David Bourque’s Post

This article from CLARA Analytics explains how AI can reduce medical costs for Workers' Comp claims. https://lnkd.in/d4KEa6SU #insurtech #insuranceagent #insurancebrokers #generativeai

It's crucial we focus new technology like #GenerativeAI on the protection of the patient-physician relationship—the true joy of medicine! Always an honor to join Anjalee Khemlani on Yahoo Finance. 57% of Americans trust their doctors; we have to focus on how AI can amplify those trusted relationships, giving science the comeback it needs. Read more on the potential of AI across healthcare: https://yhoo.it/46zya2I #AI #YahooFinance #Patients #DigitalTransformation Brian Sozzi

Ethan Mollick is one of the most provocative researchers on how AI will transform our day-to-day jobs, and his new book 𝐶𝑜-𝐼𝑛𝑡𝑒𝑙𝑙𝑖𝑔𝑒𝑛𝑐𝑒 rounds up his best thinking. Here are 3 striking quotes – and my quick reflections on what they imply for healthcare. 𝟏. “𝐆𝐞𝐧𝐞𝐫𝐚𝐥 𝐏𝐮𝐫𝐩𝐨𝐬𝐞 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 [𝐬𝐮𝐜𝐡 𝐚𝐬 𝐀𝐈] 𝐭𝐲𝐩𝐢𝐜𝐚𝐥𝐥𝐲 𝐡𝐚𝐯𝐞 𝐬𝐥𝐨𝐰 𝐚𝐝𝐨𝐩𝐭𝐢𝐨𝐧, 𝐚𝐬 𝐭𝐡𝐞𝐲 𝐫𝐞𝐪𝐮𝐢𝐫𝐞 𝐦𝐚𝐧𝐲 𝐨𝐭𝐡𝐞𝐫 𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐭𝐨 𝐰𝐨𝐫𝐤 𝐰𝐞𝐥𝐥.” Consider the internet, which took decades to transform our world as individuals, organizations, and markets figured out how to use it effectively. Similarly, healthcare will need many years to adapt our practices for AI. We'll need to do the hard work of implementing AI in every exam room, every back office, and every C-suite. But when we're done ... wow, what a different world we'll live in. As Amara's Law puts it, "We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run." 𝟐. “𝐖𝐡𝐞𝐧 𝐰𝐞 𝐮𝐬𝐞 𝐀𝐈 𝐭𝐨 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐞 𝐨𝐮𝐫 𝐟𝐢𝐫𝐬𝐭 𝐝𝐫𝐚𝐟𝐭𝐬, 𝐰𝐞 𝐭𝐞𝐧𝐝 𝐭𝐨 𝐚𝐧𝐜𝐡𝐨𝐫 𝐨𝐧 𝐭𝐡𝐞 𝐟𝐢𝐫𝐬𝐭 𝐢𝐝𝐞𝐚 𝐭𝐡𝐚𝐭 𝐭𝐡𝐞 𝐦𝐚𝐜𝐡𝐢𝐧𝐞 𝐩𝐫𝐨𝐝𝐮𝐜𝐞𝐬, 𝐰𝐡𝐢𝐜𝐡 𝐢𝐧𝐟𝐥𝐮𝐞𝐧𝐜𝐞𝐬 𝐨𝐮𝐫 𝐟𝐮𝐭𝐮𝐫𝐞 𝐰𝐨𝐫𝐤.” This is an example of automation bias: deferring to automated decision-making systems, rather than using our own judgment. It's particularly hazardous in healthcare, where, for example, a radiologist who’s presented with an AI-generated diagnosis might not bother to second-guess the AI’s output. When I use AI tools such as ChatGPT in my own work, I try to avoid automation bias in a few ways: (1) by pausing to consider my own perspective before asking the AI to weigh in; (2) by asking the AI to help me think through a topic, rather than offering its own solution; and (3) by asking the AI to give me 5-10 diverse perspectives to consider, rather than just one. 𝟑. “𝐀 𝐥𝐨𝐭 𝐨𝐟 𝐰𝐨𝐫𝐤 𝐢𝐬 𝐭𝐢𝐦𝐞-𝐜𝐨𝐧𝐬𝐮𝐦𝐢𝐧𝐠 𝐛𝐲 𝐝𝐞𝐬𝐢𝐠𝐧…. [𝐂𝐨𝐧𝐬𝐢𝐝𝐞𝐫] 𝐭𝐚𝐬𝐤𝐬 𝐰𝐡𝐨𝐬𝐞 𝐟𝐢𝐧𝐚𝐥 𝐰𝐫𝐢𝐭𝐭𝐞𝐧 𝐨𝐮𝐭𝐩𝐮𝐭 𝐢𝐬 𝐢𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐛𝐞𝐜𝐚𝐮𝐬𝐞 𝐢𝐭 𝐢𝐬 𝐚 𝐬𝐢𝐠𝐧𝐚𝐥 𝐨𝐟 𝐭𝐡𝐞 𝐭𝐢𝐦𝐞 𝐬𝐩𝐞𝐧𝐭 𝐨𝐧 𝐭𝐡𝐞 𝐭𝐚𝐬𝐤 𝐚𝐧𝐝 𝐨𝐟 𝐭𝐡𝐞 𝐭𝐡𝐨𝐮𝐠𝐡𝐭𝐟𝐮𝐥𝐧𝐞𝐬𝐬 𝐭𝐡𝐚𝐭 𝐰𝐞𝐧𝐭 𝐢𝐧𝐭𝐨 𝐢𝐭 – 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 𝐫𝐞𝐯𝐢𝐞𝐰𝐬, 𝐬𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐜 𝐦𝐞𝐦𝐨𝐬, 𝐜𝐨𝐥𝐥𝐞𝐠𝐞 𝐞𝐬𝐬𝐚𝐲𝐬, 𝐠𝐫𝐚𝐧𝐭 𝐚𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬, 𝐬𝐩𝐞𝐞𝐜𝐡𝐞𝐬, 𝐜𝐨𝐦𝐦𝐞𝐧𝐭𝐬 𝐨𝐧 𝐩𝐚𝐩𝐞𝐫𝐬.” One such task in healthcare might be prior authorization, which physicians have long claimed is used to gatekeep expensive care. In this view, if AI made it easier for physicians to file prior authorization requests, insurers might replace them with a different hurdle – so the payoff from automation might be lower than anticipated. What other intriguing books or articles on AI have you been reading lately? Any quotes stand out as particularly provocative?

