1. Epi 202: Designing Clinical Research Data Management for Clinical Research Thomas B. Newman, MD,MPH Professor of Epidemiology & Biostatistics and Pediatrics, UCSF September 6, 2011 1

2. Outline n Data management steps n Advantages of database vs spreadsheet entry n REDCap demonstration n Take-home message: Pretest should include data entry and analysis 2

3. Data Management Steps n Data collection form design n Data capture n Data entry n Data cleaning n Then can do data analysis 3

4. Traditional Paper method n Data collection form design -- Word n Data capture – Pen n Data entry -- keyboard transcription into Excel n Data cleaning -- painful 4

5. Questionnaire from DCR 2009 5

6. Oophorectomy ID oophe- rectomy 204no 205yes 207no 208no 209no 211no 212yes 214no 215no 216yes (one) 217no 218no 219no Advantage of paper form: ability to write in answers you had not anticipated Subject might leave it blank or guess if forced to chose 6

7. Race coding IDrace 204black 205hispanic 207Asian 208white 209latina 211white 212asian 214white 215white 216black 217black 218hispanic 219white n Problems –Free text for “other”: hispanic, latina –“Asian” and “asian” are different values for a string variable 7

8. Weight change IDrace weight changegain/lose 204black40loose 205hispanic35gain 207Asian2blank (+/-) 208white10gain 209latina5gain 211white0lose 212asian0 214white15gain 215white10loose 216black25loose 217black0 218hispanic15loose 219white 5-10 poundsloose 8

9. Data cleaning before transcription- study staff Different color ink Person making changes identified 9

10. Data cleaning (Stata example) replace race = “Asian” if race == “asian” replace weightchange = 7.5 if weightchange == “5-10 pounds” generate weightgain = real(weightchange) 10

11. Exercise ID exercise type exercise freqency 204walking2-4times/week 205stretch/walk2-3 days/week 207walking3x 208Curves 3-5 x/week 209bikingevery day 211walking 212walking2x/week 214 215 aerobic- resistant5-6days/week 216walking2x/week 217 218 219blank These variables will be hard to analyze. This is what we are trying to avoid. 11

12. Advantages of paper n Rapid data entry anywhere n Readily understood n Permanent record n Allows ready annotation 12

13. Disadvantages of paper n No immediate quality control n Branching logic harder n Data entry required n Allows you to postpone thinking about data analysis when you should be thinking about it now! 13

14. Consider data analysis early n Restrict options n Provide range and logic checks n Include coding on the paper form n PRETEST data entry and analysis! 14

15. Data Dictionary n Variable name n Type of variable (binary, integer, real, string, etc.) n Variable label (longer name) n Value labels (e.g., 0 = No, 1 =Yes) n Permitted values n Notes 15

16. Research Electronic Data Capture (REDCap) n Design survey or data collection form n Creates data dictionary n Can track subjects and responses n Exports to statistical packages n Available with MyResearch account n Other options: Access (PC), Epi-Info (PC), FilemakerPro 16

17. REDCap demo 17

18. Home Page 18

19. My Projects 19

20. Project Setup 20

21. Online Survey Designer 21

22. Add New Field 22

23. New Question added 23

24. REDCap Creates a Stata do file clear insheet participant_id redcap_survey_timestamp redcap_survey_identifier mas_or_ticr want_attend_review dates_available___1 dates_available___2 dates_available___3 dates_available___4 field comments survey_complete using "DATA_DCR_FINAL_REVIEW_SESSION_SURVEY_COPY_2_TNEWMAN_2011-08-10- 22-39-34.CSV", nonames label data "DATA_DCR_FINAL_REVIEW_SESSION_SURVEY_COPY_2_TNEWMAN_2011-08-10- 22-39-34.CSV” label define mas_or_ticr_ 1 "No" 2 "Yes ===> Exit this survey" label define want_attend_review_ 1 "No ====> Exit this survey" 2 "Yes" label define dates_available___1_ 0 "Unchecked" 1 "Checked" label define field_ 1 "Clinical pharmacology" 2 "Community medicine" 3 "Dentistry" 4 "Dermatology" 5 "Emergency medicine" 6 "Endocrinology" 7 "Epidemiology/environmental health" 8 "Family medicine" 9 "Global health" 10 "Hospital medicine" 11 "Infectious disease" 12 … label variable mas_or_ticr "Are you in either the Masters Degree in Clinical Research program or the ATCR (Advanced Training in Clinical Research) program?" 24

25. Most Important Messages 25

26. Questions and comments 26

27. Extra slides 27

28. Main decisions n Electronic capture vs paper n Optical form reading vs keyboard transcription n Enter data into database, spreadsheet or statistical package Highly recommended! 28

29. Advantages of database vs Spreadsheet n Restricts choices n Error checking n Can track study progress, produce reports, export to statistical package n Safer – harder to accidentally alter data 29

30. (use microphone or repeat) 30