Planning and Budgeting for Data Management in a Clinical Research Study

1. Planning and Budgeting for Data Management in a Clinical Research Study Michael A. Kohn, MD, MPP 4 February 2003

2. Outline • Assignment 3 Review • Guidelines for Research Databases • Loose Ends: Look-up Tables, Modules/Macros • Planning and Budgeting for Data Management in a Research Project

3. Assignment 3 Lab 3: Exporting and Analyzing Data 1/28/2003 Determine if neonatal jaundice was associated with the 5-year neuropsychiatric scores and create a table, figure, or paragraph appropriate for the “Results” section of a manuscript summarizing the association. Write a sentence or two for the “Methods” section on inter-rater reliability. (Use Bland and Altman, BMJ 1996; 313:744) Send assignment to ahigh@psg.ucsf.edu by 2/3/2003.

4. Browner on Figures Figures should have a minimum of four data points. A figure that shows that the rate of colon cancer is higher in men than in women, or that diabetes is more common in Hispanics than in whites or blacks, [or that jaundiced babies had higher IQs at age 5 years than non-jaundiced babies,] is not worth the ink required to print it. Use text instead. Browner, WS. Publishing and Presenting Clinical Research; 1999; Williams and Wilkins. Pg. 90

5. Browner on 3-D Figures Three dimensional graphs usually are not helpful. Browner, WS. Publishing and Presenting Clinical Research; 1999; Williams and Wilkins. Pg. 97

6. What Have You Learned? • The meaning and importance of the terms “normalization”, “primary key”, and “foreign key”. • The difference between a flat-file database, and a normalized, multi-table relational database. • A little bit of Microsoft Access 2000

7. Guidelines for Data Management in Clinical Research 1. Establish the database tables, their rows and columns, and their relationships correctly at the outset.   A poorly organized database makes data maintenance and retrieval nearly impossible. Make sure the data are normalized. The data structures should never require duplicate data entry or redundant storage. Sometimes it helps to start with the data collection forms, but remember, you do NOT need one table per data collection form. In the labs you learned that one form can combine data from several tables. And data from one table can appear on several forms.

8. Guidelines for Data Management in Clinical Research 2. Establish and follow naming conventions for columns and tables. Short field names without spaces or underscores are convenient for programming, querying, and other manipulations. Instead of spaces or underscores, use “IntraCaps” (upper case letters within the variable name) to distinguish words, e.g. “StudyID”, “FName”, or “ExamDate”. Table names should be singular, e.g. “Baby” instead of “Babies”, “Exam” instead of “Exams”.

9. Guidelines for Data Management in Clinical Research 3. Store raw data not calculation results. (e.g., store dates and times; calculate intervals.) Storing a patient’s birth date allows calculation of his or her exact age on the date of a particular measurement. Correcting an error in the birth date, does not require correcting any other fields (because age is calculated, not stored in a field). In general, one should store the raw data fields, not the calculated numbers based on these fields. In the case of extremely complex calculations, it is acceptable to store the calculated field along with the raw data fields, and remember to update the calculated field with the raw data fields.

10. Demonstration • Age Example Query versus Age Example Table

11. Modules and Macros • Age function

12. Guidelines for Data Management in Clinical Research 4. Obtain baseline demographic and clinical information about members of the study population from existing computer databases. Avoid re-entering data which are already available (in digital formats) from other sources. In the JIFee Study, the patient demographic data and contact information are obtained from the hospital database. Computer systems can almost always produce text-delimited or fixed-column-width character files that the database management system can import.

13. Guidelines for Data Management in Clinical Research 5. Minimize the extent to which study measurements are recorded on paper forms. Enter data directly into the computer database or move data from paper forms into the computer database as close to the data collection time as possible. When you define a variable in a computer database, you specify both its format and its domain or range of allowed values. Using these format and domain specifications, computer data entry forms give immediate feedback about improper formats and values that are out of range. The best time to receive this feedback is when the study subject is still on site.

14. Guidelines for Data Management in Clinical Research 6. Follow standard data entry conventions. Several conventions for data entry and display have developed over time. Although most users of screen forms are not aware of these conventions, they have come to expect them subconsciously. For example, a series of mutually exclusive, collectively exhaustive choices is usually displayed as an “option group” consisting of several different “radio buttons”, whereas choices which are not mutually exclusive are displayed as check boxes. N.B. An “option group” of mutually exclusive choices is a single column or field. A group of N check boxes represents N yes/no fields.

15. Use check boxes when options are not mutually exclusive. (5 fields) Use radio buttons when options are mutually exclusive. (1 field) Computer chart abstraction form showing two common data entry conventions.

16. Demonstration Option group for examiner’s medical specialty

17. Demonstration Field types are not limited to numbers, text, dates. You can put an “object”, such as a Word document or a photo, in a field Memo fields in the Infant Jaundice Database Word Document Fields on the “Class” form of the ATCR Student Database Photograph fields in the ATCR Student Database

18. Guidelines for Data Management in Clinical Research 7.      Back up the database regularly and check the adequacy of the back up procedure by periodically restoring a file from the back up medium.

