Tag Archives: anayansigamboa

Oracle Clinical – How to Use Study Design

Study Design in OC is the process of setting up the protocol for the study. This includes:

  •  creating a record for the study
  • creating patient positions or placeholders
  • creating events or study visits
  • assigning sites or locations where data is collected
  • assigning patient positions to the site

Remember that the required study planning objects, sites and investigators must be created prior to the Design Process being completed.

It is a good idea to review all protocol and study related documentation prior to creating the study to make sure you have all of the necessary information but you can always change the Design elements at any time except for the study name.

Once the Study Design is completed, you can move to the next module: The Study Definition (creating CRFs) and develop Procedures (Edit Checks, derivations).

Tips:

  •  Records for the new studies are created in the Easy Design module (Design, Studies, Easy Design)
  • Verify that the required Planning Objects exist for the study
  • In the Easy Design form create the study. Enter the study name or number, version and study description/title. Some parameters are optional. Once you click save, the system will prompt you to choose whether the study requires Pass 2 Data Entry.
  • Most Study Design parameters may be changed except fr the Study Name

Study Design Key Terms:

  • Program: Code (name) for the compound being investigated
  • Protocol: Document describing the plan of action for a study
  • Project: Code (name) for the indication under investigation
  • Study: The name for the Clinical Study
  • Organizational Unit: Code (name) for the unit responsible for the study
  • Event: Clinical Planned Event or Visits
  • Region: Code (name) of the location where the study is managed
  • Patient Positions: Identifier for a participant in a study
  • Site: A location where all or part of the study is conducted
  • Investigator: Primary researcher/clinician for the study at a site

Study Design – Events

• Study timeline is used to identify when data is collected or for tracking purposes (missing or overdue DCMs)

• Consists of one or more intervals and one or more events (visits)

• Timeline consists of intervals that are subdivided into events. By default each study is pre-populated with two defaults intervals that can be used in creating events.

• To create intervals, select the study in the Easy Design module and click on Intervals. Intervals are defined by a Phase Name, Short Name, Phase Type, Blind type (single, double, etc) and a minimum and maximum duration. The duration is used to calculate when the interval is expected to take place within the study.

• To create events, select the study in the Easy Design module and click on Events. Create all the events (visits) in which data will be collected during the course of the study. Events are defined by Event Name, Interval, Visit Number (the order o f the event is expected to occur) and minimum and maximum Offsets from the Interval Start.

• Time calculations (event offsets and interval durations) are useful only for descriptive purposes and for determining if expected CRFs are Missing or Overdue.

If this functionality is not required then this information is not useful in the execution of the study.

Study Design – Patient Positions

• Patient Positions are the placeholders for the actual partaker in the study. Each patient for whom data will be collected must have a unique patient position within that study.

• Can be crated in blocks or one-by-one.

• Patients can be of several types: Screening, Normal or Replacement.

For general patients, use NORMAL.

Replacements are used in Randomization.

• To create patient positions, select the study in the Easy Design module; click on Create PP. Create the required patient position for the study by entering starting and ending numbers.

• Duplicates numbers are not allowed within a study.

Study Design – Sites and Investigators

• Sites are the locations where the data is collected and investigators represent the medical researcher at the site responsible for the patients. It can be used in multiple studies.

• Each study requires a minimum of one site assigned to it with an investigator assigned to that site.

• Create Sites in the Sites module. A site is defined by a Code, Name, Phone Number, Address, City, State, Country, and Postal Code. Site code must be unique.

Design ->Investigators and Sites -> Sites

Create Investigators in the Investigators module. An Investigator is defined by a Investigator Code, First Name, Last Name, and Phone Number. Other information is optional. Investigator code must be unique.

Design -> Investigators and Sites ->Investigators

• Assign an Investigator to each site. There can only be one active Investigator assigned to a site at any time. If a second Investigator is assigned to the same Site, the system automatically enters a Termination Date for the current Investigator.

• Assign Patient Positions to the Study Sites. Patients may be optionally enrolled in the study. Enrolling patients can be performed in the Enrollment module.

Tip: The system only requires the enrollment date to consider a patient “Enrolled”, however, the lab range system will not work without the entry of the patient’s birth date and sex.


Anayansi Gamboa has an extensive background in clinical data management as well as experience with different EDC systems including Oracle InForm, InForm Architect, Central Designer, CIS, Clintrial, Medidata Rave, Central Coding, OpenClinica Open Source and Oracle Clinical.

Disclaimer: The legal entity on this blog is registered as Doing Business As (DBA) – Trade Name – Fictitious Name – Assumed Name as “GAMBOA”.

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A QC Plan for A Quality Clinical Database

Before a clinical database can be locked, data management run a set of qualify control checklists to ensure that quality is built into the clinical database.

This process is also known as ″estimated error rate″ which is a calculation of an error occurred during the course of the clinical trial, from the data management point of view.

The formula is:

Percentage error rate = # of errors detected/total #’s of items checked x 100

Depending upon the tool you are using, i.e. OC or Clintrial, you will need to count and determine the number of items for a particular dataset. 80% of the time, SAS tool is used for this step. Other times, a manual count is required.

Not every issue or discrepancy found is considered an error. This is described in a section of the QC plan. Each Sponsor or CRO is different. For example, misspelling mistakes or changes in punctuation are not considered an error. Also, your statistical team member should be able to identified those items considered ‘critical’ for the statistical analysis.

Common panels/items are: Demography (date of birth, sex, race), lab data, randomization data, Study Conclusion/final status table.

When a clinical database is considered 80-90% clean, the data manager will randomly select a set of patients, as discussed with the statistical leader for the study, to be included in the final QC.

Sample size = √n + 1 where n=the number of patients in the study.

If a study has 34 patients and 1 study site then √34 = 5.83, 5.83 + 1= 6.83. We also determined that only 20% of the patient enrolled will be QC’d therefore, 7 case report forms will be included in the final review.

In order for a clinical data to be considered acceptable, the error rate must be below 0.1% or less.

In conclusion, a good QC plan identify what quality control tasks are needed and that all activities are completed in the most effective way through out the project.


Anayansi Gamboa has an extensive background in clinical data management as well as experience with different EDC systems including Oracle InForm, InForm Architect, Central Designer, CIS, Clintrial, Medidata Rave, Central Coding, OpenClinica Open Source and Oracle Clinical.

Disclaimer: The legal entity on this blog is registered as Doing Business As (DBA) – Trade Name – Fictitious Name – Assumed Name as “GAMBOA”.

Audit Record Status in Clintrial

Did you ever wonder what the various status designations used for records in the audit table mean?

Audit table record status is contingent on:

  • The record’s status at the time it was modified or deleted.
  • The database table where the record was stored (update or data).

Audit Table
Status prior to change: Table location prior to change: Audit table code if modified: Audit table code if deleted:
Entered Update -60 -61
Verification Error Update -50 -51
Verified Update -40 -41
Validation Error Update -30 -31
Validated Update -20 -21
Validated Data -10 -11

Did You Know?

Did You Know? »

You can hide temporary SAS datasets by adding a prefix of “_to” and your temporary datasets will not show up in the Work folder in the Explorer window.

e.g. work._toEDC

Remember, temporary datasets are removed at the end of your SAS session.

data work._toPK;
set pk;
rename pkcolt=tm01;
where pkhrs=0.1 ;
run;


Anayansi Gamboa has an extensive background in clinical data management as well as experience with different EDC systems including Oracle InForm, InForm Architect, Central Designer, CIS, Clintrial, Medidata Rave, Central Coding, OpenClinica Open Source and Oracle Clinical.