Ryan Lissack

We're underestimating how physicians will build and access software in the future and we're 100% underestimating how this will impact independent practice. By now I'm sure you've seen the Claude 3.5 Sonnet demos and all of the use cases or application non technical folks are building with 1-3 line prompts. Even Jensen Huang, CEO of Nvidia made a controversial comment on the future of coding, “It is our job to create computing technology such that nobody has to program. And that the programming language is human, everybody in the world is now a programmer. This is the miracle of artificial intelligence,” This is absolutely true, and if there's one area where this will have the biggest impact on society, it will be healthcare. The reason for that is that physicians and clinicians have NOT been included in the design of healthcare technology over the last 20ish years, leaving them to practice in systems designed by non-clinical people. Claude 3.5 offers a glimpse into the future of independent practice. Physicians will be able to design, build, and launch AI applications as needed without requiring developer support. In the future, I envision independent practices hiring their own AI Agent developers who can not only build these applications, but also integrate them into their practice operations infrastructure to create the ultimate practice management system. What application would you build if this were possible today? ----- Hi, I'm Dr. Mario Amaro, Founder and CEO Ease, and I talk about all things starting, running, and growing a private practice with AI. Follow me, if you are planning to start one or are currently figuring out creative ways to grow one. #PrivatePractice #SelfEmployment #HealthcareOnLinkedin #HeyEase #IndependentTogether #Fintech #Infrastructure #AIinHealthcare #CareDelivery

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How to improve #interoperability through #FHIR? Efficient interoperability is key to the democratization of data, but smaller EHRs have been slow to join the movement. CapMinds and Vozo have helped its #ehr clients especially smaller one to join the #fhir movement.

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One key reason why healthcare technologies like AI, telemedicine, and software haven't structurally lowered costs or broadened access for the entire system after decades of experimentation (excluding pure financial engineering of payer contracts) is the limited reimagining of care delivery itself, with asynchronous telemedicine as a notable exception. In the same way that digitizing physical paper failed to exploit the capabilities of a new computing medium for word processing, hosting physician-patient conversations over video does not transform the actual delivery of care. In telemedicine, many of the inputs (e.g., clinician time) and therefore cost structures of in-person care persist, which is why we often see fee-for-service telemedicine companies struggle to achieve economies of scale (i.e., growing revenues non-linearly while growing costs linearly). Until we deconstruct the components of a medical appointment – from intake and triage, to chart review, history gathering, physical examination, diagnosis, treatment, and follow-up – we will continue to be underwhelmed by the disconnect between the transformative potential of these technologies and real-world patient/system impact. I’m optimistic that the emergence of reliable and performant medical AI agents will urge us to perform this deconstruction and redesign the fundamental building blocks of a “medical appointment.”

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In case you missed it, last week the Coalition for Health AI (CHAI) released a draft consensus framework for responsible health AI. Developed with input from over 100 contributors representing a diverse network of healthcare stakeholders, this guide proposes actionable evaluation criteria throughout the AI lifecycle—from identifying use cases to deployment and monitoring. Key examples outlined in the guide include: • Predictive EHR Risk Use Case (Pediatric Asthma Exacerbation) • Imaging Diagnostic Use Case (Mammography) • Generative AI Use Case (EHR Query and Extraction) • Claims-Based Outpatient Use Case (Care Management) • Clinical Ops & Administration Use Case (Prior Authorization with Medical Coding) • Genomics Use Case (Precision Oncology with Genomic Markers) The draft framework is open for public review and comment for the next sixty days. Please use this form to submit feedback: https://lnkd.in/eYughFYC Kudos to the CHAI team led by CEO & President, Dr. Brian Anderson, MD, on this milestone. Eric Horvitz Jennifer Goldsack John Halamka, M.D., M.S. Michael Pencina Micky Tripathi Nigam Shah Suchi Saria Troy Tazbaz #healthcare #ai #artificialintelligence #generativeai https://lnkd.in/e7VRv6fD

