Strategies to Maximize Data Collection Response Rates in a Randomized Control Trial Focused on Children with Medical Complexity.
BACKGROUND
Obtaining complete and timely subject data is key to the success of clinical trials, particularly for studies requiring data collected from subjects at home or other remote sites. A multifaceted strategy for data collection in a randomized controlled trial (RCT) focused on care coordination for children with medical complexity is described. The influences of data collection mode, incentives, and study group membership on subject response patterns are analyzed. Data collection included monthly healthcare service utilization (HCSU) calendars and annual surveys focused on care coordination outcomes.


METHODS
One hundred sixty-three families were enrolled in the 30-month TeleFamilies RCT. Subjects were 2-15 years of age at enrollment. HCSU data were collected by parent/guardian self-report using mail, e-mail, telephone, or texting. Surveys were collected by mail. Incentives were provided for completed surveys after 8 months to improve collection returns. Outcome measures were the number of HCSU calendars and surveys returned, the return interval, data collection mode, and incentive impact.


RESULTS
Return rates of 90% for HCSU calendars and 82% for annual surveys were achieved. Mean return intervals were 72 and 65 days for HCSU and surveys, respectively. Survey response increased from 55% to 95% after introduction of a gift card and added research staff.


CONCLUSIONS
High return rates for HCSU calendars and health-related surveys are attainable but required a flexible and personnel-intensive approach to collection methods. Family preference for data collection approach should be obtained at enrollment, should be modified as needed, and requires flexible options, training, intensive staff/family interaction, and patience.
1 Department of Laboratory Medicine and Pathology/Health Informatics, University of Minnesota , Minneapolis, Minnesota.
Stanley M
SM
Finkelstein
1 Department of Laboratory Medicine and Pathology/Health Informatics, University of Minnesota , Minneapolis, Minnesota.|2 School of Nursing, University of Minnesota , Minneapolis, Minnesota.
Margaret
M
Celebrezze
1 Department of Laboratory Medicine and Pathology/Health Informatics, University of Minnesota , Minneapolis, Minnesota.|3 Gillette Children's Specialty Healthcare , St. Paul, Minnesota.
Rhonda
R
Cady
4 Clinical and Translational Science Institute, University of Minnesota , Minneapolis, Minnesota.
Scott
S
Lunos
2 School of Nursing, University of Minnesota , Minneapolis, Minnesota.
Wendy S
WS
Looman
D000293:Adolescent; D002648:Child; D002675:Child, Preschool; D015897:Comorbidity; D003266:Continuity of Patient Care / Q000706:statistics & numerical data*; D003625:Data Collection / Q000379:methods*; D019988:Children with Disabilities; D005260:Female; D006296:Health Services / Q000706:statistics & numerical data*; D006699:Home Care Services / Q000706:statistics & numerical data; D006776:Hospitals, Pediatric; D006801:Humans; D008297:Male; D018670:Monitoring, Ambulatory; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D011795:Surveys and Questionnaires; D017216:Telemedicine / Q000379:methods*
home health monitoring; information management; telehealth; telenursing