Clinical Research Courses Ensure Data Quality while Optimizing a Clinical Trial Management System

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Clinical Research Courses Ensure Data Quality
while Optimizing a Clinical Trial Management
System
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(No Transcript)
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INDEX

• Significance of Data Quality
• Characteristics of Data Quality
• Prioritize their needs first
• Assessing data collecting and monitoring
  processes
• 3. Certain Tools that ensure ongoing success

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Significance of Data Quality

• Data Quality is of great significance for
  clinical research professionals when it comes to
  optimizing a current system or implementing a new
  clinical trial management system.
• It is essential to create processes that result
  in accurate, timely and complete data. As a
  result, it leads to more efficient workflows and
  minimized anxiety in reporting.
• However, quality data is not an impromptu thing,
  it is the outcome of a lot of planning and
  execution.
• There are several characteristics of data quality
  that are kept in mind by clinical research
  professionals while capturing data. These are
  taught to students while they are enrolled in
  clinical research courses.

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Characteristics of Data Quality

• There are seven diverse characteristics that
  define data quality. They are
• Accuracy and Precision
• Legitimacy and Validity
• Reliability and Consistency
• Timeliness and Relevance
• Completeness and Comprehensiveness
• Availability and Accessibility
• Granularity and Uniqueness

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Prioritize their needs first

• They could do so by doing a cost benefit analysis
  which determines whether certain data points are
  worth being tracked. While prioritizing specific
  data points, here are some questions that should
  be asked
• Is the data relevant to multiple areas.
• Does it support large organizational goals.
• Does the data gathered require other data to be
  present.
• When clinical research professionals ask the
  above questions, they will not only be able to
  prioritize goals first.

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Assessing data collecting and monitoring processes

• After the process of prioritizing data points,
  clinical researchers should review their methods
  for data gathering and monitoring.
• Inferior data is more dangerous for clinical
  research organizations than no data at all.
  Therefore, it is vital for organizations to start
  these processes before they go live.
• Monitoring needs to be clearly defined both from
  a personnel perspective that is who is
  responsible for data integrity and a process
  perspective i.e. What tools and the reports does
  the person use to make certain that processes are
  being followed.
• This is also the perfect time to review the
  processes of other teams in the organization.

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Certain Tools that ensure ongoing success

• The third step after prioritizing goals and
  reviewing processes is to give research staff the
  tools to efficiently maintain these processes.
• Tools could help identify missing data for both
  protocols and subjects.
• These tools would help you fulfill the goal of
  prioritizing important needs and fixing those
  errors first.
• To gain extensive knowledge on maintaining
  accurate data, get in touch with the best
  clinical research training institute in Pune.

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• Thank You
• For more details https//www.technobridge.in/clin
  ical-research/clinical-research-courses-scope-care
  er-salary-syllabus-eligibility/