{"id":73485,"date":"2024-01-10T07:06:09","date_gmt":"2024-01-10T14:06:09","guid":{"rendered":"https:\/\/www.uchealth.org\/today\/?p=73485"},"modified":"2024-01-17T08:14:33","modified_gmt":"2024-01-17T15:14:33","slug":"catching-lung-cancer-earlier-through-ai-powered-systems","status":"publish","type":"post","link":"https:\/\/www.uchealth.org\/today\/catching-lung-cancer-earlier-through-ai-powered-systems\/","title":{"rendered":"Catching lung cancer earlier through AI-powered systems benefits patients"},"content":{"rendered":"
<\/div>
\"Eon\u2019s
Lung cancers start with lung nodules, most of which stay benign. Eon\u2019s AI-driven software helps make sure that lung nodules spotted during scans for other issues \u2013 called incidental findings \u2013 don\u2019t slip through the cracks. Getty Images.<\/figcaption><\/figure>\n

You\u2019re playing catch in a casually maintained field. The ball lands in a patch of clover a few feet away. As you reach down to pick it up, you note a sprig with four leaves. You pluck it. Then, as you stand to announce your good fortune to your throwing partner, the four-leaf clover slips from your fingers and back into the mob of its three-leaf brethren. You start looking for it. Your friend asks: What\u2019s the holdup? You pick up the ball, toss it back, and move on, leaving the lucky charm behind.<\/p>\n

When doctors review X-rays or CT scans to look for a specific issue like a broken bone or pneumonia, they often don’t have time to look for unrelated medical “four-leaf clovers”: findings that might show up if diagnosticians hunted for surprises that are known as “Incidental findings.”<\/p>\n

If experts happen to see unexpected results when they are looking for something else, they can save lives.<\/p>\n

In the past, there haven’t been good ways to hunt down these incidental findings. Now, the Denver-based health-technology firm\u00a0Eon<\/a>\u00a0is trying to solve the puzzle of incidental findings. With help and investment from UCHealth, they\u2019ve built a system that integrates into UCHealth\u2019s Epic electronic health record (EHR), the engine behind the\u00a0My Health Connection<\/a>\u00a0patient portal and much more.<\/p>\n

The system, Eon Patient Management, uses artificial intelligence (AI) to parse the standardized language of radiologists for incidental findings, categorize them based on risk, and then make sure they don\u2019t go lost like so many sprigs of clover.<\/p>\n

Catching lung cancer earlier through AI<\/strong><\/h2>\n
\"\"
Dr. Diana Breyer<\/figcaption><\/figure>\n

The Eon-UCHealth team started with incidental findings of lung nodules. The impetus came from pulmonologist Dr. Diana Breyer<\/a>, who is UCHealth\u2019s chief medical officer for northern Colorado, and a team that called itself \u201cthe haystack group.\u201d That\u2019s because, she explained, \u201cgetting incidental findings into the appropriate track for many of our clinicians is like trying to find a needle in a haystack.\u201d<\/p>\n

Let\u2019s say a patient arrives at a UCHealth Medical Center of the Rockies<\/a> emergency room with heavy lungs. He gets a chest CT scan for possible blood clots. The radiologist finds no blood clots, but notes pneumonia and something else: lung nodules. She notes their prevalence, location, and size (they\u2019re typically less than a centimeter in diameter), and then dictates these incidental findings into the patient\u2019s electronic health record.<\/p>\n

But then what? While some lung nodules do turn into cancer, more than 95% of them end up benign, so it\u2019s less pressing than the pneumonia. Plus, the patient may be visiting from out of town and not on the Epic EHR. And even if he\u2019s a UCHealth primary care patient, how does the radiologist alert the appropriate physician to check out the nodule-related findings in the EHR note? Emails and even faxes remain mainstays in what has continued to be an ad-hoc process.<\/p>\n

And while fewer than 5% or so of lung nodules turn out to be cancerous, the sheer number of patients whose lung cancers might be caught early thanks to incidental findings could be large across UCHealth, which has more than 40 imaging centers doing nearly a million radiology exams a year. Doing incidental findings right could avoid difficult treatments for more advanced disease \u2013 and save lives.<\/p>\n

\"A
A nodule appears on an image from a CT scan. The cancerous nodule is the round white area that appears on the left side of the image and is located in a patient’s right lung. Photo: UCHealth.<\/figcaption><\/figure>\n

\u201cThese are obviously huge impacts to patients,\u201d Breyer said. \u201cYou miss a nodule that becomes a cancer and it\u2019s not curable anymore.\u201d<\/p>\n

The question was how to automate the process. Breyer\u2019s team reached out to the UCHealth CARE Innovation Center<\/a>, which works with and invests in companies developing digital technologies that improve health care decision-making and delivery. They soon settled upon Eon \u2013 but with a caveat.<\/p>\n