19. Four Types of Research Database • Combination of paper files, Excel spreadsheets, and direct keyboard entry into the statistical analysis package. • Desktop multi-table relational database.* • Client-Server multi-table relational database. • Internet database server. * Best fit for most people in this class

20. Desktop DBMS The processing of records is done by the desktop. The server simply stores files (file server). Microsoft Access Claris Filemaker Pro Paradox Microsoft Visual FoxPro Dataease

21. Client-Server DBMS The processing of records is done by the server. The desktop manages the screen, but passes queries on to the server. (Just to confuse things, MS Access can be a client for SQL Server, and other enterprise systems. The ultimate in “thin” clients is a browser (Internet Explorer). In this case, the server is an intranet or internet database server.) Microsoft SQL Server Oracle Informix Sybase

22. File Server SQL Server Server thinks too! Workstation does all the “thinking”… Client Machine Client Machine File Server vs. Client Server

23. Advice on Building a Desktop Multi-Table Relational Database for your Study • Build it yourself using what you learned in this class—with occasional help from a database expert • Budget $500-$1000 per month out of your grant for database consulting during the design phase. • Take advantage of your departmental resources. • Take advantage of campus resources. • Don’t confuse database development with network administration and systems management.

24. But does not become more complex with time 6. Automation 5. Data Flows 4. Dynamic Documents 3. Structuring Input 2. Identifying Experts Development is relatively slower, more complex 1. Natural Systems The Allure of the “Simple Solution” System Capabilities Development is “simple” and fast at first, but becomes very complex later Time

25. Costs There is no adequate, on-campus resource for database design consulting. (If there were, it would cost $100/hour just like biostatistical consulting.) Independent database consultants also cost $100+ per hour.

26. Costs The JIFee Study developed a comprehensive database for study administrative data as well as results. They have a full time project coordinator and spent about $10,000 on database consulting. Total cost of the JIFee Database in time and money was at least $25,000.

27. Departmental Resources • Your department should provide you with a networked desktop computer, as well as network support, server access, and database hosting. However, the departmental computer person will NOT be able to help you with database design or development. • System administrators do not and cannot build database management systems.

28. Campus Resources • GCRC/PCRC Informatics Lab (Requires an approved CRC protocol and approval from CRC Director) • Independent consultants. • Other campus resources? Library? PSG?

29. Data Management Protocol • General description of database • Data collection and entry • Error checking and data validation • Analysis (e.g., export to Stata) • Security/confidentiality • Back up

30. General Description of Database • DBMS, e.g. MS Access XP • # of dynamic tables • # of static “lookup” tables • # of forms • # of reports An appendix should include the relationships diagram, the table names and descriptions, and the field names and descriptions (data dictionary).

31. Data Collection and Entry • Import baseline data from existing systems • Import lab results, scan results (e.g. DEXA), holter monitor data, and other digital data. • For each form, who will collect the data? • Collect onto paper forms and then transcribe? Enter directly using screen forms? Scannable forms?

32. Error Checking and Validation • Database automatically checks data against the range of allowed values. • Periodic outlier detection. (Outliers still within the range of allowed values.) • Calculation checks • Is double data entry really needed ?

33. Analysis • How will you get the data out of the database?

34. Security/Confidentiality • Keep identifying data (name, SSN, MRN) in a separate table. • Link rest of DB to this table via a Subject ID that has no meaning external to the DB. • Restrict access to identifying data. • Password protect at both OS and application levels. • Audit entries and updates.

35. Back ups • Ask your system person to restore a file periodically. This tests both the back-up and restore systems.

36. Assignment Class session 5 (not a lab): Planning and Budgeting for Data Management 2/4/2003 Write a one-page data management section for your research study protocol and create a budget for data management. If you do not have your own research study protocol, write the data management section and create a budget for the fictional Infant Jaundice Study protocol. We can compare your budget with the real budget of JIFee. Send assignment to ahigh@psg.ucsf.edu by 2/10/2003.

37. Data Management Advice from New Investigators

38. Jon Zaroff At the time I was in ATCR, I knew it was critical that I get reasonably comfortable with Access and get some expert advice (yours!). I thought carefully about going with paperless data entry (directly into Access on a laptop) and I think this was a very good idea; reducing entry errors and increasing efficiency. This led to thoughts about the need to back-up the data well (my database gets backed up at two different UCSF campuses and at my home - hopefully one computer will survive a really big earthquake). Protecting patient confidentiality is also a concern with this approach so all of my computers are password protected. The interaction between Access and Stata has worked very well for me. Regarding the budget, I have invested in Office Professional for all of my computers and have gotten advice (yours!) for free so far. I am hoping that my next grants will include an informatics budget.

39. Cathy Lomen-Hoerth My advice is to start simple and start using it right away.  It was through using the database-many people using the database-that we figured out what we wanted.  I would budget $1000/month for consulting to design a database.  If funds are very limited, then set up a very simple database.  Taking a class on Access or reading a book is helpful before starting to understand what a database can do.  Please feel free to give my number /e-mail out to anyone who wants to talk further.  I paid for the consulting costs from my K23 NIH grant, which has a budget for consulting.  cathylh@itsa.ucsf.edu

40. Roberta KellerYvonne WuJim QuinnPetra LiljestrandMark Pletcher