Tag: medical imaging

Next-Generation AI Platform Redefines Radiology Workflow Standards

Posted on by Partner Content

AI is no longer being viewed as a diagnostic aid but as essential medical infrastructure. Nowhere is that more apparent than in lung screening, with Germany and other European Union countries now issuing guidelines that recommend AI for use in lung screening workflows.

This evolution will be on display at RSNA 2025, where Coreline Soft will introduce its groundbreaking chest AI platform AVIEW 2.0.

  • The solution demonstrates how unified AI automation is fundamentally transforming radiology workflows and elevating diagnostic precision across pulmonary, cardiac, and airway pathologies.

AVIEW 2.0 represents a paradigm shift from task-specific tools to an integrated diagnostic ecosystem. 

  • The platform seamlessly combines lung-cancer screening (LCS), coronary-artery calcium (CAC) scoring, and COPD quantification into a single, continuous analytical pipeline. 

Clinical validation shows radiologists using AVIEW 2.0 achieve 89% increase in case throughput and 60% reduction in interpretation time compared to the previous generation. 

  • This effectively consolidates multi-disease CT assessment into one streamlined, automated workflow.

AVIEW’s clinical foundation extends far beyond pilot studies. The platform has processed over 2.5M cases across 19 countries, establishing itself as a proven solution in diverse healthcare ecosystems. 

  • Most notably, AVIEW has been adopted as the standard AI platform for government-led lung cancer screening programs in major European nations – including Germany, France, and Italy.

Beyond Europe, AVIEW solutions are already integrated into major U.S. medical centers, where their clinical reliability has been independently validated in real-world settings…

  • UMass Memorial Medical Center has deployed the system as an integrated platform for LCS, CAC, and COPD diagnosis, supporting full-spectrum thoracic screening in daily radiology operations.
  • Temple Lung Center, 3DR Labs, and ImageCare Radiology have incorporated AVIEW products into their research and diagnostic environments – each adapting AI functions to site-specific workflows and physician preferences.

Together, these deployments demonstrate that AVIEW 2.0 is more than proof of concept; it is a platform that adapts to real-world hospital operations while meeting the rigorous clinical standards of leading U.S. institutions.

“We see RSNA 2025 as confirmation that AI’s value is no longer theoretical,” said James Lee, COO of Coreline North America. “When workflow efficiency and diagnostic safety advance together, AI stops being an add-on — it becomes infrastructure. AVIEW 2.0 embodies that transition, delivering not just automation, but a sustainable foundation for precision medicine at scale.”

With national-scale validation in Europe, clinical adoption across top-tier U.S. institutions, and 2.5M cases processed globally, Coreline Soft is positioning AVIEW 2.0 as the new benchmark for AI-driven thoracic imaging – where efficiency, accuracy, and scalability converge.

The Takeaway

Coreline Soft will conduct an end-to-end AI workflow demonstration in the “Radiology Reimagined” demo zone at RSNA 2025, using real-world clinical scenarios. With AVIEW and HUB, the full pathway – from triage and interpretation to reporting and quality management – will be validated against standards such as IHE and FHIR, allowing attendees to experience integrated flow firsthand. Learn more or book an appointment on Coreline Soft’s website.

Why MRI Providers Make Patient Comfort a Top Priority

Posted on by Partner Content

Smart MRI providers know patient comfort is linked to profitability. After all, the comfort quotient impacts image quality, diagnostic accuracy, operational efficiency, and patient satisfaction. 

  • Yet at least one-third of adult patients report distress, moderate anxiety, and discomfort related to MRI, according to a systematic review involving 220 patients.

When patients are claustrophobic or uncomfortable, it negatively impacts MRI providers…

  • Fidgety patients lead to motion artifacts/poor quality images and the need to retake scans – impacting overall productivity.
  • Sedating patients requires additional safety precautions, costing time and money.
  • Cancellations and no-shows due to patient anxiety translate to lost revenue.
  • Patients who have an uncomfortable MRI experience may go elsewhere next time – reducing repeat business and word-of-mouth referrals.

