Collecting and Organizing Data (for ease of analysis and good results!)

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Collecting and Organizing Data (for ease of
analysis and good results!)

• Annie N. Simpson, MSc.
• Biostatistician

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(No Transcript)
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Data Collection Considerations

• Should be investigated when your study is being
  planned
• Should be implemented before (or shortly after)
  subjects are being recruited
• Computational collection tools should be
  proportionate to the size of your study
• (size number of subjects, number of
  forms/collection instruments)
• A data Collection Schedule is often the best
  place to start!

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Case Report Forms

• If available use a previously used and vetted
  form (i.e. HAM-D)
• All forms in a case book for a study should have
  the same header information
• Header Information should capture, patient id,
  patient initials (if commonly used), visit number
  and or type, time of visit (if collecting things
  multiple times over 1 visit)
• Remember that you are creating forms that may be
  used more than once depending on your study
  design, so you need to know how to differentiate
  visits etc.

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In Protocol
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For Data Collection During Study!
Can even be used as a face page for each
subjects binder, where each visit/form can get
checked off!
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Steps that I follow when I have a new study (from
my perspective)

• Create and review with the Team (this is a very
  long but worthwhile meeting)
• Updated Form Based Data Collection Schedule
• Complete Blank Case Report Form Book
• Go through each page of the CRF book with your
  team and ask questions (let them ask) that are
  not clear to everyone (include your
  statistician!).
• Review each persons responsibilities/roles
• Review the current timeline

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How to electronically capture your data to a
spreadsheet

• Not every form HAS to be entered, think about
  whether the information will be analyzed or is it
  for study coordination
• Patient Identifier number should be a column on
  every spreadsheet and should be set up EXACTLY
  the same (same length and type)
• Usually one spreadsheet per collection form
• Usually laid out vertically, i.e. one row for
  each patients for each visit time
• NEVER skip filling down the columns!

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Examples of bad data layouts

• And good ones ?

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How to think about how to begin analysis? 1st
clean you data!

• Dont forget to first check your Ns for
  correctness, are they what you expect (for each
  form!).
• Also examine the extreme values (max mins) for
  each of your variables as the simplest way to
  check for incorrectly entered (i.e. dirty) data.
• Always have original source documents (when you
  can) and dont neglect checking between them and
  your spreadsheets!

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How to think about how to begin analysis?

• Think about what and how your Table 1 will look
• Should the table be describe the total sampleor
  perhaps by gender (depends on the question or
  focus of your research)
• Can use any simple software to do this
• Excel, SPSS, Minitab
• For all continuous vars get N, Mean, STD
• For all categorical vars get N, , Total Ns

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Basic Analysis of Continuous Response Variables

• Numerical Descriptives
• Mean
• Median
• Mode
• Variance
• Range

• Graphical Descriptives
• Boxplots
• Scatterplots
• Histograms

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Basic Analysis of Categorical Response Variables

• Numerical Descriptives
• Frequencies
• Percents/Proportions

• Graphical Descriptives
• Bar Charts
• Pie Graphs (not so common in biomedical research)

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Other data considerations

• Large multi-center clinical trials will usually
  have a centralized data collection and
  coordinating center.
• You, as a clinical site, would be responsible for
  error correction with source documentation.
• Training of entry/coordination staff is very
  important (ex 5 year study data collected, at
  the end statistician got the data and nowhere was
  the study group collected, and it wasnt on
  source documents either!)
• Your study is only as good as the data that you
  collect, pre-planning is the key.