Healthcare / Health system
The Christ Hospital: Finding and following up lung nodules buried in radiology reports
- Company
- The Christ Hospital
- Country
- United States
- Adoption stage
- In operation
- Source published
- Date basis
- The date the source was published. It can differ from the date adoption started.
- How the source was checked
- Read the full source text
The work problem
Epic's material said lung cancer is the most common cause of cancer related deaths worldwide and that in 2020 only 16% of lung cancers in the United States were detected at a localized stage. Lung nodules often show up by chance on scans ordered for something else, such as trauma or cardiac symptoms, and radiologists record these incidental findings in the free text of their reports. Because the finding sits inside a long narrative, it is hard to tell which patients need to enter a monitoring program, and follow up was inconsistent. A study cited in the same material found that 36% of patients with stage IV lung cancer had nodules referenced in their radiology reports without receiving appropriate follow up. Joy Oh, chief information and digital transformation officer at The Christ Hospital, said the earlier approach depended on radiologists entering particular wording in particular fields, and that findings were missed because each radiologist writes differently.
Technology and data
After a radiologist finalizes a study, the impression and narrative are sent through Epic's AI extracted findings model. The model pulls mentions of lung nodules and lung masses out of the report and returns them in a daily report. That report carries the surrounding context of the finding, the radiologist's follow up recommendation such as additional scans, tissue sampling or a referral, and the due date the radiologist recorded. Three nurse navigators read the extracted findings and recommendations, check that they match the radiologist's impression, and then open the patient's chart to judge whether the recommendation is appropriate. Once a navigator verifies a finding, it becomes discrete data in the chart. Navigators use that data to see current and potential enrollment in the lung nodule program, unreviewed results, upcoming appointments and their own outstanding tasks on a single dashboard. Patients can be seen in the lung nodule clinic without a referral, so most are seen within three days of appearing on the daily report. Nurse practitioner Ashley Campbell can order additional diagnostic tests or hand the patient to one of ten pulmonologists who see patients on a rotating basis. When the team first turned the feature on, they ran the previous 90 days of reports through the model and surfaced more than 2,000 nodules that had not been documented as discrete data. Later the team found that nodules on scans ordered by oncologists or pulmonologists already had follow up in place, so they stopped sending those reports through the model and concentrated staff on scans ordered by primary care and the emergency department, where patients were more likely to fall through the cracks.
Results
The Christ Hospital said the number of lung nodules it tracks increased sixfold and that it diagnosed 23 lung cancers in the first six months of the program, matching its 2023 total in half the time. It said 64 additional patients began cancer treatment in the first eight months. Ashley Campbell said the feature has helped the team diagnose close to 70% of lung cancers at stage I or II, far above the national average of around 50%. Marcus Romanello, the chief medical officer, said the work is affecting mortality. In its March 2026 material Epic put the hospital's early detection rate for lung cancer at 69% against a national average of 46%. In the summary of the same material Epic said navigators followed up on almost 5,000 additional lung nodules, which led to 116 additional cancers being detected across the hospital's network.
Limits and open questions
The sources do not say how accurately the model extracts nodule mentions or how many extractions were wrong. They also do not give the month the program started. The early detection figures differ between sources: the June 2025 material gives close to 70% against a national average of around 50%, while the March 2026 material gives 69% against 46%.
Sources
Compiled from public sources. These are not results from ATF Works customers.