Kevin Ferris

Something for people to consider, which most people probably don't - especially applicable if you use your phone for navigation. In short, you data consented on many apps on your phone that aggregate and sell your data, and one of those buyers could be your insurance company. When some of the companies were offering discounts to drivers who "plugged in" a monitoring device for driving tracking, this is a more insidious approach, but very likely is happening. More and more I want to go to a de-googled basic or non-smart phone to cut the chains. While there is a great convenience to these mini computers in our pockets, there are costs we are just starting to become more aware of. https://lnkd.in/g2x49ZiU

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Was awesome to learn from the brilliant Dr. Jennifer Goldman DO, MBA, FAAFP, CMIO of Memorial Healthcare System, on The Digital Patient podcast. We went deep on: → Strategies used to eliminate 800,000+ daily clicks across the health system → How to implement Social Determinants of Health (SDoH) tools into the EHR → Leveraging technology to streamline primary care, including automating preventive care processes and documentation → How digital health leaders should think about balancing competing priorities between improving patient outcomes and addressing operational challenges (workforce shortages, financial losses) … and much, much more! Link to the episode in the comments below 👇 #digitalhealth #healthcareinnovation

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🆕 Episode: Continuing our recap of HIMSS 24, host Angelo Kastroulis sat down with Nicholas Stepro of Arcadia. In this clip, they touch on the topics of value-based care, social determinants, and AI in the healthcare setting. You can catch the full podcast with this link 👇 or on any major platform. https://lnkd.in/eYt2suhf #healthcare #data #analytics #sdoh #ai #himss24

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📡 What’s ambient signal, and how can it help address social determinants of health? Arcadia’s Chief Product and Technology Officer, Nicholas Stepro, explains in this episode of the Counting Sand Podcast. 🎙️ Give it a listen to learn how: ➡ Data and analytics provide an understanding of performance and identify areas for improvement in healthcare ➡ Artificial intelligence can be used to enhance healthcare efficiency and effectiveness ➡ Trust and transparency can lead to the adoption of AI in healthcare

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"How can you ensure patient data accuracy in your healthcare database?" LinkedIn randomly asked me this question, dangling another community topvoice" badge of questionable value like a topdoc award, in front of me. There are great things about LinkedIn which I love, but I don't like its thought policing algorithms. LinkedIn has two types of top voice badges: 1) "topvoice" and 2) "community topvoice". The "topvoice" badges are "invitation only" which LinkedIn appears to give out to, only powerful, or politically correct members, whose posts are always amplified on its platform. I have seen many ordinary posts from some "top voice" members being amplified. LinkedIn cleverly invented the "community topvoice" for the intellectual coolies to train its AI engine to produce so called community knowledgebase articles. LinkedIn's random question today about the accuracy of healthcare database was one such attempt. The video shared with this post is my answer. Watch till the end :) We still love you LinkedIn. #healthcare #healthcaredata #humanresource

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This article is concerning and puts our future trajectory with AI at risk. #AI is the buzzword of our era, and I've been at the forefront, utilizing ChatGPT for several years now, including during my tenure in academic medicine. My thoughts on #AI and #nursing: 1. AI is NOT a replacement for nurses. Any company claiming otherwise is not genuinely aiming to empower nurses to work at their full potential. 2. AI is not about reducing our need for human touch. Rather, it enhances human efficiency in the workplace. More tasks done by AI = more human time with patients. 3. The future lies in AI solutions that assist nurses and care teams in delivering more effective care. It is crucial that clinicians are integral to the development of these technologies. Thoughts? Dominick Pahl, M.S., R.N.Erika Rolland, MSN, RN, RN-BCRachel SantarpiaBonnie Clipper DNP, MA, MBA, RN, CENP, FACHE, FAANEdwina Bhaskaran #AI #nursingleadership #ChatGpt #healthcare

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ICYMI: Our CEO Rajaie Batniji spoke at Fortune Brainstorm Health this week on value-based care and AI. Thanks to Christina Farr, Sachin H. Jain, MD, MBA, and Brent Nicholson for an insightful discussion! “So much of how we talk about AI in healthcare is focused on replacing humans, and I think that’s totally wrong. Our approach to AI development is to automate the routine tasks so that we can allow our care team to spend as much as possible with patients. Second, let’s automate the identification of which patients are going to benefit from certain services so that we can spend our time targeting the appropriate groups. That’s where you have step-change in improving access to care.” Watch the recording here: https://wymrk.co/3KdruPb