But it doesn’t have to be this way. Providers should seek out high-performance MRI systems designed with patient comfort in mind…

  • Shorter scans – The shorter the scan, the easier it is for patients to stay still. Fujifilm’s ECHELON Synergy MRI features up to 50% scan time reduction over previous generation 1.5T MRI scanners, and a 70-cm-wide bore with a 62-cm-wide table to enhance comfort.
  • Software tools – A study found that 15-20% of MRI scans require re-scan due to patient motion. ECHELON Synergy offers software that mitigates the impact of motion artifacts, making it easier and quicker to complete scans on fidgety patients.
  • Open design – Put claustrophobic patients at ease and scanning needn’t stop mid-way through an exam. Providers are alleviating anxiety and boosting efficiency with Fujifilm’s OASIS Velocity MRI, which features a true open design, where patients have an unobstructed view for maximum comfort. OASIS Velocity also supports patients who weigh up to 660 pounds.
  • Easy access – Improving comfort for all patient populations can help keep a facility competitive. Fujifilm’s APERTO Lucent is a powerful permanent magnet open-sided 0.4T MRI that delivers an optimal patient experience. Its unique single-pillar design provides ideal technologist-patient access, and the wide, laterally moving table lowers to 20 inches, ensuring easy access for pediatric, elderly, and/or injured patients.

Hospitals and imaging facilities across the U.S. rely on Fujifilm for state-of-the-art, patient-centric MRI systems. For example…

Make patient comfort a top priority and give your MRI business a competitive edge with solutions from FUJIFILM Healthcare Americas Corp. 

Opportunistic Screening Takes Big Step Forward

Posted on by Brian Casey

Opportunistic screening took a big step forward this week with new research in Nature Scientific Reports showing how an AI algorithm from Riverain Technologies was able to calculate coronary artery calcium scores from non-contrast CT scans – with performance close to that of radiologists. 

Opportunistic screening gives radiologists the chance to detect clinical conditions other than those for which the original scan was ordered. 

  • Potential use cases include calculating cardiovascular risk from mammograms or undiagnosed osteoporosis from CT exams.

One of the opportunistic applications with the most potential is CAC scoring from CT scans. 

  • CAC scores are a good marker for future cardiovascular risk. But it can be time-consuming to perform separate cardiac CT scans just to acquire CAC data when thousands of abdominal and thoracic CT studies are conducted every day and could serve just as well.

Riverain’s ClearRead CT CAC algorithm uses AI to analyze non-contrast CT exams and produce Agatston scores, the reference standard for CAC analysis. 

  • Previous research found Agatston scores to be predictive for both cardiovascular and all-cause mortality, but generating the scores requires some manual involvement from clinicians. 

In the new study, Mass General Brigham researchers compared ClearRead CT CAC’s performance to ground-truth calculations from radiologists in 491 patients who got non-contrast CT scans at five U.S. hospitals in 2022 and 2023. Researchers found…

  • CAC score agreement between AI and radiologists was high, with a kappa of 0.959 (1.0 is perfect agreement).
  • The association remained strong regardless of sex, age, race, ethnicity, and CT scanner model, with kappa higher than 0.90 for all groups except “other race.” 
  • The AI model’s CAC scores from non-gated CT scans were similar to those from gated cardiac CT exams (kappa = 0.906), which are generally considered the gold standard for cardiac CT but are more complex to perform.
  • The model’s kappa for gated CT exams compared favorably to recent research conducted with other commercially available algorithms.

The results are a boost for opportunistic screening but in particular for Riverain, which got FDA clearance for ClearRead CT CAC in December 2024 and offers the solution as part of its ClearRead CT suite.

The Takeaway

The new results show that opportunistic screening is moving beyond the research phase and that the opportunity could be now for real-world clinical use. 

Radiology Untethered: Sirona’s Approach to Unified Radiology

Posted on by Partner Content

Radiology stands at a breaking point. 

Hospitals and imaging practices are overwhelmed by fragmented IT systems, cumbersome technology integrations, and staff burnout. Medical imaging is the central hub through which more than 80% of healthcare data flows, but it’s become hobbled by technology that was never designed to work together.

Sirona Medical is changing the equation by rebuilding radiology software from the ground up with a cloud-based architecture that’s as simple as launching a web browser. The company hopes to free radiologists from the constraints of legacy infrastructure and redefine how diagnostic medicine operates in the cloud era, and is demonstrating its approach to radiology professionals.

The fragmented roots of radiology IT. For over two decades, diagnostic imaging has relied on three separate technological worlds that each evolved independently: PACS, reporting, and worklists…

  • PACS revolutionized image storage and viewing in the 1990s, replacing film with pixels. 
  • Reporting software brought speed through voice recognition, ending the days of transcription backlogs. 
  • Worklists organized the chaos of multi-site reading, giving radiologists a unified queue.

