Your EHR has the answers. LungIQ finds them.
USPSTF guidelines require a 20+ pack-year smoking history for LDCT eligibility. That number demands both intensity and duration, and it is almost never in a structured field. Patients underreport. Charts are incomplete.
LungIQ uses AI to recover pack-year history from clinical notes, medications, and diagnoses, then delivers a ranked worklist your team can act on immediately. No EHR integration required. Start from a CSV.
Pack-year history is the rate-limiting step
LDCT eligibility requires a 20+ pack-year smoking history. But that data is almost never in a structured, reportable field. It is the specific reason NCQA has not been able to advance a HEDIS lung cancer screening measure.
Patients minimize or deny smoking history. Intake forms go unfilled. Even when smoking is documented, pack-year quantities are rarely entered into structured EHR fields. The data is there, scattered across years of clinical notes, or it is not there at all.
Reviewing a single chart for smoking history takes 15+ minutes. Multiply that by your patient panel. No staff has the bandwidth to check every chart, so eligible patients go unidentified year after year.
FQHCs do not have CT scanners. Eligible patients need referral to imaging, insurance verification, pre-authorization, and follow-up. Without a downstream pathway, identification alone does not move the needle.
No EHR integration, no FHIR interface, no IT project. Export demographics, clinical notes, diagnoses, and medications as delimited text files under a signed BAA. We map your columns at configuration time. Any EHR, any schema.
A large language model reads clinical notes to extract smoking status, pack-years, and 9 tobacco-associated risk factors. A machine learning classifier combines this with ICD, CPT, and medication signals to score every patient's probability of eligibility.
Every patient is sorted into an action queue: USPSTF Eligible, Incomplete Smoking History, Needs Review, Not Currently Eligible, or Non-Candidate. Each patient carries a written explanation of why they were flagged, so the caller knows before dialing.
No EHR integration project. No new hardware. No vendor lock-in. LungIQ works with any EHR and starts from a simple flat-file export. We help connect FQHCs with consortium partners, including health systems and health plans, who have a shared interest in closing the screening gap.
Every shared decision-making visit is billable under your PPS rate. G0296 coding is built into the workflow. Your FQHC captures visit revenue while improving UDS Table 6B screening metrics and positioning for the expected HEDIS lung cancer screening measure.
Your patients are eligible. We help them get screened.
Millions of FQHC patients qualify for lung cancer screening but never receive it. Oatmeal Health identifies those patients in your EHR and connects them to imaging partners. No CT scanner required.
AI analyzes your patient records to surface everyone who meets USPSTF lung cancer screening criteria. LungIQ extracts smoking history and clinical risk factors from unstructured notes, then generates a ranked worklist your care team can act on immediately.
- Works from a CSV or flat file export. No EHR integration needed.
- Ranked by eligibility probability so outreach teams start with the strongest candidates
- 94% of top-ranked patients confirmed eligible on chart review
- Supports UDS reporting and quality measure tracking
When your patient reaches the imaging partner for their LDCT, LungAI provides the radiologist with a 0 to 100 malignancy probability for each nodule found on the scan. Your patients get the benefit of advanced AI analysis at no cost to your center.
- Continuous malignancy score augments categorical Lung-RADS
- Runs at the imaging partner site, not at your FQHC
- Results flow back to the referring provider
- Helps close the loop on patient follow-up
You have the patients. Imaging partners have the scanners. Oatmeal Health connects both sides so your patients can access screening without leaving the network. 91% of patients who receive proper education agree to proceed with their CT scan.
LungIQ runs on patient data you already have. You do not need imaging equipment, new hardware, or an EHR integration to start. Export a flat file, and LungIQ returns your screening worklist. Consortium partners and grant funding can help offset costs for qualifying health centers.
LungIQ performance validated on a 35,000-patient FQHC deployment. LungAI performance from internal retrospective validation on NLST held-out data. LungAI is not FDA-cleared and is not available for clinical use. Prospective clinical performance has not been established. Consortium structure and partner availability vary by region.
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Works with any EHR. No vendor lock-in. No IT project.