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The MedCity News article highlights the issue of data fidelity in healthcare. Despite the vast amount of data generated, much of it is unreliable, hindering effective decision-making. Challenges include fragmented systems and poor patient identity matching. Solutions proposed include investing in master data management (MDM) systems, complying with the Cures Act, and improving data accuracy to handle future data influxes. Legislative measures like the Match IT Act aim to improve data standardization and interoperability, essential for leveraging data for improved patient outcomes and operational efficiency. https://lnkd.in/epytxJWv #healthcare #healthcareit #healthcaredata #bigdata #ehr #emr #his

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The goal isn't so much to build something as it is to test a hypothesis and then gain an understanding. You must figure out how to phrase your prompts to get the most useful response. Learn to become a "Prompt Engineer"

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I’ve been at Kooth for 2 months now, and I’m so in love with my job! 💗 This role has reminded me how essential it is to work for a company that aligns with our values, and I want to take a moment to highlight my three favorite things about working at Kooth: ✨ I’m part of the mission to implement free mental health support for all California youth aged 13 to 25  Kooth provides universal access to mental health support for teens and young adults that's free at the point of service, something I’ve been fighting for my whole career! My role is to help get the word out about our app Soluna, funded by the California Department of Health Care Services (DHCS), to provide free mental health support for all California youth aged 13 to 25. This is HUGE – free support, in their pockets, whenever they need it, for millions of young people! ✨ I get to work for a company that values autonomy, the lived experience, and peer support  #Soluna gives users complete control over their mental health journey. Whether they choose to explore interactive resources, join peer support forums, or engage in 1:1 coaching with certified professionals, Soluna empowers them to seek support their way. Our coaching team includes certified peer support specialists with diverse backgrounds and lived experience. Connecting with someone who shares similar experiences helps us feel less alone and more understood. I’m proud to be part of a company that prioritizes this approach! ✨Soluna adopts a holistic, person-centered approach, addressing various life challenges and social determinants of health, not just mental health issues  For example, users seeking housing resources can access them within the app and receive coaching support. Our coaching emphasizes setting meaningful goals tailored to the individual rather than solely focusing on symptoms. Within one month of using Kooth, 69% of users in the UK report significant progress toward their goals. We aim to empower young people to shape the lives they desire! Ok, ok. I’m done boasting…for now…😛 (If you want to chat more about Soluna and our California project or learn more about what it’s like working for Kooth, message me!) Want to explore on your own? Visit our site: https://solunaapp.com/ #SolunaApp #MentalHealth #MentalHealthAwareness #MentalHealthMatters

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Based on what I was hearing at the California Health Information Association meeting this week, I feel like suggesting that #interoperability is at a 'routine' stage is an overstatement. I am sure that is, in part, an interpretation of the meaning of the words "interoperability" and "routine", but it's my opinion that we still have a lot of work to do to stop printing and faxing records and make information exchange ubiquitous. Thoughts?? Open to being proven wrong on this assessment. #CIACon24 #HealthITRockStar https://lnkd.in/gRTHRnc7

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Last week, Elion covered the AI prior auth space for providers. This week we're looking at it from the payer side. For payers, prior authorization (PA) is a necessary burden: important for utilization management (UM) and financial planning, but a nightmare to manage. After PA requests are sent in, payers have to process the request from various channels into a case, match it with clinical criteria, validate required information, review and make the PA determination, then respond and iterate through any appeals. As payers update their procedures with new clinical evidence guidelines and new diagnostics and treatments, managing policies and creating decision trees for PA decisions requires enormous effort. Payer-facing AI prior authorization platforms have a huge opportunity to streamline these workflows by: 📒 Improving rules-engine generation and updates from unstructured policy documents and PDFs 📤 Automatically processing PA requests across all channels ✅ Matching the case to the right clinical criteria, validating data completeness, and determining if policies have been met through machine learning models and generative AI 📬 Generating decision documents and automating appeals correspondence with providers Several vendors are already making strides in AI-enabled PA for payers. Banjo Health offers tooling both for the PA request and clinical decision policy creation workflows for health plans, TPAs, and pharmacy benefit managers. basys.ai uses LLMs to offer rapid ingestion of policy documents for fast integration and up-to-date policies. Cohere Health is one of the more mature vendors in the space, and offers a variety of products for UM. Co:Helm is a generative AI platform for payers, with initial use cases around enabling UM nurses to make complex PA decisions more quickly. Finally, GenHealth.ai has built their own large medical foundation model and is using it to enable both rapid policy ingestion and PA review. We see PA as the first place where payers will incorporate advanced clinical AI. Although PA denials should never be fully automated, vendors that can drive efficiency here stand to become a core part of payers’ clinical decision-making process. --- We received a number of interesting responses last week regarding the AI prior auth space. We're continuing to dive deep here, so please reach out if you're currently investigating it and would like to discuss.

