Using machine learning to improve scheduling in outpatient clinics
Operationalizing Machine Learning and Discrete Event Simulation Models to Improve Clinic Efficiency
This study is working on ways to help clinics better predict how long your visit will take, if you might miss an appointment, and how long you'll have to wait, so you can enjoy a smoother and more enjoyable healthcare experience.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Oregon Health & Science University NIH-funded |
| Lab location | 1 site (Portland, United States) |
| Project ID | NIH-10664923 on NIH RePORTER |
What this research studies
This research focuses on enhancing the efficiency of outpatient clinics by developing real-time prediction models that estimate patient visit lengths, the likelihood of missed appointments, and wait times. By utilizing machine learning and discrete event simulation, the project aims to create data-driven scheduling methods that allow clinics to optimize patient appointments and manage their workflows better. Patients can expect improved scheduling accuracy and reduced wait times, leading to a more satisfying healthcare experience.
Who could benefit from this research
Good fit: Ideal candidates for this research include patients who frequently visit outpatient clinics, particularly those receiving care in ophthalmology or similar fields.
Not a fit: Patients who do not utilize outpatient clinic services or those with conditions requiring inpatient care may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could significantly enhance patient satisfaction by reducing wait times and improving the overall efficiency of outpatient care.
How similar studies have performed: Previous research has shown that data-driven scheduling methods can improve clinic efficiency, suggesting that this approach has the potential for success.
Where this research is happening
Portland, United States
- Oregon Health & Science University — Portland, United States (Active)
Researchers
- Principal investigator: Hribar, Michelle — Oregon Health & Science University
- Study coordinator: Hribar, Michelle
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.