| PredUTI: Artificial Intelligence-Based Clinical Decision Support to Improve Urinary Tract Infection in Real Time | |
|---|---|
| Co-Lead | Mark Iscoe, MD, MHS, Richard Andrew Taylor MD, MHS |
| Team | Melissa Davis MD MBA, Beckman Coulter Diagnostics |
| Description | We aim to integrate an artificial intelligence model into the electronic health record that helps emergency department clinicians accurately diagnose urinary tract infections (bladder and kidney infections) in real time. We will create a tool that clearly displays the model’s predictions along with urinalysis results and evaluate the tool’s effect on patient care. |
| Target Impact | We hope that by presenting our artificial intelligence model’s predictions in real time we are able to augment clinicians’ clinical reasoning, leading to safer and more appropriate diagnoses and treatment decisions. Based on preliminary data, we estimate that we can reduce both over-diagnosis and under-diagnosis by as much as 50%. |
| Project Lead's Vision | Develop a way to diagnose Urinary Tract Infection Diagnosis in real time using artificial intelligence. |
Center for Health Care Innovation