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🌟 Exciting Insights from the Latest Harvard-Inovalon Medicare Study! 🌟 As professionals in the Medicare Advantage space, we’re always on the lookout for data that underscores the efficacy and efficiency of MA plans. A recent study by Harvard and Inovalon has brought some compelling findings to light, showing that Medicare Advantage not only reduces healthcare expenditures but also maintains high levels of care compared to traditional Medicare Fee-for-Service. Here are some key takeaways: - MA enrollees experience over 50% fewer inpatient stays and 22% fewer emergency visits compared to FFS, with no significant reduction in primary care or prescription drug services. - Overall, MA shows a 12% reduction in health expenditures, highlighting its efficiency in managing healthcare resources. At Sonder Health Plans, we're proud to say that we're already implementing many of the strategies that make Medicare Advantage so beneficial. Our focus on care coordination and preventive care isn’t just about keeping costs down—it's about providing a foundation for healthier, happier lives for all our members. This study reinforces the value of the Medicare Advantage program and the potential for more innovative, cost-effective care models. Let’s continue to push forward, driving improvements that matter. #MedicareAdvantage #HealthcareInnovation #SonderHealthPlans

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5 months ago, Kaiser Permanente implemented an AI to reduce physicians' workload and reduce burnout. Today, they’ve saved physicians hours of effort by diverting 1.5 million out of 4.7 million patient messages to an AI that resolved them. I was pretty intrigued by this experiment and how the system was set up. Here’s what I found: 1. The main goal was to reduce the workload on physicians by automatically handling simple patient queries like pharmacy hours or medication refills through the AI system. 2. The AI system processed over 4.7 million messages for five months. Out of these, approximately 1.5 million messages, or 31.9%, were handled by the AI without needing to reach a physician. 3. The AI system categorized messages and redirected them to appropriate staff members, such as medical assistants or pharmacists, based on the content. This AI was used to attach labels to the messages for categorization. 4. The AI was initially trained on 20,000 patient messages given by triage nurses and physicians, and it received updates every two months. This helped in improving its accuracy and adaptability over time. 5. The implementation showed significant improvement in managing message traffic &  It also provided insights into health trends and improved patient care through quicker responses. When we talk of implementing AI on a large scale, I imagine that systems like these will be mainstream. EMRs like our midoc.ai platform, conversational AI like Kaiser’s AI & other tools coming together for solid patient care. Looking forward to what new implementations come our way this year. What do you think of Kaiser’s system?

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Lets talk #healthtech in AZ. ⚕ 💻 Last year, Arizona invested $242 million in health tech companies.  2024 year-to-date is at $112 million within this sector and we are tracking towards a projected 34% increase year-over-year of investment into health tech.   Notable recent investments in Q1 '24 include: $3.3 million seed round for Rivia Health. $2.3 million seed round for Imagen Dental Partners. $3.9 million Series A for Med-Surgical Services Services. Arizona is quickly becoming a premier destination for top health tech companies and founders!   We'd like to recognize active Arizona investors and venture studios focused on this sector, such as Bluestone Ventures in Tucson, Desert Angels, Canyon Angels, The Journey Venture Studio, Banner Capital Ventures Inc, The Blue Venture Fund, and Emmeline Ventures. Source: Phx Startup Ecosystem Dashboard - Snapshot of health tech investment activity as of 5/9/24 https://lnkd.in/ge2_KRuA

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