Harvest

1. Harvest Collecting data for a field investigation FETP India

2. Competency to be gained from this lecture Collect data for a field investigation according to standard operating procedures

3. Key issues • Data quality • Field work

4. Data quality • Reliability • Reproducibility/repeatability/precision • Ability of a measurement to give the same result or similar result with repeated measurements of the same thing • Refers to stability or consistency of information • Accuracy • Ability of a measurement to be correct on the average Data quality

5. Reliability and accuracy • Reliable • Accurate • Reliable • Not accurate • Not reliable • Accurate • Not reliable • Not accurate Data quality

6. Seven steps to data collection • Draft question-by-question guide • Train staff members who will collect data • Standardize the data collection procedure • Initiate field work • Control instruments • Debrief to trouble shoot difficulties • Validate Data collection

7. 1. The question by question guide(q-by-q) • Short document to be understood as a guide for field workers • Consider each question, number by number • Provide guidance as to how the data should be collected • Used as a road map for good data collection • Drafted initially • Revised as issues arise and are addressed Data collection

8. Example of q-by-q • Question 6 (Housing): • Observe the house and note if made of mud or bricks • Question 12 (Household income) : • Identify all the person with financial income in the household • Estimate each source of income • Sum up to generate household income Data collection

9. 2. Train field workers • Select good, experienced field workers • Present the study and its objectives • Slide presentation • Distribute the q-by-q • Walk people through the q-by-q • List tasks to be conducted • Answer questions • Simulate interviews within the team Data collection

10. 3. Standardize data collection • Interviewers • Take field workers by teams in the field • Conduct interviews as a small group • Note issues that may come us, resolve them as a group • Continue until the procedure is clear to everyone • Instruments • Calibration, standardization Data collection

11. 4. Field work • Send field workers by team of at least two persons • Interviewer (Speak the local language) • Note taker • Initiate data collection • Be available to answer questions • Visit teams in the field • Do not press for quick completion Data collection

12. 5. Checking the instruments • Each team checks the instrument before leaving the household • Cross check: The one who did not fill checks • The supervisor checks the instruments before leaving the location • All take responsibility for the instrument: • Names and signatures • Investigator checks instruments as they come Data collection

13. Checks to conduct • Completeness • Did the field worker fill all items? • Readability • Is the writing readable? • Consistency • Do the answer make sense? • Is there internal consistency? Data collection

14. Auto-coding • Q.25: Where did you go when your child had diarrhoea? • Hospital • Public clinic • Private clinic • Pharmacist Data collection in the field 2 Coding right after field work Data collection

15. 6. Debrief to trouble shoot difficulties • Regular meetings • Evening or morning • Facilitate a discussion about • Issues identified • Clarification needed • Make note of decisions on the q-by-q if needed Data collection

16. 7. Validate • Select a number of study participants at random • Conduct a second interview • Compare results • Debrief discrepancies with: • Field worker if individual issue • Group if general issue Data collection

17. Take home messages • Understand the concepts of data quality • Supportive supervision and team work are key to good quality data collection