Bias in Treatment Selection Among Survivors in Assessments of Virtual Care Transition
By
Hongmei Yang
Christopher D Russell
Amy Arnder Greene
Angela D Humphrey
September 10, 2026
Clinical Scorecard: Bias in Treatment Selection Among Survivors in Assessments of Virtual Care Transition
At a Glance
Category Detail
Condition Virtual Transition of Care Clinics Key Mechanisms Survivor treatment selection bias and immortal time bias affect outcome evaluation. Target Population Patients undergoing virtual transition of care follow-up after hospitalization. Care Setting Post-discharge virtual care settings.
Key Highlights
VToC follow-up associated with lower 30-day readmission rates. Survivor treatment selection bias may overestimate readmission rates in non-VToC groups. Intent-to-treat analysis recommended to mitigate bias. Temporal concordance is crucial in assessing exposure and outcomes. Adjustment for baseline risk factors alone cannot eliminate bias. Guideline-Based Recommendations
Diagnosis
Management
Use intent-to-treat analysis using referral status. Incorporate time-varying Cox regression models to address exposure timing. Monitoring & Follow-up
Risks
Risk of misclassification of patients experiencing early readmission. Patient & Prescribing Data
Patients discharged from hospitalization requiring follow-up care.
Completion of virtual follow-up visits may not correlate with reduced readmissions due to bias.
Clinical Best Practices
Address exposure timing explicitly in analyses. Evaluate the impact of survivor treatment selection bias in observational studies. Related Resources & Content
