Metrics and Best Practices in Clinical Data Management: Conclusions of a Dia Roundtable Workshop
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Drug Information Journal, Vol. 35, pp. 681-694, 2001 hinted in the USA. All rights reserved.
METRICS AND BEST PRACTICES IN CLINICAL DATA MANAGEMENT: CONCLUSIONS OF A DIA ROUNDTABLE WORKSHOP* RONALDW. HELMS,PHD Chairman, Rho, Inc., and Professor Emeritus, Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina
RONFITZMARTIN, PHD, MBA Group Executive Director, Biostatistics and Clinical Data Management, Purdue Pharma L.P., Stamford, Connecticut
PAULAJ. FILLOW Assistant Manager, BCDM Operations, Purdue Pharma L.P., Stamford, Connecticut
SHARON A. MILLER Associate Consultant, Clinical Data Management Consultant, Eli Lilly and Company, Indianapolis, Indiana
LINDAM. TALLEY Team Leader Data Management Program Phase, Global Clinical Research, Eli Lilly and Company, Indianapolis, Indiana
ROSEMARYMURPHY Head of Business Strategy for Medical Information Processing and Statistics, Novartis, Horsham, United Kingdom
Metrics are statistics that characterize the quality, productivity, speed (pe$ormance), or cost of one or more clinical data management activities. Even though clinical data management metrics have been used for decades, little effort has been made to standardize definitions of metrics or publish their values (“practices”). Participants in a Drug Information Association (DIA)roundtable conference on metrics, organized by Ron Fitzmartin, began discussions that could lead to standardization and publication of metrics and practices. The participants discussed a wide variety of clinical data management and biostatistical metrics, assigned subjective priority (importance) levels, created descriptions for many, and estimated current and best practices for some. Noting that clinical data management procedures vary widely, that actual procedures profoundly affect prac-
*Responsibility for this work and any flaws therein rests solely with the authors. Dr. Helms’ work on this paper was supported by the Statistics and Data Management Center for the Comprehensive Sickle Cell Centers Program, funded by the National Heart, Lung, and Blood Institute, Grant No. P60 HL38632. Reprint address: Ronald W. Helms, PhD, Rho, Inc., 100 Eastowne Drive, Chapel Hill NC 27514. E-mail: [email protected].
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R. W. Helms, R. Fitzmartin, P. J. Fillow, S.A. Miller, L. M . Talley, and R. Murphy tices, and that little is known publicly about current or best practices, the participants were reluctant to place great confidence in their estimates of best and current practices. Key Words: Metrics; Current practices; Best practices; Quality; Productivity; Performance;
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INTRODUCTION Concepts and Terminology: Metrics and Best Practices in Clinical Data Management A METRIC IS A STATISTIC that quantitatively represents a characteristic of a process or a component of a process. In clinical data management, one is often interested in metr i c ~representing quality, productivity, speed (or “performance”), or cost of one or more cli
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