Yet these systems were never designed to function as one. Every integration became a brittle patchwork of custom connections. Every update risked breaking the workflow. 

The result was a “house of cards” of on-prem servers, co-located databases, and expensive maintenance contracts. Radiologists found themselves acting as system operators rather than clinical specialists, forced to navigate between screens and dictate into isolated software, losing valuable time that could be spent on patient care.

The hidden cost of separation. This disconnected infrastructure carries enormous financial, operational, and human costs. Hospitals often juggle dozens of software solutions that must be maintained, updated, and bridged by manual effort. 

A single broken link can break the entire workflow. Meanwhile, legacy vendors profit from the complexity, locking customers into long-term contracts that drain budgets and stifle innovation.

The radiologist shortage and rising imaging demand only worsen the problem. Real progress requires not another integration, but a complete re-architecture of the radiology technology stack.

Sirona’s break from the past. Enter Sirona Medical with the mission of rebuilding radiology software as a single, cloud-native platform where PACS, reporting, and worklist live together seamlessly. Delivered entirely through a Chrome browser, Sirona’s system eliminates handoffs, brittle integrations, and costly local servers.

At the platform’s foundation is RadOS, a unified data model and operating system that ingests, normalizes, and orchestrates imaging and text data across formats including DICOM, HL7, FHIR, PDFs, and clinical notes. By consolidating all this information into one consistent data model, RadOS replaces thousands of fragile interfaces with a single source of truth.

RadOS does more than unify; it enables intelligence. Built-in large language and ontology-classification models transform raw imaging and text data into structured, machine-readable insights. As a result, radiologists can work as fast as they can think, and organizations can operate profitably while improving care quality.

Powered by AWS: Streaming radiology to the world. Sirona’s platform runs on AWS, the world’s most robust cloud infrastructure. Sirona delivers massive imaging datasets to radiologists, ensuring near-instant access regardless of geography.

This design provides…

  • Low-latency performance through local caching.
  • HIPAA-compliant, military-grade security across devices and networks.
  • Global reliability backed by AWS’s resilient backbone.
  • Automatic updates via simple browser refresh.
  • Scalable storage without hardware investment.

Hospitals and imaging practices can now connect radiologists worldwide without maintaining physical servers or dealing with VPN bottlenecks.

The application layer: Intelligence built in. Sirona’s application layer sits on top of RadOS and is a seamlessly integrated environment that merges the universal worklist, diagnostic viewer, and AI-driven reporting solution. 

Key capabilities include…

  • Auto-Impressions: AI generates customizable draft impressions, fine-tuned for each reader.
  • Focus Mode: Radiologists dictate naturally while AI maps findings to structured report sections.
  • Quality Assist: A radiology-specific large language model detects speech-to-text errors and clinical inconsistencies in real time.
  • AI Orchestration: Third-party AI tools plug directly into reporting, no brittle middleware required.
  • Priors Summary and Auto-Priors: AI retrieves and summarizes prior exams automatically, accelerating interpretation and ensuring continuity of care.

These features turn the radiology report from a static document into a dynamic, intelligent artifact that supports decision-making across the care continuum.

The time is now for cloud-native PACS, and for the unified approach to radiology viewing, reporting, and worklist that Sirona Medical has pioneered. Radiology’s next era has arrived: one PACS, one worklist, one reporter – and it’s a reality right now.

Learn more about Sirona Medical’s approach to radiology software by booking a demo today.

CAC Research Leads Imaging at AHA 2025

Posted on by Brian Casey

The 2025 American Heart Association annual conference wraps up today, and cardiac imaging has been a major focus in New Orleans. In particular, research has highlighted imaging’s power to predict future cardiac events – and guide treatment to prevent them. 

Coronary artery calcium scoring with CT is a great example, as CAC scores can predict not only cardiovascular but also all-cause mortality. 

  • Another common theme at AHA 2025 has been opportunistic screening, in which data from imaging exams acquired for other clinical indications can be used to detect osteoporosis, cardiovascular disease, and other issues. 

Check out the items below for some of the hottest imaging topics at AHA 2025, and for a deeper dive into non-imaging news from New Orleans, be sure to visit our Cardiac Wire sister site. 