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One of the biggest open secrets is that the healthcare market is mostly closed to vendors that don't understand healthcare economics. What we found in research for our AI & Cybersecurity for Boards book (forthcoming) is more boards of directors now expect the whole C suite including technical and clinical executives to be up to speed on the basics. This post on DRGs is part of a series of posts for shared taxonomy within the Trustworthy Technology and Innovation in Healthcare Book Series .  Yesterday, I posted about how hospitals get paid: "CPT (current procedural terminology): Describes services a healthcare professional provides to a patient. DRG (diagnostic-related group): Categorizes hospital services using information from a patient's diagnosis (ICD), treatment provided (CPT), and other factors." "When you've been admitted as an inpatient to a hospital, that hospital assigns a DRG when you're discharged, basing it on the diagnosis you received and the treatment that you needed during your hospital stay. The hospital gets paid a fixed amount for that DRG. If a hospital can effectively treat you for less money than Medicare pays for your DRG, then the hospital makes money on that hospitalization. If the hospital spends more money caring for you than Medicare gives it for your DRG, then the hospital loses money." "DRG stands for diagnosis-related group. Medicare's DRG system is called the Medicare severity diagnosis-related group, or MS-DRG, which is used to determine hospital payments under the inpatient prospective payment system (IPPS). It's the system used to classify various diagnoses for inpatient hospital stays into groups and subgroups so that Medicare can accurately pay hospital bills. DRGs -the goal is to ensure that Medicare reimbursements adequately reflect "the fundamental role a hospital’s case mix (the type of patients the hospitals treats, and severity of their medical issues) plays in determining its costs" and number of resources that the hospital needs to treat patients." "When a patient with Medicare (or many types of private insurance) is hospitalized, a DRG code is assigned. There are numerous determining factors for each patient and each DRG has a different relative weight, depending on the resources that are generally needed to provide care for someone with that DRG. Each hospital has a blended base rate, which is based on a variety of factors, including location, patient demographics, whether it's a teaching hospital, etc. The relative weight of the DRG is multiplied by the hospital's base rate to determine how much the hospital will be paid for that patient." "article explains how DRG system works and determines the payment amounts that hospitals receive." https://lnkd.in/gXRYXrQk Thanks to Robin Farmanfarmaian et al and more for inspiring this post series June 4-6. Next up! The role of technology in driving quality & finance

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Some MAJOR NEWS for the no-code/AI space in healthcare. Airtable is now HIPAA compliant! This is a game changer for database access, which has been dominated by traditional SQL databases, and has limited the ability of the average doctor, clinician, or weekend hacker from creating their own headless EHR or digital health applications. I'm excited to see where this goes and what people build and expect Ease's AppStore to have a robust Zapier like integration with Airtable to make building healthcare businesses 10x easier. https://lnkd.in/gG9ssKuS ------ Hi, I'm Dr. Mario Amaro, Founder and CEO Ease, and I talk about all things starting, running, and growing a private practice with AI. Follow me, if you are planning to start one or are currently figuring out creative ways to grow one. #PrivatePractice #SelfEmployment #HealthcareOnLinkedin #HeyEase #IndependentTogether #Fintech #Infrastructure #AIinHealthcare #CareDelivery

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The defining factor isn't the size of the company or startup, but the vision behind it. Take OpenAI, for instance. Until last year, unless you were deeply embedded in the ML world as a computer scientist/researcher, or enthusiast, you might not have heard of OpenAI. Meanwhile, a giant like Google was dominating the scene. However, a few years back, OpenAI was just another small startup. Now, it's rapidly evolving into a major player in big tech. Why and how? It comes down to having a long-term vision, a clear roadmap, patience, and solid execution (i.e., talents). Even in the context of healthcare AI, where (small) startups face many challenges (including the ones mentioned), the principles of vision and strategy apply. While merging with big tech might seem like an option for some, if a startup truly believes in its vision and has a well-defined path to achieve it, it should forge ahead independently. The landscape is evolving, and like OpenAI, today’s small startups with clear, visionary goals could be tomorrow's industry leaders. #starup #founders #openai #google #healthcare

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As the AI-accelerated future unfolds, ownership and sovereignty of data is vital and is the focus of Native BioData Consortium. Here, they share a paper co-authored by their Executive Director Joseph Yracheta presenting a framework for reducing biases and reducing disparities in the integration of AI into health care.

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AI NEWS SERIES Trovo Health Secures $15M Seed for AI Healthcare Expansion Product: - Trovo Health's AI platform integrates specialty-specific workflow technology and a multidisciplinary care team, enhancing provider capabilities and efficiency. - The platform enables physicians to add complex, specialty-specific tasks, thereby improving patient outcomes and experience. Company: - Founded in 2024 in New York, NY, Trovo Health secured $15M in Seed funding from Oak HC/FT, aiming to revolutionize healthcare delivery. Impact: - Trovo's technology facilitates significant enhancements in healthcare delivery, enabling seamless integration of advanced AI with clinical operations, which streamlines provider services and enhances patient care. sources: businesswire #technology #innovation #future #artificialintelligence #business

