The field of medical imaging has seen many changes in recent years, especially in finding incidental findings, also called incidentalomas. These are unexpected things that show up in imaging tests done for other reasons. Incidentalomas can give early signs of serious problems like cancer. But they also cause challenges in how to handle them. Medical practice administrators, owners, and IT managers in the United States are learning the importance of tracking these findings carefully in their workflow. Doing this not only helps patients but can also reduce legal risks, make operations smoother, and improve the care given.
Improvements in imaging like CT scans, MRIs, and other types have made incidental findings more common. Studies show that these unexpected findings appear in about 20% to almost 98% of imaging tests, depending on the group of patients and the test used. However, many of these findings do not get proper follow-up care.
Research shows that 65% or more of incidental findings that need follow-up are often missed because patients do not come back for more tests or exams. Not following up can delay diagnosis or treatment for serious illnesses like cancer. This can cause worse health, more worry for patients, and higher healthcare costs over time. For example, adrenal gland masses show up in 3% to 7% of adults who have imaging, and up to 27% of these might be cancer that has spread. Also, pancreatic cysts appear in about 19.6% of MRI exams and need close watching to catch any signs of cancer.
Missing follow-up care is especially worrying for cancer detection because cancers found early are easier to treat. Sutter Health doubled their early lung cancer detection rate by carefully following up on lung nodules found in scans. They found 70% of lung cancers at early stages I or II, which helped patients do better.
More incidentalomas make things harder for healthcare groups. There is a thin line between testing too much and testing too little. Testing too much gives patients extra radiation, causes stress, costs more money, and uses more resources. But testing too little means missing or delaying cancer diagnoses, which can cause bigger problems and more legal risks. In the end, patients may suffer more.
Dr. Elliot Fishman says radiologists have a tough job trying to avoid both too much and too little testing while helping patients. Often, problems happen because communication breaks down between radiologists, doctors who order the tests, and patients. Recommendations made by radiologists might not reach the right people or might not be acted on. This communication gap is a big issue for medical practice administrators since it affects patient safety, satisfaction, and how people view the organization.
Also, normal electronic medical record (EMR) systems do not track patients with incidental findings well. Managing these cases by hand can be hard and full of mistakes, taking lots of staff time with few good tools.
Some healthcare systems in the United States have made progress by using systematic and AI-based methods to handle incidental findings.
Saint Joseph Mercy Health System in Michigan is one example. After adding the AI-powered Nuance PowerScribe Follow-up Manager into their EMR system, they raised the rate of follow-up on incidental lung nodules from 36% to over 98%. This shows how technology can help patients get care faster.
Besides AI tools, processes that help different departments talk to each other are needed. Dr. Mark Perry says that teamwork between radiology, primary care, and specialists makes radiology useful not just for diagnosis but also for follow-up. Good follow-up leads to earlier cancer detection and better use of resources.
Spartanburg Regional Healthcare System also shows how good workflow design can help. They included nursing leaders in choosing their electronic health record system, which made documentation faster and saved about 9,000 staff hours a year. Having front-line staff involved helps match technology to user needs, improving work and satisfaction.
Artificial intelligence (AI) and automated workflows are being added to healthcare systems to meet the challenges of incidentalomas. These technologies help find patients, assess risk, support communication, and track follow-up. This lowers the workload for healthcare workers.
AI tools work like radiologists by spotting incidental findings in reports automatically and flagging patients who need more care. Software like Illuminate’s Discovery360 finds patients who have not had follow-up by checking electronic records and orders. It helps care teams focus on important cases and share recommendations well. Cole Erdmann from Illuminate says managing follow-up for incidental findings lets healthcare groups improve care while meeting financial goals.
AI programs often send automatic alerts and reminders to radiologists, doctors, and patients, helping reduce missed follow-ups. Nurse navigators use AI-supported tools like Illuminate’s ActKnowledge to organize care smoothly, making sure no patients are forgotten.
Using these technologies cuts down the work doctors and nurses have and makes their work more accurate and timely. For example, at John Muir Health in California, clinicians saved about 34 minutes a day on paperwork thanks to AI that helps with charting and listening. This helped reduce doctor burnout, and staff turnover dropped by 44% after AI started. Also, the University of Pittsburgh Medical Center cut late-night charting time by nearly two hours each day because of AI. These improvements help doctors focus more on patient care, including handling incidental findings.
Healthcare IT managers need to choose AI tools carefully so they fit into their existing EMR systems and workflows. Epic Systems Corporation connects 625 hospitals through the TEFCA Interoperability Framework, which helps share data. This sharing supports better care coordination and follow-up for incidentalomas. Smooth information exchange helps close gaps between radiologists, specialists, and primary care doctors.
Medical practice administrators and owners should focus on tracking incidental findings carefully, from both patient care and operation points of view. When incidentalomas are handled well, practices see many benefits:
Medical practices should train staff and leaders to understand clinical needs related to incidental findings. Working together with nursing leaders, radiologists, IT, and administrators can find problems in workflows and make them better. Spartanburg Regional Healthcare showed this can save thousands of work hours each year.
IT managers play a key role in picking and setting up systems for incidental findings follow-up. Important points to think about include:
By thinking carefully about these factors, healthcare groups can do a better job using technology to manage incidental findings.
This knowledge about incidental findings and cancer detection is important for healthcare workers across the United States. Systematic tracking combined with AI and automation tools leads to real improvements in patient care, reduces staff workload, and lowers legal risks. Handling incidentalomas through organized programs helps clinical, administrative, and tech teams work together to give timely, efficient, and safer care.
AI is being utilized in healthcare to streamline various processes, improve clinician efficiency, enhance patient experience, and facilitate better care delivery through advanced tools.
Clinicians using AI charting with ambient listening technology, like at John Muir Health, saved an average of 34 minutes per day on documentation, significantly impacting their overall workload.
At UPMC, clinicians reduced their ‘pajama time’—the time spent on paperwork—by nearly two hours daily, allowing more focus on patient care.
Centralized medical records promote higher quality and personalized care by providing comprehensive patient information, making healthcare simpler for patients and providers.
Spartanburg Regional enhanced nursing efficiency by involving nursing leaders in decision-making, leading to time-saving changes like automated documentation that saved 9,000 hours annually.
Piedmont Healthcare achieved a remarkable 95.8% response rate for CMS-required pre-op surveys by providing multiple options for patients to complete them.
Sutter Health improved early lung cancer detection by systematically monitoring incidental pulmonary nodules found in scans, doubling their detection rate for early-stage cancers.
The implementation of AI tools, such as AI charting, led to a significant 44% reduction in physician turnover at John Muir Health, suggesting better job satisfaction.
Epic’s software connects 625 hospitals to the TEFCA Interoperability Framework, enabling seamless information exchange which is crucial for coordinated care.
Epic aims to design clinician-centered AI tools that lighten workloads while enhancing care delivery, aligning technology with the needs of healthcare professionals.
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