News from the show’s first three days include…

  • A massive study of 40k people found that those with CT-derived CAC scores greater than 0 were 2X-3X more likely to die from any cause than people without any CAC – and more died of causes other than cardiovascular disease. Also, 8.5% of patients had other significant findings. 
  • Community health personnel on a Native American reservation were trained to perform point-of-care screening echocardiography assisted by Us2.ai’s AI algorithms. 
  • Us2.ai’s algorithm was also used with transthoracic echo in the SCAN-MP study to detect transthyretin amyloid cardiomyopathy, a cause of heart failure. 
  • Treadmill stress tests fell short compared to CCTA in screening older master’s athletes for ischemia that could lead to sudden cardiac death.
  • A program in Brazil that used echocardiography to screen schoolchildren for latent rheumatic heart disease led to lower prevalence rates after 10 years (2.5% vs. 4.5%). 
  • Patients with hypertrophic cardiomyopathy who had higher levels of myocardial fibrosis on cardiac MRI were almost 6X more likely to have adverse events over eight years.
  • HeartLung Technologies’ AI tool predicted CAC presence on CT scans in 2.1k participants in the MESA study with higher AUC than other tools (AUC = 0.73 vs. 0.68).
  • Another study used HeartLung’s AI to analyze CAC scans to detect myosteatosis – a sign of systemic metabolic dysfunction – which predicted atrial fibrillation and heart failure. 
  • A program promoting CAC scoring to an urban population brought in people for screening who might have been missed through physician referral. 

The Takeaway

This week’s news from AHA 2025 shows medical imaging’s contribution to early detection of cardiovascular disease – the leading cause of death worldwide. CT-based CAC scoring has especially promising potential, not only for heart disease but also other conditions through opportunistic screening.

Medicare Payment Pushback to 2026 Physician Rates

Posted on by Brian Casey

CMS gave U.S. medical specialists a fright on Halloween with the publication of its final 2026 Medicare Physician Fee Schedule. The new MPFS rates lock in a controversial “efficiency adjustment” for specialist physicians (including radiologists) and continue a decline in Medicare payment rates for specialists.

Physicians have long complained about low reimbursement rates in the Medicare and Medicaid programs, which are tasked with providing healthcare services to an aging population under a budget that’s, by law, limited to a fixed amount.

  • The situation creates a zero-sum game: increased healthcare spending in one area has to be offset by reductions in another.

Physicians thought they won a victory in summer 2025 with the passage of the One Big Beautiful Bill Act, which included a 2.5% increase in the Medicare conversion factor, the complicated formula governing physician payments.

  • But it didn’t take long for the bill to come due. Within weeks of OBBBA’s passage, CMS issued its proposed 2026 MPFS rates, which included the conversion factor bump but also what the agency called a 2.5% “efficiency adjustment” payment reduction.

CMS justified the reduction by stating that it applied to medical services “that have likely become able to be furnished more efficiently over time but still retain valuations based on outdated assumptions” – including medical image interpretation.

  • But the subtext is that the adjustment continues the agency’s long shift away from medical specialties – which CMS believes are overpaid – and toward primary care physicians.

Organized medicine’s response illustrates the rule’s uneven impact. 

Indeed, an ACR analysis of the final rule estimates an overall impact of the MPFS changes to be -2% for radiology, -1% for nuclear medicine, +2% for interventional radiology, and -1% for radiation oncology.

  • That may not sound like a lot, but the reductions come on top of years of similar declines that some observers have likened to “death by a thousand cuts.”

The Takeaway

By finalizing the 2026 MPFS, CMS is locking in a physician reimbursement schedule that continues to shift payments away from medical specialties like radiology and toward primary care. It’s a trend that’s been happening for decades, and is one that this year’s change in administration has done little to reverse. Radiology should buckle up. 

New CT Protocols Reduce Radiation Dose

Posted on by Brian Casey

With patient safety top of mind these days, radiology professionals are correct to focus on performing CT scans with less radiation. To that end, three recently published research studies highlight new protocols to do just that.

Radiation safety has been one of the top radiology stories in 2025 following several studies underscoring the links between medical radiation and cancer. 

  • The irony is that patient radiation exposure can be reduced dramatically using protocols that already exist – it’s just a matter of applying them consistently in the real world. 

In the first paper, published in European Journal of Radiology, researchers share their MINDS-CAD protocol for coronary CT angiography. 

  • MINDS-CAD relies on tailoring contrast dose to patient weight and CT scanner tube voltage using a five-step process. 