In case you were unsure if AI documentation was a big deal. It saves clinicians time and increases patient engagement (among other things), and they will become table stakes for most practices. Here are the numbers : MDs in America 938,966 DOs in America 186,000 PAs in America 168,318 NPs in America 211,280 DPMs in America 18,000 Total 🟰 1,522,564 That makes AI documentation a $2.2 to $9.1 Billion market each year if you assume $120-500/ month for a clinician to use a tool. (Current Market prices and some are higher) Now are you paying attention?

In the least surprising lead-in of the day, people are excited about #artificialintelligence 😁 According to an AMA survey, #physicians thought AI would be the most helpful in: ·       🦴Diagnostic ability: 72% ·       🏃♀️Work efficiency: 69% ·       ✅Clinical outcomes: 61% ·       ✏Documentation of billing codes, medical charts or visit notes: 54% ·       📞 Automation of insurance prior authorization: 48% ·       📝Creation of discharge instructions, care plans or progress notes: 43% Many of the respondents were also worried about the impact on patient/physician #relationships and #patient privacy. So how do you start to work with #AI? Don't expect it to be a fully patient-facing robot that controls the entire relationship. Instead, see it for what it is: a tool to help you actually focus on the patient. Look for areas that it can assist, not replace. For example, one of the issues we hear about repeatedly is the clinician focusing on the screen in front of them instead of the patient in the chair. That's understandable as you want to make sure you note the conversation and document everything. But what if AI could do that for you? Then you could focus on the patient.

From LLMs for clinical decision support, to best-in-class medical chatbots, healthcare is paving the way for applied generative AI. Here are 4 lessons #healthcare can teach us about successful applications of #AI: https://trib.al/8AkywJb

Using data, machine learning, and predictive analysis, hospital systems & insurers will reap benefit$ by improving clinical operation$ leveraging AI for continuity of care, like referral management---to hospice. https://lnkd.in/gyiT5BKT .

In our latest case study, discover how our AI-powered retrieval solution helped a large state Blue Cross Blue Shield Plan achieve: • +1k hours saved • 53% faster medical record retrieval turnaround time • 75% reduction in chart review staff • 50% reduction in outreach staff Learn how this BCBS Plan eliminated manual workflows, accelerated record collection, and drove a smoother audit process. Find it here: https://bit.ly/4eY8Qc9 #IVA #auditdeadlines #AI

➡ Via Healthcare IT News: "Further, with #AI doing the routine and boring work, the professionals will have time for patient financial counseling, complicated claims and managing appeals. AI tools can assist in these tasks, essentially being copilots to enable #RCM professionals to focus on the most critical work."

4 lessons healthcare can teach us about successful applications of AI The healthcare industry is the exception, with a breadth of generative AI use cases under its belt. - Patient journey trajectories  - Improvements to medical chatbots  - Democratizing generative AI  - Addressing challenges and ethical considerations #Healthcare #AI #Technology https://lnkd.in/g6BmhApt