Wednesday, May 5, 2010

Performance Management, Clinical Submission Data Governance and Quality

Establishing a standard of operation and a business case for data and clinical submission quality improvement hinges upon the ability to document the pains incurred by identifying errors from day to day. The standard of operation to ensure good quality data and clinical submission are not easy, in fact tedious, but worthwhile and requires leadership and relentless management. The task of segmenting flaws and errors across pharma functions and business units involved with the data and clinical submission is daunting. The impact of data and a clinical submission that lacks quality impacts all pharma and business units from low to high levels of negative perception with FDA and financial projection attributable to "bad data". Reviewing the scale of the data and clinical submission failures based on their corresponding negative regulatory perception, and financial impact will suggest ways to prioritize remediation and "corrective action" and "quality management and change control".

Identifying data and clinical submission flaws, inconsistencies and errors, relies on data quality tools, protocols, processes, procedures and monitoring by an experienced team of quality reviewers and auditors. Data flaws, inconsistencies and errors are not readily seen. So, the process of improving data and clinical submission quality is not an easy task.

However, the challenge in employing the concept of return of investment for justifying the finding of an improvement project to improve quality of data and clinical submission is the ability to monitor, over time, whether the improvements implemented through the project are facilitating positive impacts, for examples, shorter timelines, reduced costs, improved regulatory perception, ease of review, improved credibility with all agencies, enhanced approval perception, reduced time to market, reduced risk management, decreased delays - control surprises.

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