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Excited to share my recent article on Patient Safety and Quality Healthcare! Discover how innovative digital solutions are reshaping patient care and safety. From predictive analytics to real-time monitoring, explore the future of healthcare and how we can achieve excellence in patient outcomes. Let’s innovate together! #DigitalTransformation #HealthTech #FutureOfHealth

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If you are in software or innovation generally, you should read David Heinemeier Hansson - he is so perceptive and ahead of the curve. This post is fascinating, but I want to extend it a bit to healthcare. There is always a sense that bigger is better and what David is saying is that you need to go a level deeper. For the last decade, I kept hearing that a big company initiative into healthcare would sweep the field clean. Nothing could be further from the truth - focusing on healthcare outcomes - when it is all you do - is the path to a great company. https://lnkd.in/eeDdu-G9

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Wondering about #PlatformEngineering hidden traps? I share some thoughts on the matter with health tech magazine. To me this reculumination of central SOA team with a twist. Your customer are internal developers and business users. DM if you would like to discuss more.

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The debate about who controls one's own healthcare data is fundamental to how we evolve our health systems. - It enables us to manage our #wellness on an ongoing basis rather than any illness that may occur - It enables us to contribute our unique #realworlddata as we see relevant for #clinicaltrials or #populationhealth studies - It enables us to optimise #healthsystems to increase efficiency and improve #valuebasedoutcomes - It enables us to address #diversity and #bias through synthetic data generation where gaps exist - It gives us the potential of #portability of service for our healthcare needs The article from Artur Olesch shows how badly broken current systems are around the world. Currently Governments; Health Care Providers; Insurers; Tech Companies and Health Care Professionals all manage our healthcare data. Innovation in this space to enable citizens and patients to manage their own data assets and benefit from #genai tools to analyse will provide us with the next great leap forward in terms of health outcomes and system efficiencies.

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To follow up on Dede Ainbinder recent post: If we use the current EHR data to build a AI clinical decision support tool it is unlikely to capture our clinical decision making process. EHR's are inherently designed to maximize billing and minimize risk of litigation. A clinical decision support tool based on this data will likely do the same. There is a large sunken cost fallacy here where we continue to hang on to garbage data. Just because the data gathering and storage process was capital and time intensive doesnt mean the data is valuable. To truly capture the clinical decision process we need to capture data which sits outside billing and litigation. Its hard to imagine a future where this data isnt used for billing and cannot be called upon during litigation. #EHR #healthdata #clinicaldecision

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STATworkUP®, is a medical app intended to Enable A New Era In Healthcare. 1. STATworkUP™ rapidly builds prioritized or alphabetized lists of potential diagnoses, based upon findings you designate or signify by adding checkmarks to listed items. 2. STATworkUP correlates findings, tests, disorders and remedies, to help you evaluate, diagnose and manage many medical problems. 3. You can even adjust the output results by setting a probability meter to expand or constrain the resulting array of differential diagnoses based on the amount of likelihood you desire. 4. STATworkUP can help you to shift focus from the chief complaint to facilitate discovery of less obvious, but significant, manifestations and plausible causes as workup proceeds. 5. The user interface features typical approaches to investigation, so its operation will be fairly intuitive to medical practitioners. 6. The program quickly calculates and shows diagnoses that fit with the selected findings for all of the conditions in the database. 7. Weights of corroborative findings are rapidly processed, to create lists of possible differential diagnoses for your consideration. 8. Locate any symptom, study, diagnosis or treatment on full lists in a flash, using tools that let you search by synonyms, categories, and even by voice activation. 9. Subject matter expert web pages are also readily available for each entry in the database, and you can link to them from within the application at the touch of a button. 10. The content, user interface and structure of this application have been carefully crafted during 30 years by practicing physicians, computer engineers, mathematicians and medical informaticists. The IatroCom® team keeps the info current to stay up-to-date over time too. Plus no subscriptions are required once you get the app and it comes with no annoying advertisements either. Additionally, it has Free, frequent database updates after an affordable initial purchase. Like other customers you will probably be glad to have STATworkUP. It is a great learning and reference resource for all types of healthcare providers, from students to senior directors ... and they just love it. STATworkUP® DDx is NOT intended to supplant sound medical judgment! It Is NOT Intended To Treat, Diagnose, Cure, Mitigate, Or Prevent Disease Or Other Conditions. Have a look at these sites to find out more info about this elegant and amazing medical app: See it in action here:  https://lnkd.in/bm75XKM Read more about it here:  https://www.statworkup.com This dazzling new, best-in-class, medical software is only available for sale at the Apple App and Google Play Stores. You can get the latest version of STATworkUP here now, to improve comprehensive examinations, and enhance excellent care:  https://lnkd.in/buE-rTk https://lnkd.in/gXWR7Xt 

