LONGITUDINAL OUTCOMES OF GASTROINTESTINAL SYMPTOMS IN CANADA (LOGIC): KEY FACTORS FOR AN EFFECTIVE PATIENT RETENTION IN OBSERVATIONAL STUDIES

Main Article Content

R Balshaw
S Khorasheh
M Barbeau
S Kelly
S Flynn
O Heisel
CR McBurney

Keywords

IBS, recruitment, observational studies, patient retention, Canada

Abstract

Background


Longitudinal Outcomes of GastroIntestinal symptoms in Canada (LOGIC) is an ongoing study on irritable bowel  syndrome  (IBS)  treatment  patterns  and  health  outcomes  in routine  Canadian  clinical  practice. Advancements in understanding IBS, a chronic multifaceted GI disorder, may be possible through methodical observational studies. The objective of this paper is to describe site recruitment techniques and extensive subject follow-up methodology used to facilitate a high return rate of questionnaires from this population-based study of subjects with IBS.


 Methods


Invitation letters along with protocol synopses and preliminary site assessment questionnaires were faxed to potential sites across Canada. There were 1,556 subjects enrolled in this study from general practitioner sites (GP) and specialist sites (SP) in Canada. Subjects were compensated for the return of questionnaires reporting symptoms, quality of life, productivity, healthcare and resource utilization at baseline, Month 1, 3, 6, 9, and 12. Upon the return of questionnaires, subjects received thank you cards which included a reminder of the next questionnaire’s due date. If subject questionnaires were not received within 2 weeks after the due date, the subjects received a reminder letter in the mail.


 Results


The methodology in the LOGIC study allowed for a high patient questionnaire return rate (89%) through extensive subject reminders and follow-up. Subject participation throughout the study was not found to be linked to study site size or type (GP or SP).


 Conclusion


Questionnaire   based   observational   studies   may   benefit   from   focusing   resources   on   increasing questionnaire return rates to effectively maintain data reliability and also reduce non-response bias

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