“With AI, we can use the results of what’s actually on the image to prioritize our studies. If our goal is to read the most important study first, what’s more important than a study that has a positive finding?”
- Evan Kaminer, MD
Montefiore Nyack Hospital
Montefiore Nyack Hospital
Nyack, New York
Expedite identification of critical medical conditions on patient CT scans to speed patient diagnosis and treatment
Change Healthcare Radiology Solutions™
Change Healthcare Workflow Intelligence™
- Improved ED turnaround times by 27% over three months with data-driven study prioritization
- Implemented automatic, AI-enabled study prioritization to read urgent studies first
- Reduced turnaround time for studies with positive findings by 17%
- Decreased physician and radiologist stress
Located thirty minutes north of New York City, Montefiore Nyack Hospital is a 391-bed community hospital providing emergency and acute care services to the residents of Rockland County and surrounding areas.
This Level II Trauma Center handles approximately 60,000 emergency room visits per year, and is 1 of 10 member hospitals in the nationally recognized Montefiore Health System. Since its founding in 1895, Montefiore Nyack has focused on practicing consistent, innovative medical care.
The Challenge: Moving Urgent Studies to the Front of the Queue
The Radiology Department at Montefiore Nyack Hospital is committed to continuous quality improvement. The team of radiologists reads more than 100,000 studies annually, and is always searching for ways to improve productivity without sacrificing quality.
A long-term customer of Change Healthcare, Montefiore Nyack first implemented Change Healthcare Radiology Solutions™ in 2009.
In 2015, the hospital served as the beta site for the Change Healthcare Workflow Intelligence™ solution, an imaging workflow rules engine designed to balance workload. The solution features a universal worklist that incorporates all of a radiologist’s tasks in one place for greater productivity.
“Our worklist prioritization was initially based on exam metadata,” explains Dr. Evan Kaminer, Director of Radiology at Montefiore Nyack Hospital. “How old was the patient? Where is the patient located? Inpatient or outpatient? When was the scan done?”
In partnership with Change Healthcare, the hospital built a detailed prioritization model that used data elements, such as referring doctor and exam type, to rank studies in the order in which they should be read. The new model allowed Montefiore Nyack to improve its Emergency Department (ED) turnaround times by 27% over the first three months.
The hospital still sought a reliable way to triage its ED cases. When the hospital’s leadership heard that Change Healthcare had partnered with Aidoc, a pioneer of medical artificial intelligence (AI), they were interested in how an AI-driven workflow could expedite care for critical patients.
The Solution: AI-powered Worklist Flags Positive Findings for Immediate Attention
In April 2019, Montefiore Nyack was the first hospital to implement Change Healthcare Workflow Intelligence 3.0, which offers AI decision support capabilities via Aidoc integration. The solution uses AI algorithms to scan diagnostic images for specific clinical findings, such as analyzing CT Head exams for anomalies related to intercranial hemorrhages.
After a scan is performed, the image is sent to an on-premises server, which anonymizes the data before transmitting it to Aidoc. The AI algorithms analyze the data for specified study types, sending the results back before Montefiore Nyack’s radiologists have read the study. If the platform detects any abnormalities, the exam is escalated to the top of the radiologists’ worklist.
“For the first time, with AI, we can use the results of what’s actually on the image to prioritize our studies,” says Dr. Kaminer. “If our goal is to read the most important study first, what’s more important than a study that has a positive finding?”
In keeping with its goal of triaging ED cases, Montefiore Nyack has implemented three AI algorithms designed to detect specific findings— intracranial hemorrhage, pulmonary embolism, and CT cervical spine fracture.
“We also have what’s called incidental pulmonary embolism, in which AI scans all of the chest CTs to see if there’s a pulmonary embolism that the radiologist may not have been looking for,” explains Dr. Kaminer.
At first, Montefiore Nyack’s leadership was concerned about the radiologists’ reaction to the new AI-driven workflow. Given the industry hype about AI’s potential impact, they didn’t want radiologists to feel undermined. Fortunately, the AI algorithms soon proved their worth.