alexa Toward a Comprehensive and Accurate Measure of Clinical Trial Workload, Equity, Quality Assurance and Patient Safety-How Much Workload is Too Much? Commentary and Brief Research Report
ISSN: 2167-0870

Journal of Clinical Trials
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Commentary

Toward a Comprehensive and Accurate Measure of Clinical Trial Workload, Equity, Quality Assurance and Patient Safety-How Much Workload is Too Much? Commentary and Brief Research Report

Ralph Jay Johnson*

MD Anderson Cancer Center, University of Texas, Unit 439, 1515 Holcombe Blvd Houston, Texas 77030, USA

*Corresponding Author:
Ralph Jay Johnson, MD
Anderson Cancer Center
University of Texas, Unit 439
1515 Holcombe Blvd Houston, Texas 77030, USA
Tel: + 832-372-3511
E-mail: [email protected]

Received Date: May 09, 2017; Accepted Date: May 23, 2017; Published Date: May 29, 2017

Citation: Johnson RJ (2017) Toward a Comprehensive and Accurate Measure of Clinical Trial Workload, Equity, Quality Assurance and Patient Safety-How Much Workload is Too Much? Commentary and Brief Research Report. J Clin Trials 7:309. doi: 10.4172/2167-0870.1000309

Copyright: © 2017 Johnson RJ. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 

Abstract

This article provides a brief commentary on the methodology surrounding controlled clinical trials, the growing trend of centers conducting multiple controlled trials (i.e. “factory science”), trial workload measures, and possible relationships among workload, especially excessive workload, and mistakes, mishaps, deviations, violations, or just plain slippage. Findings are reported for each factor or measure included in an incremental algorithm designed to provide a numeric score for clinical trial workload. This algorithm was developed in the interest of quality assurance as part of program evaluation through an Oracle Delphi process by a study group of subject matter experts who work with a substantial number of clinical trials in an international cancer center in Houston, Texas (UT-MD Anderson). At a minimum, the algorithm also reflects the complexity of the issues surrounding the clinical trial workload and the conduct of clinical trials in general. Unlike previous measures reported in the literature, it may lack in simplicity for expedient use as a tool for informing management, although it provides comprehensiveness and accuracy and lends itself more to scientific testing. Future avenues of study are considered.

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