\u201cThey didn\u2019t have a fully developed product in a way that would have enabled us to partner with them as a vendor,\u201d said Dr. Jennifer Wiler<\/a>, cofounder of the CARE Innovation Center\u2019s and chief quality officer for UCHealth University of Colorado Hospital<\/a> on the Anschutz Medical Campus<\/a>.<\/p>\n

\"Dr.
Dr. Jennifer Wiler. Photo courtesy of Dr. Wiler.<\/figcaption><\/figure>\n

\u201cBut we saw the potential to grow their technology, and that meant not just the AI component, but also the full end-to-end care coordination,” said Wiler, who is also a professor<\/a> at the University of Colorado School of Medicine<\/a>.<\/p>\n

Care coordination, in this case, means making sure the four-leaf clovers of incidental findings not only avoid burial in medical notes or going lost in missed handoffs, but also that they find the right providers to ensure proper patient care.<\/p>\n

Bigger picture, Eon fit perfectly into the CARE Innovation Center\u2019s guiding philosophy of finding and fostering technologies to solve pressing problems from the medical front lines, adds Dr. Richard Zane<\/a>, UCHealth\u2019s chief innovation officer, CARE Innovation Center cofounder and chair of emergency medicine<\/a> at the University of Colorado School of Medicine.<\/p>\n

\u201cIt was consistent with our strategy of simplifying the delivery of health care by using technology to do what technology can do and allowing humans to do what they do, which is adjudication,\u201d Zane said.<\/p>\n

Quick work, striking results<\/strong><\/h2>\n

Eon and UCHealth signed their agreement on May 22, 2022. Eon used anonymized UCHealth medical record data to further train its AI, and UCHealth worked with the company on the care-coordination front. Based on nodule size and other factors, the Eon system would automatically categorize incidental findings. Low-risk nodules would trigger an automated referral for patients to follow up with primary care providers \u2013 and, if the patients didn\u2019t schedule their follow-ups within a given window, the system would automatically alert providers to remind patients directly.<\/p>\n

\"Dr.
Dr. Richard Zane<\/figcaption><\/figure>\n

Incidental findings of high-risk nodules would follow a different automated path. They would be assigned to a pulmonologist in the appropriate UCHealth region who could then fast-track the patient to a lung-nodule clinic for biopsy and diagnosis, Breyer says.<\/p>\n

On Sept 22, 2022, just four months after the project\u2019s launch, the Eon system went live (yes, that\u2019s fast). In its first seven months, the lung-nodule incidental findings it mined and managed reduced the time of referral from 34 days to five days and yielded 263 cancer diagnoses.<\/p>\n

If data from University of Colorado Hospital are any measure, many of those cancers would have been caught much later. In the first quarter of 2022, before the Eon system went live, experts at the hospital registered 112 new incidental pulmonary-nodule patients. In the first quarter of 2023, the system captured and managed 1,889 patients with incidental findings of lung nodules.<\/p>\n

Further, patients with lung-nodule incidental findings are pursuing follow-up care at far greater rates. At Universtiy of Colorado Hospital, just half of those 112 patients in 2022 bothered to follow up. With Eon, about 80% of the 1,889 did.<\/p>\n

\u201cA significant portion are not going to end up with cancer, but you\u2019re not going to know that unless you follow them,\u201d Breyer said. \u201cSo having that kind of return on scheduled, recommended follow-up for their size and type of nodule is really the key piece of it.\u201d<\/p>\n

Eon\u2019s lung-nodule software is now running throughout the UCHealth system, and what works at UCHealth is working at a growing number of institutions. The UCHealth CARE Innovation Center team continues its collaboration with Eon even as UCHealth considers where it will integrate the AI solution next. (Eon also has incidental finding products for abdominal aortic aneurisms, thyroid nodules, pancreatic cancer, breast cancer and liver cancer.)<\/p>\n

For Breyer, the ability to capture, categorize, and boost the odds of incidental-finding follow-up amounts to a safety net for patients who might otherwise plunge into a belated cancer diagnosis. It took a great deal more than the luck of the Irish to realize.<\/p>\n

\u201cIt\u2019s very exciting to be able to provide this and really support our clinicians in caring for their patients,\u201d she said.<\/p>\n","protected":false},"excerpt":{"rendered":"

You\u2019re playing catch in a casually maintained field. The ball lands in a patch of clover a few feet away. As you reach down to pick it up, you note a sprig with four leaves. You pluck it. Then, as you stand to announce your good fortune to your throwing partner, the four-leaf clover slips […]<\/p>\n","protected":false},"author":23,"featured_media":73491,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_relevanssi_hide_post":"","_relevanssi_hide_content":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"","_relevanssi_noindex_reason":"","footnotes":""},"categories":[5],"tags":[28,4842,49,6836,4843,4670],"class_list":["post-73485","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-innovative-care","tag-cancer-care-oncology","tag-cancer-screening","tag-cancer-treatment","tag-lung-and-thoracic-cancer","tag-lung-cancer-screening-program-at-uchealth","tag-lung-tumor-testing-and-clinical-trials"],"acf":[],"yoast_head":"\nCatching lung cancer earlier through AI-powered systems - 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