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Analytic Challenges Arising from the STOP CRC Trial: Pragmatic Solutions for Pragmatic Problems
William M Vollmer1, Beverly B Green2, Gloria D Coronado1
1Kaiser Permanente, Center for Health Research.
EGEMS (Washington, DC)
|January 22, 2016
Summary
This study addresses challenges in pragmatic trials by adjusting intervention timelines and measurement windows to improve colorectal cancer (CRC) screening rates. Strategies were developed to mitigate contamination and synchronization issues in electronic medical record (EMR)-driven interventions.
Area of Science:
- Clinical Trials
- Public Health
- Health Services Research
Background:
- Pragmatic trials present unique analytical challenges due to real-world implementation constraints, differing from traditional efficacy studies.
- Quality control in pragmatic trials can be less stringent, necessitating careful consideration of analytic methodologies.
- The STOP CRC trial aimed to increase colorectal cancer (CRC) screening rates in safety net clinics using electronic medical record (EMR)-driven strategies.
Purpose of the Study:
- To evaluate the effectiveness of automated, EMR-driven strategies for increasing colorectal cancer (CRC) screening rates.
- To address and mitigate analytical challenges arising from intervention rollout and measurement window synchronization issues in a cluster randomized trial.
- To provide insights into managing implementation challenges in pragmatic trial designs.
Main Methods:
- A cluster randomized trial (STOP CRC) was conducted in safety net clinics.
- The intervention involved automated, EMR-driven strategies to promote CRC screening.
- Participants were accrued in year 1, with a 12-month measurement window; control clinics received the intervention in year 2.
Main Results:
- Implementation challenges included overlap between measurement windows and intervention rollout, potentially contaminating outcomes.
- Lack of synchronization between measurement windows and intervention delivery could diminish estimated intervention impact.
- Solutions involved delaying intervention rollout and truncating measurement windows, alongside sensitivity analyses.
Conclusions:
- This case study highlights practical strategies for addressing analytical issues in pragmatic trials.
- Investigatos facing similar challenges can learn from the described methods for managing intervention timing and measurement windows.
- The findings contribute to best practices for conducting EMR-driven health interventions in real-world settings.
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