Volunteer Outreach and Predictive Modeling: Rapid Randomized Quality Improvement Project for New Patient Attendance...

Area of Science:

• Health Services Research
• Quality Improvement Science
• Patient Engagement Strategies

Background:

• Nonattendance at new patient appointments results in missed care opportunities, revenue loss, and inefficient resource use.
• Effective strategies are needed to improve new patient visit attendance in primary care settings.

Purpose of the Study:

• To evaluate the impact of volunteer-conducted outreach calls, guided by a no-show predictive algorithm, on new patient appointment attendance.

Main Methods:

• A rapid randomized quality improvement project was conducted.
• Patients scheduled for new appointments at an urban safety-net clinic were randomized.
• The intervention group received volunteer calls plus standard reminders; the control group received standard reminders only. A predictive algorithm identified high-risk patients for prioritization.

Main Results:

• The intervention group showed significantly higher attendance (68.0%) compared to the control group (54.1%).
• Attendance increased for in-person visits but not telehealth visits.
• Patients preferring English and those in the second/third quartiles of no-show probability saw the greatest attendance improvements.

Conclusions:

• Targeted, volunteer-led outreach calls, informed by predictive analytics, are a feasible and effective method for boosting new patient visit attendance.
• Further research is required to optimize support for non-English speaking patients and telehealth appointment attendance.