- Clinicians of the Future: A survey of nearly 3,000 clinicians from Elsevier Health and Ipsos revealed that 70% of clinicians believe digital health technologies will enable a positive healthcare transformation and 59% believe that most clinical decisions will be based on AI-enabled tools. However, these technology shifts will face plenty of challenges, as 69% reported being overwhelmed with the current volume of data, 69% predict that digital health technologies will become a greater burden in the future, and 83% believe clinician training needs to be overhauled so they can keep up with technological advancements.
- HALO Dx & Precision Imaging’s JV: HALO Diagnostics launched a joint venture with Northeast Florida radiology practice Precision Imaging Centers, opening four locations that combine HALO Dx’s multi-modal diagnostic approach (imaging + genomics + biopsy + labs) with Precision Imaging’s local staff and relationships. This is one of the first major geographic expansions we’ve seen from HALO Dx since they emerged in 2019 after acquiring ten California imaging centers with a goal to become “one of the top radiogenomics networks in the United States.”
- Patient Safety Concerns: The Emergency Care Research Institute’s list of 2022’s top-10 patient safety concerns highlighted a number of major challenges that we’re also seeing within radiology, including staffing shortages (#1 concern), COVID’s effect on provider mental health (#2), racial biases in patient care (#3), and cognitive biases and diagnostic errors (#5). The report didn’t specifically mention radiology, but its recommendations focused on the entire healthcare organization, suggesting that radiology-focused initiatives or products that address these concerns might be more likely to receive organizational support.
- LiverMultiScan Coverage: Perspectum’s LiverMultiScan solution (quantifies liver tissue w/ mpMRI) hit another coverage milestone, after AIM Specialty Health deemed it “medically necessary for evaluating diffuse liver diseases,” paving the way for coverage by Anthem and BlueCross BlueShield. A number of Medicare Administrative Contractors also updated their schedules to cover LiverMultiScan, suggesting that its usage volumes are poised to increase significantly when its CPT codes go into effect in July (0648T and 0649T).
- The Value of Second Opinions: A new MD Anderson study highlighted the clinical value of performing second-opinion scans and interpretations when patients were originally scanned at outside institutions (that aren’t the #1 cancer centers in the US). Analysis of 915 outside abdominal CT and MRI studies revealed that 65% had worse image quality and 31% were inappropriate for oncologic management. Of 375 outside radiology reports, 34% (131) had interpretation discrepancies versus reports from MD Anderson subspecialists and 48% of those discrepancies (42 patients) led to treatment plan changes.
- WellSpan’s Aidoc Adoption: Pennsylvania’s WellSpan Health (200 locations, >1,600 physicians & APPs) announced its adoption of Aidoc’s imaging AI platform, starting with WellSpan York Hospital and expanding to other locations going forward. WellSpan will leverage a range of Aidoc abnormality detection and prioritization solutions (PE, ICH, c-spine fracture), aiming to help improve efficiencies, catch abnormalities that might have otherwise been missed, and expedite care coordination.
- Identifying False True Positives: The smart folks from CARPL.ai unveiled a new AI explainability validation technique that might help identify when AI algorithms make the right predictions for the wrong reasons. CARPL’s new Explainability Failure Ratio (EFR) process identifies when AI models localize part of an image that’s not within an explainability bounding box or near radiologist annotations, and then has a human expert determine if there is a logical reason for this failure. If there’s no logical reason, it’s likely that this is an Explainability Failure that should be flagged during the AI validation process.
- Edison Digital Health: GE Healthcare announced the upcoming launch of its Edison Digital Health Platform, which will enable healthcare systems to have a vendor-agnostic platform to integrate apps into clinical workflows. The platform will aggregate data from multiple sources (e.g. EMRs, labs, imaging, genomics) so that providers can easily access relevant patient information in a unified view, allowing them to break out different patient cohorts for analytics.
- LDCT + Incidental Programs: A new study in the Journal of Clinical Oncology highlighted the complementary role of LDCT lung cancer screening programs and lung nodule follow up programs. The prospective observational study monitored outcomes from concurrent LDCT and Lung Nodule programs (n = 5,659 & 15,461), finding comparable stage I/II and stage IV cancer detection rates (I/II 61% & 60%; IV 19% & 20%), while the LDCT program had higher three and five-year survival rates (3yr 80% vs. 64%; 5yr 76% vs. 60%). More notably, only 54% of the lung nodule program participants who were diagnosed with cancer would have qualified for LDCT screening based on current guidelines.
- Info Blocking Numbers: Nearly a year after the US info blocking rules went live (and radiology reports had to be made immediately available), 274 information blocking claims have been entered into the ONC’s online portal. Claims most often came from patients who were seeking access to their electronic health information (176 claims) and were either charged to see them or faced unnecessary delays. Although both of these are explicitly forbidden in the 21st Century Cures Act, surveys following the law’s implementation showed that there’s still widespread confusion on what information blocking actually entails.
- Annalise CXR Matches Rad CTs: A new study in The British Journal of Radiology found that Annalise.ai’s Annalise CXR deep learning algorithm identified abnormalities in chest X-rays comparably to radiologists interpreting chest CTs from the same patients (n = 1,404 trauma cases). The CXR AI tool performed better than radiologists’ CT interpretations in identifying pneumothorax (p = 0.007) and segmental collapse (p = 0.012), while radiologists performed better than AI for clavicle fracture (p = 0.002), humerus fracture (p < 0.0015), and scapula fracture (p = 0.014). Annalise CXR performed about the same as the radiologists in the identification of rib fractures and pneumomediastinum.
