MedApp AI’s Post

Who Pays the Tab for #Hospital #ArtificialIntelligence? Dr. Nina Kottler, MD, MS and Dave Fornell Spill the Tea on #Reimbursement, #ROI, and Who Wins (Hint: It's Not Just Patients) 🫖 Say it with me, healthcare peeps: AI is hot! We spend lots of time at iSono Health to map out our #Ai Features #Radiologists, hospitals, Payors, and patients will benefit from it! But who foots the bill when these fancy algorithms waltz into hospitals? Buckle up because the answer might surprise you! Forget direct patient payments – that's a whole lotta nope :) Instead, it's a tangled web of stakeholders, from hospitals hungry for ROI to radiologists juggling efficiency and burnout. Meet the #Reimbursement Puzzle: (Private Payers, Public Payer (#CMS) and everyone else) - Medicare: Doles out temporary cash for fancy AI tech, but only if it improves patient outcomes (think "Breakthrough Devices Designations"). And don't get too comfy; that funding usually lasts three years, tops (#NTAP (New Technology Add-on Payments ) designation by #CMS). These threw some bucks at stroke AI a few years back, but don't expect a regular handout. - CMS's Transitional Coverage of Emerging Technologies (#TCET) for FDA-approved breakthrough AI tech. Think four years of temporary love, then it's on you, buddy. Category III CPT codes: Don't let the fancy acronym fool you; these are trackers for new tech. They don't pay the bills, but they help the AMA determine if AI deserves a seat at the reimbursement table. So, who screams "cha-ching" when AI lands in their corner? - Hospitals: Efficiency is the name of the game. AI that streamlines admissions, speeds up the ER, and shrinks patient stays gets a big ol' high five (and maybe a bonus check). - #Radiology: AI's their efficiency BFF (that is why I'm excited about iSono Health product! Taking care of tedious reporting, reducing mental fatigue, and even boosting accuracy by 20% (talk about a superhero!). Plus, those extra scans they can squeeze in thanks to AI? More moolah for the department. But where does the patient fit in? Remember, the goal is better care, not higher bills. AI helps detect cancers earlier, reducing misdiagnoses and freeing up radiologists for complex cases. That's a win-win-win situation for everyone. The Final Sip: Hospital AI's a fascinating tango between innovation, ROI, and reimbursement. It's not just about fancy tech; it's about who benefits and how. let's keep the conversation flowing! Share your thoughts and your experiences... Is AI your future dance partner, or just a temporary fling? #Radiologists spill the tea! Centers for Medicare & Medicaid Services RADEQUAL LTD. Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI) RADDX #AIinHealthcare #RadiologyRevolution #BurnoutBlues #RSNA #RSNA2023 American College of Radiology Radiology AI Radiology Business #HealthcareAI #ReimbursementDilemma #RadiologyRevolution #PatientsFirst #AIinUltrasound #ultrasoundtechnology

Healthcare Data Analytics: The ability to deliver high-quality patient care while managing costs and resources efficiently is more critical than ever. As we step into an era dominated by data, leveraging analytics has become paramount in enhancing patient health outcomes and helping with the patience experience. Click below to read more. #EY #eycareers #AI #DataAnalyticsInHealthcare #PatientOutcomes #HealthcareAnalytics #ClinicalDataAnalytics #PatientHealth #HealthDataScience #MedicalInformatics #PredictiveAnalytics #HealthInformationTechnology #DigitalHealth #HealthTech #HealthcareIT #Healthcare #AIHealthcare #PatientCare #generativeAI #datamanagement #AIinhealthcare #clinicaltrials #orthopedics #telemedicine #ambulatorysurgerycenter #ortho #patientexperience #ClinicalDataManagement #HealthcareResearch #DataIntegrity #ClinicalTrials #MedicalData #ClinicalData #DataEngineering #RegulatoryCompliance #dataanalytics #HealthcareAI #healthcarecareers #lifesciences #advancedanalytics #MachineLearning

