Roadmap for the development of the University of North Carolina at Chapel Hill Genitourinary OncoLogy Database--UNC GOLD.

BACKGROUND The management of genitourinary malignancies requires a multidisciplinary care team composed of urologists, medical oncologists, and radiation oncologists. A genitourinary (GU) oncology clinical database is an invaluable resource for patient care and research. Although electronic medical records provide a single web-based record used for clinical care, billing, and scheduling, information is typically stored in a discipline-specific manner and data extraction is often not applicable to a research setting. A GU oncology database may be used for the development of multidisciplinary treatment plans, analysis of disease-specific practice patterns, and identification of patients for research studies. Despite the potential utility, there are many important considerations that must be addressed when developing and implementing a discipline-specific database. METHODS AND MATERIALS The creation of the GU oncology database including prostate, bladder, and kidney cancers with the identification of necessary variables was facilitated by meetings of stakeholders in medical oncology, urology, and radiation oncology at the University of North Carolina (UNC) at Chapel Hill with a template data dictionary provided by the Department of Urologic Surgery at Vanderbilt University Medical Center. Utilizing Research Electronic Data Capture (REDCap, version 4.14.5), the UNC Genitourinary OncoLogy Database (UNC GOLD) was designed and implemented. RESULTS The process of designing and implementing a discipline-specific clinical database requires many important considerations. The primary consideration is determining the relationship between the database and the Institutional Review Board (IRB) given the potential applications for both clinical and research uses. Several other necessary steps include ensuring information technology security and federal regulation compliance; determination of a core complete dataset; creation of standard operating procedures; standardizing entry of free text fields; use of data exports, queries, and de-identification strategies; inclusion of individual investigators' data; and strategies for prioritizing specific projects and data entry. CONCLUSIONS A discipline-specific database requires a buy-in from all stakeholders, meticulous development, and data entry resources to generate a unique platform for housing information that may be used for clinical care and research with IRB approval. The steps and issues identified in the development of UNC GOLD provide a process map for others interested in developing a GU oncology database.

[1]  Stan A. Waddell,et al.  Creation and Use of a Database in Clinical and Translational Research , 2010, Journal of investigative medicine : the official publication of the American Federation for Clinical Research.

[2]  James G. Anderson,et al.  Clearing the way for physicians' use of clinical information systems , 1997, CACM.

[3]  Eric Poon,et al.  Meaningful use of health information technology: evidence suggests benefits and challenges lie ahead. , 2011, The American journal of managed care.

[4]  Timothy S. Carey,et al.  Reflections on the use of electronic health record data for clinical research , 2009, Health Informatics J..

[5]  Lori Yackanicz,et al.  Physician Buy-In for EMR's , 2010 .

[6]  Philip R. O. Payne,et al.  CRC Clinical Trials Management System (CTMS): An Integrated Information Management Solution for Collaborative Clinical Research , 2003, AMIA.

[7]  Binny Krishnankutty,et al.  Data management in clinical research: An overview , 2012, Indian journal of pharmacology.

[8]  S Day,et al.  Double data entry: what value, what price? , 1998, Controlled clinical trials.

[9]  Lori Yackanicz,et al.  Physician buy-in for EMRs. , 2010, Journal of healthcare information management : JHIM.

[10]  D Gibson,et al.  Is double data entry necessary? The CHART trials. CHART Steering Committee. Continuous, Hyperfractionated, Accelerated Radiotherapy. , 1994, Controlled clinical trials.

[11]  S. Deo.  Computerized Clinical Database Development in Oncology , 2011, Indian Journal of Palliative Care.

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

[13]  James F. Brinkley,et al.  A partnership approach for Electronic Data Capture in small-scale clinical trials , 2011, J. Biomed. Informatics.

[14]  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..

[15]  P. Harris,et al.  Research electronic data capture (REDCap) - A metadata-driven methodology and workflow process for providing translational research informatics support , 2009, J. Biomed. Informatics.

[16]  Y. Lotan,et al.  Comprehensive handbook for developing a bladder cancer cystectomy database. , 2013, Urologic oncology.

[17]  Leonard Steinborn.  The United States Code of Federal Regulations 21 CFR, Section 821.25 for Medical Device Tracking , 2004 .

[18]  C Ohmann,et al.  Future Developments of Medical Informatics from the Viewpoint of Networked Clinical Research , 2009, Methods of Information in Medicine.

[19]  H. Prokosch,et al.  Perspectives for Medical Informatics , 2009, Methods of Information in Medicine.

[20]  A. Butte,et al.  Translational Bioinformatics: Data‐driven Drug Discovery and Development , 2012, Clinical pharmacology and therapeutics.

[21]  W W Marshall,et al.  Use of a secure Internet Web site for collaborative medical research. , 2000, JAMA.