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The healthcare system is broken, or at least hugely unoptimized, from any reasonable perspective (flatlined outcomes, falling patient/provider satisfaction, rising costs, etc.) The market for new health technology is framed around this flawed system. Almost all health tech innovation funding, private and increasingly public, is steered towards near-term product-market fit. The overall health ecosystem is incentivized to perpetuation decline and dilute transformative innovation. Perhaps it is time for a new approach at a systems level? AI MINDSystems Foundation #health #tech #science #research #outcomes #ecosystem

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Healthcare technology is in trouble. After the relative boom time we experienced through during the pandemic, the fervor to innovate in health systems and payers seems to have dried up. While organizations continue to post stellar earnings, they also continue to lay off experienced health technology people en masse. Why? I think it's time for a bit of honest reflection. 70% of all enterprise healthcare technology projects fail. 17% of of all large scale IT projects go so badly that they threaten the very existence of the company itself. Bridging Business & IT, LLC For projects with a total price tag of over $1MM, that failure rate jumps to over 90%. And the ever prescient Clayton Christensen believed that the failure rate for all new product introductions is 95%. This is not new information. What is new is the most recent E&Y Pulse Survey that has health system CIOs believing that 7 in 10 of their healthcare IT projects have had no discernible #ROI. None. And this is for the projects that didn't fail. https://lnkd.in/gRgVt_Xs This is an existential crisis that health technology must face honestly and soberly. Lack of planning and poor communication are the core culprits. Clunky and outdated Waterfall project methodologies can be blamed for many of these failures. And frankly Agile disciples could use a bit more planning before they start iterating so they know what they're building. There are, however, some problem actors and business models that need to be called out. The historically biggest culprits, in my humble opinion, are large, institutional, enterprise software vendors and their server-based architectures. For decades they feasted on seven figure licensing deals, sometimes humble-bragging to potential implementation partners about 5:1 or 7:1 implementation cost to license cost ratios. Companies just went along with it, because no one gets fired for buying IBM, right? But the failures in this segment are legendary. And many have indeed been a key cause in the parent company failure. As for the ROI, there was a bright spot in the E&Y Pulse Survey. Despite not having established a demonstrable ROI, 96% of them still wanted to move forward with the projects, believed the investment was worth it. So the issue isn't necessarily that the projects aren't generating value, the issue is that the organizations (and their vendors) didn't do a good job up front validating agreed upon ROI metrics and measures. They don’t fully understand the value it is (or isn't) creating. This is our collective job to be better at this. So what can we do to reduce the failure rate and get health systems and payers back into investing in #innovation? #ROI #startups #valueengineering #goldenpath #LCNC #opensource

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A follower asked me, "How can I get MDM credit for reviewing telemetry?" "Can I use it as independent interpretation of a test (Category 2)?" Here's my response: -- //Use in Category 2\\ The AMA says that for category 2, the interpretation must be one that is "typically performed by another physician or qualified healthcare professional" and for which an "interpretation or report is customary." So, while EKG's would count because they ARE typically given a formal report / interpretation by a cardiologist, I would not say the same about telemetry as they don't typically undergo a formal read by another physician / QHP. -- //Use in Category 1\\ However, I'd say you could get credit for telemetry as a test that you order or review. The AMA says that "tests that do not require separate interpretation (eg, tests that are results only) and are analyzed as part of MDM do not count as an independent interpretation (as stated above) but may be counted as ordered or reviewed for selecting an MDM level." -- //Use as High risk\\ One option in the high-risk category is "drug therapy requiring intensive monitoring for toxicity." They say that this "intensive monitoring" can be done using "physiologic data" such as EKG's (defined in AMA's CPT code 99091 and CMS's MLN 006764) and I would extend that to telemetry as they fall under the same type of "physiologic" assessment but do not use the same qualifying language of "typically performed by another physician...etc" in this instance. So, for example, if you started a patient on a new antiarrhythmic medication or are giving a patient high doses of a QT prolongating medication and felt telemetry was required to monitor for toxicity, then I would say that counts. As always, I recommend being clear that you are using these elements by specifying clearly in a "billing timeout" with a Medical Decision Making section. Agree? Other thoughts? Be on the lookout for a launch of something special August 1! ------- If you liked this post, consider reposting to share with your audience. I'm Dr. Robert Oubre, a CDI medical director and hospitalist, and I teach residents and new inpatient physicians how to bill and document.

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