This week's episode of Four Corners, caused quite a lot of conversation in the medical device and technology industry by telling stories of patient adverse experiences following surgery. Unfortunately, there is no burden of proof when it comes to media reporting, and there was no data shared, only stories. While any adverse event from surgery is tragic, it is also true that many patients need surgery when less invasive options are not sufficient to resolve or manage their health issues. In response, the NSANZ has published a press releasing suggesting an independent but collaborative registry for spinal cord stimulators. Registries are fairly common, for example, a 25 year old registry already exists for orthopaedic surgery, and it has been instrumental in improving clinical practice, patient safety and outcomes. Having decades of data is very useful for longitudinal research, one issue with older registries, is that they don't necessarily handle multiple data dimensions very well. This is especially relevant nowadays, as we can capture so much data, including real-time biomarkers that relate to patient outcomes and recovery. Below, I've shared a few links from IQVIA's insights library that discuss some key aspects of modern clinical registries. I believe there is a place for proactive clinical data capture across all of healthcare, including my former professional area, allied health. Ultimately, this presents opportunities to improve across all domains: clinical, commercial and policy. The Future of Clinical Data Registries "Traditional registries are very good at measuring the specific thing that they were set out to achieve such as connecting to an Electronic Health Record (EHR) and reporting. But, they don’t work well with multiple dimensions of data. They also don’t scale to collect new data—allowing for any new information that you’d like to collect that has become relevant to delivering great care." https://lnkd.in/gKzTWqWE The Changing Role of Registries and Health Data Platforms "Learning health systems are ones where practice informs research and research informs practice. These employ a continuous loop to identify outcomes, measure, analyze, recommend and implement change, and improve care delivery" https://lnkd.in/gKDQw--n Using Data Science to Unlock Insights from Your Healthcare Registry Data "Medical specialty societies, which include clinicians and practices, are increasingly focused on getting actionable insights to improve care and outcomes for their patients, so enabling organizations to expand their analytic capabilities is a necessary step when deciding areas to invest additional time and resources." https://lnkd.in/gBcyNYHC

Advancements in AI-enabled medical devices, especially in imaging, promise to enhance healthcare outcomes. These technologies can improve diagnosis accuracy, prioritize urgent cases, and reduce radiation exposure, boosting radiologist efficiency and patient safety. However, widespread access to these innovations hinges on Medicare reimbursement policies. Currently, the Centers for Medicare and Medicaid Services (CMS) has approved only a few AI-enabled devices for reimbursement, limiting their adoption. To address this, CMS should establish specific payment pathways for AI clinical tools, ensuring equitable access to these technologies for all patients, regardless of socioeconomic status. Similar to telehealth reimbursement during the pandemic, this move could expand access to critical medical advancements, particularly benefiting underserved communities. #aiinhealthcare #equitableai With the Specialist is a platform that combines artificial intelligence with a board certified neurologist to enhance neurological care in the primary care setting, bringing the neurology consult to you. Equitable access to expert care is importantly for all, and With the Specialist provides access to neurological expertise for those who don’t have quick access to a neurologist. #withthespecialist #neurology #innovation https://lnkd.in/gb9Zj-sk https://lnkd.in/gExrwg2P

𝗔𝗜 𝗖𝗔𝗡 𝗥𝗘𝗗𝗨𝗖𝗘 GP (𝗡𝗛𝗦) 𝗪𝗔𝗜𝗧𝗜𝗡𝗚 𝗟𝗜𝗦𝗧𝗦 𝗔𝗡𝗗 𝗧𝗜𝗠𝗘𝗦 The National Health Service (NHS) is renowned for its comprehensive care, but it faces persistent challenges, including long waiting lists and appointment times. Artificial Intelligence (AI) creates an unprecedented opportunity to streamline operations and enhance patient care with a focus on automating GP surgeries. ROUTINE CONTACTS AND APPOINTMENTS Many patients require regular check-ups or prescription renewals. Currently, this process involves considerable manual effort from GP surgery staff, who must contact patients and schedule these appointments. AI-powered systems can automate this entire process. By analyzing patient records and identifying those who need regular appointments, the system can automatically send reminders to patients and offer available time slots for appointments. BENEFITS TIME SAVINGS: GP staff freed from administrative burden of scheduling, allowing them to focus on patient care. REDUCED NO-SHOWS: Automated reminders ensure that patients do not forget their appointments, reducing the number of no-shows. PATIENT CONVENIENCE: Patients can easily manage their appointments, enhancing their overall experience with the healthcare system. TIME-BASED FOLLOW-UPS FOR CHRONIC AILMENTS For patients with chronic ailments, timely follow-ups are crucial. Conditions such as diabetes, hypertension, and heart disease require regular monitoring to prevent complications. Currently, it is challenging for GP surgeries to keep track of all patients who need to be seen after specific intervals. AI revolutionizes this aspect of patient care by ensuring no patient is forgotten. AI systems monitor patient records, identify those who need follow-up appointments based on their medical history, and automatically schedule these appointments. MANAGING CHRONIC AILMENTS ENHANCED PATIENT SAFETY: Timely follow-ups ensure that chronic conditions are managed effectively, reducing the risk of complications. PREVENTIVE HEALTH: Regular monitoring helps in early detection of potential issues, enabling preventive measures. RELIEF FOR GP STAFF: Automating follow-up scheduling allows GP staff to focus on more complex tasks and patient interactions. NO PATIENT IS FORGOTTEN AI follow up on appointments ensures that no patient falls through the cracks. AI can analyze data to predict patient needs, such as those who may soon require new prescriptions or those at risk of developing new conditions based on their medical history. Proactive management of patient health can significantly reduce emergency visits and hospital admissions CONCLUSION AI can play a pivotal role in reducing NHS waiting lists and times #NHS #GPs #HealthcareInnovation #AIinHealthcare #HealthTech #PatientCare #UKHealth #HealthcareLeadership #DigitalTransformation #HealthPolicy #PrimaryCare #ChronicDiseaseManagement #NHSWaitingLists #HealthcareEfficiency #FutureOfHealthcare #PublicHealth #HealthcareAutomation