MINDS-CAD was tested with 112 obese patients getting clinically indicated CCTA with Siemens Healthineers’ Somatom Force dual-source CT scanner and Bayer’s Ultravist 370 contrast agent. Researchers found that compared to a conventional tube voltage-adapted protocol, MINDS-CAD…

  • Achieved superior image quality according to cases rated “good” or “excellent” (86% vs. 75%).
  • Generated fewer poor-quality scans (3.5% vs. 8.8%).
  • Produced sharply lower radiation dose (99 vs. 386 mGy•cm).
  • Saw no link between vascular attenuation and BMI or tube voltage.

In a second EJR paper, researchers from India tested the ability of an AI-based reconstruction algorithm to reduce dose in cerebral CTA exams.

  • They used Philips’ Precise Image AI-based reconstruction protocol, which produces images resembling traditional filtered back projection scans while reducing noise like advanced iterative reconstruction methods.

In tests with 68 patients who got cerebral CTA at 100 kVp, compared to iterative reconstruction, Precise Image…

  • Improved contrast-to-noise ratio 26%, signal-to-noise ratio 22%, and visual noise 16%.
  • Generated higher image quality scores from radiologists.
  • Generated an extremely low median effective dose of 0.785 mSv.

Finally, a third study – this one in Clinical Radiology – used a “double low” technique of low-energy 50 keV images on GE HealthCare’s Revolution Apex dual-energy CT scanner with TrueFidelity deep learning image reconstruction on 60 patients with cirrhotic liver disease. 

  • Compared with a conventional protocol, the double-low technique had 48% lower radiation entrance dose (4.10 vs. 7.88 mSv) and 32% lower contrast dose (67.3 vs. 99.1 mL), while image quality was rated higher.

The Takeaway

Taken together, the new papers show that radiology’s radiation dose challenge is eminently solvable thanks to the ingenuity of clinicians and researchers who are pioneering new ways to scan.

Malpractice Reform Linked to Less Imaging Use

Posted on by Brian Casey

We all know it happens – medical imaging scans of questionable clinical value, performed not to improve patient diagnosis but to defend clinicians in the event of malpractice litigation. A new study in AJR supports the idea that defensive medicine is driving up imaging use by finding a link between malpractice reform and lower emergency imaging utilization. 

The proliferation of imaging technology throughout the healthcare enterprise – and especially in the emergency setting – gives clinicians a powerful tool that’s just too tempting not to use.

  • Head CT scans can quickly rule out patients who might have a hemorrhagic stroke, for example, while cardiac CT angiography is showing its value for working up patients with chest pain. 

But with great power comes great responsibility. Unnecessary imaging not only drives up healthcare costs but can expose patients to additional radiation as well as complications from working up suspicious findings.

  • Medical-legal experts speculate that malpractice reform through tools such as damage caps could tamp down defensive medicine by limiting physicians’ legal exposure to lawsuits in the event they make a mistake.

In the new study, researchers from the ACR’s Harvey L. Neiman Health Policy Institute tested the idea by analyzing 630k Medicaid encounters for patients with headache presenting to the emergency department in 2019. 

  • They then correlated head and neck imaging volume to various factors that could influence utilization, including whether states had implemented tort reform. 

Their analysis discovered that emergency imaging utilization was less likely to occur…

  • In states with laws on “several liability” (in which parties are only responsible for their own share of damages) (OR = 0.68).
  • In states with malpractice damage caps (OR = 0.79).
  • In states with greater mean malpractice payment (although the effect size was minimal; OR = 0.99).

A couple other interesting findings included…

  • Referring physicians other than emergency medicine were far more likely to order more imaging (OR = 8.45).
  • Facilities with fewer than 100 beds were less likely to order imaging (OR = 0.65).

The Takeaway

The new findings linking malpractice reforms with lower emergency imaging use confirm what many of us have already suspected. Whether they lead to health policy reforms remains to be seen. 

AI in Radiology: Old Problems, New Tech

Posted on by Partner Content

By Mo Abdolell, CEO, Densitas

Radiology has seen this movie before. Big promises (efficiency, accuracy, burnout relief). Big anxieties (ROI, workflow chaos, pressure to “keep up”). The question isn’t whether AI is powerful. It’s whether we’ve learned how to deploy new technology without repeating the pain of PACS migrations and the EHR era.

