Information and Data Planning

It ain't rocket science, it is just critical.

Call Clarence Potter, 6-4802, GCRC Systems Manager, to discuss. Even if you do not use the GCRCnet for storage of your data, the systems manager is available to help you in defining or reviewing applicable data requirements. We want to make sure that your data is well cared for.

1. Information / data requirements to meet the statistical goals and capture information to support future needs. Information is everything you use. Data is what you process. You need to plan for both. Be sure to include all of the information that you may need or collect, even assess the importance of and procedures for paper forms. Need to know the number of patients and general volume of expected data per patient.
1. Personal Information - contact information, demographics, primary physician and phone/ address, alternate contact person (friend).
2. Consent and phone interview data, be sure to keep track of the excluded patients, their demographics, and reasons excluded.
3. General medical history and disease history worksheets
4. Study data - labs, questionnaires, doctor and professional narrative comments
2. Information / data collection methods to capture data and enter it into electronic medium. Electronic medium improves your ability to manipulate it, control it, and distribute it.
1. Security of data. Controlled access to data, so that it cannot be tampered with or taken.
2. Patient Confidentiality. Identifying personal information is segregated from study data. Study data has a study ID.
3. Forms, forms, forms - well designed and keep them forever. Make a form to keep track of the other forms.
4. Software for making forms, for database management, and for statistical analysis- Access, FoxPro, EpiInfo, Excel, SAS, etc., etc.
5. Software design - Do you need to build some custom software for data entry or processing?
6. Double entry to ensure accuracy
7. Define the correction process
8. Review and audit of collected data
9. Logic (edit) checks for entering data, verify that calculated data provides the answers you'd expect.
10. Web based access to databases
11. Data dump and conversion from lab or other system.
12. Telnet / ftp / email from other sites.
3. Data management methods for holding the data and allowing access to it, after it is entered.
1. File access, location,
2. Who will enter the data, who will verify the data?
3. Network accessible
4. Backup and restore plan
5. Archive and close out requirements.
4. Prepare data for analysis
1. Identify and segregate data
2. Label each data record. For analysis systems, you need unique keys that may not have been implemented in the raw data storage. Will the analysis system need to distinguish between multiple patients on multiple days with the same assay run on multiple times on multiple samples. Do you need individual data points or an average for the sample. Patient study ID, date, and time of procedure or blood draw.
3. Convert data for analysis platform.
4. Transfer data to analysis platform.