NHS Nightingale boosts patient numbers with imaging tech from Canon - Digital Health #NHSNightgale #ImagingTech #Canon #PatientNumbers The NHS Nightingale hospital has increased its patient capacity by implementing imaging technology from Canon. The hospital, which was built in response to the COVID-19 pandemic, has been able to accommodate more patients by utilizing advanced imaging solutions. Canon's imaging technology has enabled faster and more accurate diagnoses, allowing healthcare professionals to provide timely and effective care. The implementation of this technology has significantly improved patient throughput and reduced waiting times. The imaging tech from Canon has also enhanced collaboration between healthcare teams by enabling the sharing of images and data in real-time. This has resulted in better coordination of care and improved patient outcomes. The success of this initiative highlights the importance of leveraging innovative technology in healthcare ai.mediformatica.com #diagnostic #medical #nhsnightingal #patients #canonmedical #hospital #imaging #technology #canonmedicalsystems #community #health #medicalimaging #digitalhealth #healthit #healthtech #healthcaretechnology @MediFormatica (https://buff.ly/3RJtSBN)

Ramsay Sime Darby Health Care and Annalise.ai have come together to offer clinicians access to Annalise Enterprise CXR, built on Amazon Web Services (AWS) which uses proprietary deep learning algorithms to identify suspected presence of up to 124 findings in chest X-rays in less than 20 seconds. This service can create a massive improvement to patient and clinician experience and is relevant across the full gamut of emergency, inpatient and outpatient, as well as conditions demanding urgent interventions.   As RSDH shares - "Annalise.ai's solution will act as a precision tool for the medical team at RSDH's hospitals, augmenting the clinician’s capacity to identify subtle details in medical images."   Leveraging Amazon Web Services (AWS) unparalleled breadth and depth of AI and Machine Learning services, organisations like Annalise.ai are able to work with industry leaders with bold visions like Ramsay Sime Darby Health Care to work backward from what is most important and most urgent. AWS Malaysia and ANZ teams are proud of this milestone and the achievement of our customer and partner.   Thank you Peter Hong Ching Yee Wong Bryan Lin Kenneth Khong Jasmine L. and the extended Ramsay Sime Darby HealthCare teams. And thank you to Anthony Saliba and Teodor Stoev from Annalise.ai looking forward to continuing our partnership here in Malaysia and across ASEAN.   At AWS in Malaysia and more broadly across ASEAN we see Healthcare as an industry rapidly changing with leaders like Ramsay Sime Darby Health Care focused on how they can continue to improve the patient and clinician experience leveraging AWS Cloud technology to support this mission.   This week in New York, AWS announced our next wave of GenAI services, of which one in particular, HealthScribe (https://lnkd.in/gzNKWXD6) will reduce the time spent on documentation and enable medical practitioners to focus their time on care. This service can transform the productivity of the industry and release huge benefits for patients and practitioners alike and its great to see AWS' GenAI approach continue to address industry challenges and real world solutions in this rapidly evolving space.   Conor McNamara Vikram Rao Rohan Kumar Russell Hall Jean Zhuang Dawn Chin Emma Rogers Wendy Kho Azhar Abdullah Rajvinder Singh Rajas Karandikar Joel H. Garcia

