Feature Selection

Overview

Click here for an overview of features available in StudyTRAX.

Things to Consider

Adverse Events

• All of a subject's adverse events are displayed on the Adverse Events tab of the Subject Overview page
• Adverse Events that are not resolved are highlighted red
• A PDF report of all adverse events for the project can be viewed/printed for a desired date range
• Limitations
  • The variables cannot be modified
  • The report cannot be modified
• An alternate option to using the StudyTRAX Adverse Events feature is to create a variable group with your custom variables and attach the variable group to a non-fixed interval

Change Reason

• When a subject's data is modified the user will be prompted to enter a reason for the data change
• All data changes are tracked in an audit log even if Change Reason is not enabled

Double Data Entry

• A Double Data Entry Delta Report displays error rates and discrepancies between primary and secondary entries
• Only primary entry values are exportable through data sets
• The variables to be double data entered are selected
• The subject's which will be double data entered are selected

Medications

• A Medications tab is displayed on the Subject Overview page where all of a subject's medications are visible
• Medications are selected from a list so they do not have to be typed
• Medications that are available for selection must be added or imported into the central list
• Medications in the central list must include:
  • Trade Name
  • Generic Name
  • Code (a unique identifier for the medication)
  • Unit of Measure
• When Medications are entered for a subject they include:
  • Medication Name - selected from the list
  • Begin Date - must be entered in full date format - mm/dd/yyyy
  • End Date - optional but if entered must be in full date format - mm/dd/yyyy
  • Dose - must be entered in the unit of measure specified for the medication in the central list
  • # / Day - must be entered as a whole number although 0 can be used
  • Notes - an optional field
• Data Sets
  • Medication Groups can be created to define dose equivalenc scales for related medications
  • Medication Groups can be exported in one column of a data set
  • Medication Group Dosage and Medication Grouop Exposure (has ever taken) can be exported for a medication group
  • Medication Dosage and Medication Exposure (has ever taken) can be exported for medications that are assigned to the project
    • Has Ever Taken:  Outputs a 0 (No) or 1 (Yes) if the subject has ever taken the medication
    • Dosage:  Outputs the dosage at an encounter based on the begin/end date of the medication and the date of the encounter
• Limitations
  • The subject medication fields cannot be modified
  • Only medications assigned to a project can be exported through data sets

    Medication Groups can be created from any medications in the central list and then exported

• Alternate options
  •  Create a Project Variable Group that is a log of all subject medications
    • The variables can be customized
    • All of a subject's medications will be visible on one form
    • When exporting the data each medication will be in a separate column
  • Create an Encounter Variable Group and assign to a non-fixed encounter
    • The variables can be customized
    • Each medication will be a separate non-fixed interval
    • A subject report can list all of a subject's medications on one report
    • When exporting the data each medication will be in a column
    • When it is expected that subjects will have numerous medications this option will result in many non-fixed intervals
      

Randomization

• Information about the randomization configuration:  Randomization
• Be sure there will be enough subjects to reasonably ensure the distribution across strata blocks are filled when using Stratification Factors
  • In pilot studies the limited sample size typically limits the number of strata that can feasibly be used, maybe 1 or 2 variables at most. 

    The number of strata are multiplicative across variables (e.g., 2 variables with 2 categories each = 4 strata groups)

• Review if there are known confounding factors that need to be controlled
  • The variables should be controlled in the randomization scheme (e.g., smoking status for a study on lung cancer)
  •  Consider the main dependent measure and whether any of the proposed stratification varaibles are 1) markedly related or 2) would differentially interact with the intervention

Screening

Subject Login

Versioning

Electronic Signatures

Examples

Always create the simplest project configuration possible. If you are not sure that your project requires a feature, do not enable the feature as most features can be enabled later. Once a feature is enabled and data is entered, it may not be able to be disabled. However, Randomization and Screening cannot be enabled once subjects are enrolled in the project.