The Myth of the Perfect Rollout. Health technology assessment (HTA) sounds great in theory – rigorous, comprehensive, evidence-first. In practice, few organizations have the time, talent, or budget to execute it at scale. 

  • Remember EHRs: adoption happened because policy and money forced it, not because the playbook was tidy. Healthcare’s default pattern is to adopt, then evolve – messy, market-driven, and iterative. Waiting for perfect plans is how you get left behind.

Are AI’s Problems really new?

  • Black box déjà vu. Radiology has long trusted complex, opaque systems (reconstruction algorithms, vendor-specific pipelines). What mattered – and still matters – is validated performance and dependable outputs, not full internal transparency.
  • Model drift ≈ old friends. We’ve always recalibrated clinical tools as populations and scanners change. Monitoring and revalidation are known problems, not alien ones.

What’s Different This Time? Unlike the top-down EHR mandate, AI is largely market-driven. That gives providers agency. 

  • AI solutions must save time, improve outcomes, or avoid costs – not just publish a ROC curve. They must show operational value inside the native radiology workflow.

Fortunately, there are ways to adopt AI and then evolve your processes to make it work…

  • Workflow or bust. Demand in-viewer evidence objects, one-click report insertion, and EHR write-back. If AI adds steps, it subtracts value.
  • Start narrow, scale deliberately. Pick high-volume, high-friction tasks. Prove value in weeks, not years. Expand only when the operational signal is undeniable.
  • Measure what matters. Track operational metrics like seconds saved and coverage (e.g. eligible cases processed before dictation), reliability (e.g. results present before finalization, fail-open behavior), and user friction like context-switching rate and time-to-evidence.
  • Monitor. Stand up organization and site-level performance checks. Treat AI like equipment – scheduled, observed, and maintained.
  • Invest in long-term value. Favor standards, vendor-agnostic interoperability, clear telemetry, and transparent pricing.

The Takeaway

AI’s success in radiology won’t be defined by elegance of algorithms but by pragmatism of deployment. This will be an evolution – hands-on, incremental, sometimes messy. The difference now is that radiology can drive. Make the technology serve the service line – not the other way around.

Target the toughest workflows. Adapt and evolve with Densitas Breast Imaging AI Suite.

New Cancer Disparity Data Show Socioeconomic Impact

Posted on by Brian Casey

Cancer screening disparities continue to draw scrutiny in radiology. A new study in JAMA Network Open takes a closer look at why some people don’t get screened as often as they should – as well as the factors that contribute to cancer prevalence and mortality. 

There’s extensive research backing the lifesaving potential of the major cancer screening exams, and cancer mortality rates have consistently declined thanks to the combination of screening and better treatments. 

  • But the declines are uneven, prompting researchers to investigate reasons for the disparities, such as in a study earlier this month documenting geographic variations in cancer screening rates. 

In the new study, researchers from the ACR’s Harvey L. Neiman Health Policy Institute looked at how 24 measures like lifestyle, socioeconomic status, and environmental background affected breast, prostate, lung, and colorectal cancer, which account for 50% of new cancer cases.

  • In particular, they examined screening completion rates and cancer prevalence and mortality at the county level in a nationally representative sample of 5% of Medicare fee-for-service beneficiaries, of whom 87% were 65 years and older. 

There’s a lot to unpack in the study, but a few highlights are below as they relate to breast and lung cancer, the two cancers for which imaging-based screening is recommended. The top three factors affecting each (in order of importance) are…

  • Breast cancer:
    • Screening rates – Hispanic population share, levels of insufficient sleep, and poverty. 
    • Prevalence – uninsured status, obesity, and housing insecurity.
    • Mortality – non-Hispanic Black race, environmental justice index, and insufficient sleep.
  • Lung cancer:
    • Screening rates – air pollution exposure, lack of access to primary care physicians, and number of poor physical health days.
    • Prevalence – limited access to healthy foods, uninsured status, and severe housing problems.
    • Mortality – smoking, poor physical health days, and environmental justice index. 

While there are some obvious findings in the data (the connection between smoking and lung cancer mortality, for example), the dominance of socioeconomic measures may take some by surprise (or maybe not). 

  • But they do track with previous research finding that socioeconomic factors account for 40-50% of health impacts.

The Takeaway

The new study – as with previous research – reinforces what we know about the strong connection between socioeconomic status and cancer screening disparities. The new data should give clinicians and public health advocates more detail on the specific factors they need to focus on to improve screening compliance and reduce cancer’s burden on society.

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