Extract-Medical device bias needs immediate action - review Immediate action is needed to tackle the impact of ethnic and other biases in the use of medical devices, an independent review says. It found pulse oximeter devices could be less accurate for people with darker skin tones, making it harder to spot dangerous falls in oxygen levels. And it warned devices using artificial intelligence (AI) could under-estimate skin cancer in people with darker skin. The review said fairer devices needed to be designed urgently. In total, it made 18 recommendations for improvement. The government says it fully accepts the report's conclusions. The review was commissioned in 2022 amid mounting concern that ethnic minorities faced greater Covid risks.. Building on previous research, the review says the devices, which are clipped on to a finger, can overestimate the level of oxygen in the blood for people with darker skin tones. The report says there is evidence from the US to suggest this can sometimes lead to worse health outcomes for black patients. And researchers say the situation is compounded by the devices mostly being tested and calibrated on participants with lighter skin tones… One example is the potential under-diagnosis of skin cancers for people with darker skin. This would probably be a result of machines being 'trained' predominantly on images of lighter skin tones, the team explains. Another concern arises when using AI systems for reading chest x-rays - which are mainly trained on images taken of men, who tend to have larger lung capacities. This could potentially lead to underdiagnosis of heart disease in women, the report suggests, worsening an already long-standing problem. The government says it is committed to removing bias in datasets and increasing training for health professionals… Prof Habib Naqvi, chief executive of the NHS Race and Health Observatory, welcomed the findings, saying access to better health should not be determined by ethnicity nor by the colour of your skin, and medical devices needed to be fit-for-purpose for all communities. He added that the lack of diverse representation in health research and robust equity considerations had "led to racial bias in medical devices, clinical assessments and in other healthcare interventions". Andrew Stephenson, Minister of State in the Department of Health, said the review was important. "Making sure the healthcare system works for everyone, regardless of ethnicity, is paramount to our values as a nation. It supports our wider work to create a fairer and simpler NHS," he said. https://lnkd.in/eJzn7-mz

🥼📈😷SURGEON WORKFORCE CHALLENGES AND SOLUTIONS!😷📈🥼 This bulletin, authored by the American College of Surgeons, provides an in-depth analysis of a report issued by theAssociation of American Medical Colleges (AAMC). According to the AAMC's projections, the United States is anticipated to face a shortage of surgeons ranging from 10,000 to 19,900 by the year 2036. This shortage forms part of a broader deficit in the physician workforce, estimated between 13,500 to 86,000 overall by the same year, as outlined in the 2024 report. Notably, the supply of surgeons fails to match the escalating demand, with projections indicating a need for approximately 160,000 surgeons by 2024, marking a 4.8% increase since 2019. While the article delves into the nuances of specialty and regional variances, its overarching message underscores the imperative to devise strategies for addressing the escalating patient demands amidst a diminishing surgeon pool. In my opinion, here are four solutions: 1) Centralization and regionalization for specific surgical services. These endeavors pose logistical challenges, potentially limiting patient access in certain communities. Furthermore, within the prevailing payment landscape, the reduction of surgical services could significantly impact the financial sustainability of hospitals situated in underserved areas. 2) Leveraging alternative healthcare providers to assume non-surgical responsibilities is pivotal in optimizing surgeon utilization. This necessitates a cultural and operational shift to ensure surgeons are predominantly engaged in surgical procedures that cannot be safely performed by other practitioners. While such delegation is already observed across various specialties, ensuring continuity and preserving the surgeon-patient relationship remains a paramount concern. 3) The integration of artificial intelligence (AI) tools holds promise in streamlining patient selection for surgical procedures. By facilitating selection of the right patient for the right procedure at the right time, AI technologies have the potential to enhance both access to care and patient outcomes. 4) Matching specialist demand to the number of training spots is a critical long-term solution. Currently, the number of residency and fellowship spots in any given specialty is largely decoupled from the demand. Repurposing training positions from specialties where there is less demand to those with significant shortages could help fix the problems long-term. This is especially salient since certain specialties can be practiced independently by APP's, a growing workforce pool, while others cannot. What solution am I missing?