry data. Among the capabilities needed to implement patient lists in an IDR are: capture of patient identifiers from a query and feedback of these into the IDR; the existence of a permanent internal identifier in the IDR that is mappable to external identifiers; the ability to add queryable attributes to the IDR; the ability to merge data from multiple queries; and suitable control over user access and de-identification of results. We implemented patient lists in a custom IDR of our own design. We reviewed capabilities of other published IDRs for focusing on sets of patients. The widely used i2b2 IDR platform has various ways to address patient sets, and it could be modified to add the low-overhead version of patient lists that we describe.

[1]  Rajiv Dhir,et al.  A multidisciplinary approach to honest broker services for tissue banks and clinical data , 2008, Cancer.

[2]  Shawn N. Murphy,et al.  Data Warehousing for Clinical Research , 2009, Encyclopedia of Database Systems.

[3]  Prakash M. Nadkarni,et al.  Data Extraction and Ad Hoc Query of an Entity– Attribute–Value Database , 2000 .

[4]  Susan C. Weber,et al.  STRIDE - An Integrated Standards-Based Translational Research Informatics Platform , 2009, AMIA.

[5]  B S Erdal,et al.  A Database De-identification Framework to Enable Direct Queries on Medical Data for Secondary Use , 2012, Methods of Information in Medicine.

[6]  Jacob Anhøj,et al.  Generic Design of Web-Based Clinical Databases , 2003, Journal of medical Internet research.

[7]  Prakash M. Nadkarni,et al.  Guidelines for the effective use of entity-attribute-value modeling for biomedical databases , 2007, Int. J. Medical Informatics.

[8]  Christopher G. Chute,et al.  The Enterprise Data Trust at Mayo Clinic: a semantically integrated warehouse of biomedical data , 2010, J. Am. Medical Informatics Assoc..

[9]  D. Blumenthal,et al.  The "meaningful use" regulation for electronic health records. , 2010, The New England journal of medicine.

[10]  P. Embí,et al.  Toward Reuse of Clinical Data for Research and Quality Improvement: The End of the Beginning? , 2009, Annals of Internal Medicine.

[11]  Ralph Kimball,et al.  The Data Warehouse Lifecycle Toolkit , 2009 .

[12]  Philip R. O. Payne,et al.  TRIAD: The Translational Research Informatics and Data Management Grid , 2011, Applied Clinical Informatics.

[13]  James J. Cimino,et al.  The Clinical Research Data Repository of the US National Institutes of Health , 2010, MedInfo.

[14]  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.

[15]  James R. Murphy,et al.  A Dimensional Bus model for integrating clinical and research data , 2011, J. Am. Medical Informatics Assoc..

[16]  Michael G Kahn,et al.  Configuration Challenges: Implementing Translational Research Policies in Electronic Medical Records , 2007, Academic medicine : journal of the Association of American Medical Colleges.

[17]  Alon Y. Halevy,et al.  Data integration and genomic medicine , 2007, J. Biomed. Informatics.

[18]  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..

[19]  Jessica D. Tenenbaum,et al.  Practices and perspectives on building integrated data repositories: results from a 2010 CTSA survey , 2012, J. Am. Medical Informatics Assoc..

[20]  D. Roden,et al.  Development of a Large‐Scale De‐Identified DNA Biobank to Enable Personalized Medicine , 2008, Clinical pharmacology and therapeutics.

[21]  Isaac S. Kohane,et al.  Strategies for maintaining patient privacy in i2b2 , 2011, J. Am. Medical Informatics Assoc..

[22]  Ralph Kimball,et al.  The Data Warehouse Lifecycle Toolkit: Expert Methods for Designing, Developing and Deploying Data Warehouses with CD Rom , 1998 .