IQVIA Obesity Clinical Trial Solutions Webinar Recording

💡 New findings from Truveta Research provide an early look at how oral semaglutide for obesity is being prescribed in real-world clinical practice. It's encouraging to see that providers are generally following the recommended dosing schedule as this new treatment becomes more widely adopted. Looking forward to seeing how research like this continues to improve our understanding of patient care: https://tr.vet/4v85hap

💡 New findings from Truveta Research provide an early look at how oral semaglutide for obesity is being prescribed in real-world clinical practice. It's encouraging to see that providers are generally following the recommended dosing schedule as this new treatment becomes more widely adopted. Looking forward to seeing how research like this continues to improve our understanding of patient care: https://tr.vet/4v85hap

A liver assessment is only valuable if it helps answer one question: What should I do next? For clinicians managing patients with MASLD/MASH, every assessment has the potential to influence the next step in care, whether that means: • Referring a patient for specialist evaluation • Prioritising further diagnostic assessment • Initiating or intensifying lifestyle interventions • Monitoring disease progression over time • Identifying patients who may benefit from emerging therapies LIVERFASt™ was designed to support these everyday clinical decisions by providing biopsy-aligned fibrosis staging, along with steatosis and activity assessment, helping translate laboratory data into clinically meaningful insights. Because clinicians don't just need results. They need information that supports confident decisions and better patient care. Learn more about the clinical evidence behind LIVERFASt™: https://zurl.co/TXJaY #PhysicianPerspective #ClinicalDecisionMaking #MASLD #MASH #LIVERFASt #ClinicalPathways #RiskStratification #LiverHealth #ClinicalEvidence #Fibronostics

Three patient subtypes. Zero treatment history. One question: 𝗰𝗮𝗻 𝘆𝗼𝘂 𝗳𝗹𝗮𝗴 𝘁𝗵𝗲 𝗵𝗶𝗴𝗵𝗲𝘀𝘁-𝗿𝗶𝘀𝗸 𝗽𝗮𝘁𝗶𝗲𝗻𝘁 𝗯𝗲𝗳𝗼𝗿𝗲 𝘆𝗼𝘂 𝗸𝗻𝗼𝘄 𝗮𝗻𝘆𝘁𝗵𝗶𝗻𝗴 𝗮𝗯𝗼𝘂𝘁 𝘁𝗵𝗲𝗶𝗿 𝘁𝗿𝗲𝗮𝘁𝗺𝗲𝗻𝘁 𝗽𝗮𝘁𝗵? Working with synthetic EHR data (1,763 type 2 diabetes patients), I first let unsupervised clustering find natural patient groups. Three emerged: a mild majority, a small dyslipidemic subgroup, and a multimorbid group ⇾ older patients, high comorbidity burden, the ones who carry the most clinical risk if missed. Then came the harder question. Clustering after the fact is useful for research. But in practice, 𝘆𝗼𝘂 𝘄𝗮𝗻𝘁 𝘁𝗼 𝗸𝗻𝗼𝘄 𝗲𝗮𝗿𝗹𝘆, 𝗮𝘁 𝘁𝗵𝗲 𝗳𝗶𝗿𝘀𝘁 𝘃𝗶𝘀𝗶𝘁, 𝗯𝗲𝗳𝗼𝗿𝗲 𝗮𝗻𝘆 𝗺𝗲𝗱𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗵𝗶𝘀𝘁𝗼𝗿𝘆 𝗲𝘅𝗶𝘀𝘁𝘀. So I deliberately stripped the model down: no comorbidity index, no treatment data, no follow-up history. Just what's available on day one: age, labs, BMI. The result on a held-out test set: 𝟵𝟮% 𝗼𝗳 𝗺𝘂𝗹𝘁𝗶𝗺𝗼𝗿𝗯𝗶𝗱 𝗽𝗮𝘁𝗶𝗲𝗻𝘁𝘀 𝗰𝗼𝗿𝗿𝗲𝗰𝘁𝗹𝘆 𝗳𝗹𝗮𝗴𝗴𝗲𝗱, using only baseline information. The model wasn't optimized for the best overall accuracy, it was optimized to catch the group that matters most clinically. That distinction, choosing what to optimize for not just how, is where a biotech background changes the questions you ask a dataset. #DataScience #MachineLearning #HealthcareAnalytics #RealWorldEvidence

🕵🏻♂️"It is a capital mistake to theorize before one has data" -Sherlock Holmes 🔎📑Sometimes the missing diagnosis is hidden in the missing record. 🔴A 50-year-old woman with persistent polyarthritis had already been evaluated for rheumatoid arthritis, gout, and psoriatic arthritis. As reactive arthritis became a more likely possibility, the clinical focus shifted toward identifying a possible infectious source. 🔵Additional history suggested pelvic inflammatory disease, prompting further workup and repeat abdominopelvic imaging. Although an earlier ultrasound had reported an IUD in place without complication, repeat imaging unexpectedly revealed two intrauterine devices. 🔴The case was a striking reminder that the real issue is not always a rare diagnosis, but sometimes a gap in record continuity. When longitudinal health information is incomplete, important details may be missed, interventions may be duplicated, and clinically relevant findings may emerge far too late. Electronic health records are not just digital archives, they are essential tools for patient safety, continuity of care, and sound clinical decision-making. #EHR #DigitalHealth #PatientSafety #ClinicalReasoning #HealthcareSystems

$50B in RHTP funding is on the table. AI diagnostics at the point of care is exactly the kind of project that wins these applications. Breakdown below 👇 #RuralHealth #DiabeticRetinopathy #ValueBasedCare #PrimaryCare 

Successful implementation will depend on workflow integration, staff training, quality execution, and measurable outcomes. Autonomous point-of-care diagnostics can be a practical way for rural primary care settings to close diabetic eye care gaps without adding unnecessary burden to patients or clinics.

Over 60% of patients with diabetes skip their annual diabetic eye exam. In rural America, that gap is often even wider because the nearest retina specialist can be hours away, transforming a routine check-up into a full day off work. That’s where the $50B Rural Health Transformation Program (RHTP) comes in, helping you close that care gap. Several states are already directing this funding to chronic disease prevention and technology innovation, exactly where autonomous, point-of-care AI diagnostics can fit. Best of all, RHTP funding covers the setup and subscription rather than the clinical exam itself.  Individual screenings are billed separately under CPT code 92229, turning a grant-funded initiative into a self-funding revenue engine. One caveat: RHTP is a competitive, scored application through your state - not an entitlement. The states reward high-impact projects that plug into existing primary care workflows. Given that, it's worth building a case that shows clear, measurable impact. We broke down how to position AI diagnostics against your state's outcome targets, navigate the RFP process, and improve your HEDIS and MIPS Measure 117 scores. You can read the full analysis here: https://lnkd.in/d6cFB_Ga

Strategic Interests, LLC is helping many providers and vendors capture a share of the $50 billion in RHTP funding available from CMS and all 50 states, by aligning your strategy with innovation and collaboration with partners to transform rural healthcare Vendors already participating can grow faster with our help Contact us at: https://lnkd.in/gGWND4pn

🔎 As new treatments become available, understanding how they're used in the real world is just as important as understanding how they performed in clinical trials. Our latest research explores early dosing trends for oral semaglutide for obesity and found that providers are generally following the recommended schedule for dose increases, an important step in helping patients tolerate therapy and stay on treatment. Truveta's helping bring real-world evidence to clinicians, researchers, and healthcare decision-makers: https://tr.vet/4v85hap