Article

Building a Protocol Expressway: The Case of Mayo Clinic Cancer Center

Cancer Center Clinical Research Office, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA.
Journal of Clinical Oncology (Impact Factor: 17.88). 07/2009; 27(23):3855-60. DOI: 10.1200/JCO.2008.21.4338
Source: PubMed

ABSTRACT Inconsistencies and errors resulting from nonstandard processes, together with redundancies, rework, and excess workload, lead to extended time frames for clinical trial protocol development. This results in dissatisfaction among sponsors, investigators, and staff and restricts the availability of novel treatment options for patients.
A team of experts from Mayo Clinic formed, including Protocol Development Unit staff and management from the three Mayo Clinic campuses (Florida, Minnesota, and Arizona), a systems and procedures analyst, a quality office analyst, and two physician members to address the identified deficiencies. The current-state process was intensively reviewed, and improvement steps were taken to accelerate the development and approval of cancer-related clinical trials. The primary goal was to decrease the time from receipt of a new protocol through submission to an approving authority, such as the National Cancer Institute or institutional review board.
Using the Define, Measure, Analyze, Improve, Control (DMAIC) framework infused with Lean waste-reduction methodologies, areas were identified for improvement, including enhancing first-time quality and processing new studies on a first-in/first-out basis. The project was successful in improving the mean turnaround time for internally authored protocols (P < .001) from 25.00 weeks (n = 41; range, 3.43 to 94.14 weeks) to 10.15 weeks (n = 14; range, 4.00 to 22.14 weeks). The mean turnaround time for externally authored protocols was improved (P < .001) from 20.61 weeks (n = 85; range, 3.29 to 108.57 weeks) to 7.79 weeks (n = 50; range, 2.00 to 20.86 weeks).
DMAIC framework combined with Lean methodologies is an effective tool to structure the definition, planning, analysis, and implementation of significant process changes.

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