Lead magnet LinkedIn — Healthcare

Healthcare

Post LinkedIn lead magnet · Healthcare

How do you get Predictable High Performance from your team from Day 1? Easy. Follow a basic logistics tenet called OTIF OTIF means distributed “on time” and “in full” My current 9-5 work is about building robust global, regional, and local health supply chains the deliver uninterrupted supply of medicines and medical supplies to all health facilities in a country. The most critical metric is OTIF. When a health facility orders 100 paracetamol, do they receive a 100 paracetamol within a specific window? By focusing on OTIF, you can surface 95% of the problems in a supply chain. In fact, the quality, whichever way one measures that is a function of OTIF So, how does this apply to Predictable High Performance of teams? Here is the thesis; ✅ An average talent will eventually deliver high quality work in a disciplined system, where they deliver work on time, and in full. Notice that quality is a lagging indicator ✅ A superstar talent will be regress to mediocrity if there is no culture of timely execution and completion. If you understand the above thesis, you will realize that high quality work is a function of operational discipline. Yes, there is psychology, biology and systems-thinking built into this idea, but won’t get into all that today If you want to get your team to execute at the highest level from Day 1, I developed a guide you can access today. Execute the guide with discipline and consistency, and Predictable High Performance is possible from Day 1. Check it out in the comments section… Let’s go!

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I developed a guide you can access today. Execute the guide with discipline and consistency, and Predictable High Performance is possible from Day 1. Check it out in the comments section…

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J'ai créé le chatbot le plus puissant qu'on puisse avoir en France : Claude X Data Gouv... Je t'explique tout Le concept est simple. Je pose une question. Claude analyse. Il me répond avec les vraies données officielles françaises. Comment ? J'ai couplé Claude à DataGouv via le MCP officiel. DataGouv c'est LA plus grande base de données publiques et fiables de France. Immobilier. Santé. Entreprises. Budgets. Transport. Éducation... Tout est là. Tout est officiel. Tout est vérifié. ( Et c'est open source ) Le problème ? Ces données étaient inaccessibles pour 99% des gens. Fallait savoir coder. Télécharger des CSV. Comprendre des API. Grâce au MCP, Claude se connecte directement à cette base. Il cherche. Il sélectionne le bon dataset. Il analyse. Il répond. En langage naturel. En quelques secondes. « Quels sont les prix immobiliers à Lyon par arrondissement ? » “Quelles communes de plus de 20 000 habitants ont une forte croissance démographique mais peu de cabinets de kinésithérapie ?” “Où y a-t-il une forte densité de jeunes actifs 25–35 ans mais peu de formations tech ?” “Quelles régions distribuent le plus de subventions à la digitalisation ?” Réponse instantanée. Source officielle. Zéro hallucination. C’est ça qui change tout. Pas une IA qui invente. Une IA qui sait où chercher la vérité. J'ai créer un ChatBot de ZinZin qui me permet de faire des analyses concrètes, de faire des études concurrentiels, étudier les opportunités, ou et surtout dans quel secteur d'activité je peux implémenter l'IA par exemple... C'est juste énorme Tu me connais, je pense, je t'ai fais : - Un Guide complet qui explique comment utiliser et créer une tel app - Les prompts au complet - L'accèes à ce fameux MCP ( Le repo GitHub ) - Des exemples d'utilisation Commentez " DataGouv" et je te l'envoie Je vous invite et republier ça peut clairement aider votre réseau

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I mapped every AI automation opportunity across 25 industries. 10-15 pain points each. With the exact positioning, pricing range, and who to sell to. This took me 4 years and 80+ client engagements to figure out. A lot of AI Agencies pick a niche and pray. They don't know the actual pain points. They don't know who the buyer is. They don't know what these companies are already paying for broken solutions. They don't know what the realistic project size is. So they end up competing on price for generic "AI automation" gigs. I've worked with marketing agencies, recruiting firms, e-commerce brands, law firms, real estate companies, healthcare practices, financial services, SaaS companies, manufacturing, construction, logistics, and more. Every single one has 10-15 processes that are bleeding money because they're still done manually. Here's what the guide covers for each industry: → The top 10-15 automation pain points (ranked by ROI) → Who the actual buyer is (CEO, COO, ops manager, etc.) → What they're currently paying for manual labor or broken SaaS → Realistic project pricing ($5K-$60K+ depending on scope) → The discovery questions that unlock the deal → How to position yourself as the expert even if you've never worked in that industry → Red flags to avoid (industries and company sizes that aren't worth it) 25 industries and 300+ specific automation opportunities. This is the cheat code for picking your niche and knowing exactly what to sell before you ever get on a call. What the full guide? 1. Like this post 2. Comment "NICHE" and I'll send the guide (must be connected) Bonus for the first 100 people: I'm also including an ROI calculator you can use on prospect calls. Plug in their numbers and show them exactly what they're losing to manual work every year.

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If you run a US health system on Epic, you have access to four native AI products that didn't exist 18 months ago. Here's the honest landscape as of HIMSS 2026. ART — clinician-facing AI Drafts progress notes from ambient listening, summarizes patient charts pre-visit, queues orders from visit conversation. The ambient scribe is GA but adoption is uneven — Penn Medicine, Mayo, and Riverside have published outcome data; many systems are still in pilot. Reported gains: 20-30% reduction in time on discharge summaries (Riverside), measurable reduction in after-hours EHR work. PENNY- revenue cycle AI Drafts prior auth responses, generates appeal letters for denials, suggests billing codes. Numbers Epic publishes from Summit Health: 42% reduction in medication PA submission time, 92% of AI-drafted responses accepted without edits. At systems most actively using Penny, coding-related denials are reportedly down >20%. EMMIE - patient-facing AI inside MyChart Answers patient billing and care questions, schedules appointments, suggests relevant screenings. Rush University Medical Center has published a sustained 58% reduction in billing-related customer service messages. AGENT FACTORY — the platform layer Announced at HIMSS 2026. Lets health systems build, monitor, and govern custom AI agents that span Epic workflows. The strategic shift. Until now, Epic AI was features. Agent Factory positions Epic as the agent runtime for the enterprise. What this means for digital strategy: The build-vs-buy line just moved. Two years ago, prior auth automation was a custom RPA project with vendors like Olive AI or Notable. Today, if you're an Epic shop, Penny is the default starting point for medication PA. Custom builds need to justify themselves against a baseline that didn't exist before. The integration tax dropped -but only inside Epic. Penny works because it lives in the same data plane as your charts, orders, and billing. Validation is now your responsibility, not Epic's. Epic's AI Trust and Assurance Suite ships an open-source framework for local validation, but proving Penny's outputs are accurate for YOUR payer mix, specialty mix, and documentation patterns sits with your health system. Most CIOs haven't budgeted for this. What I'd ask before assuming Epic AI is enough: → For Penny: which of our top 10 payers does PA automation cover end-to-end vs. which still require manual portal submission? → For Art: does our specialty mix (especially behavioral health, oncology, complex pediatrics) match the populations Epic's models were validated against? → For Emmie: what happens to messages it can't answer? Is that escalation path measured and SLA'd? → For Agent Factory: who in our org owns agent governance? CTO function, CMIO function, or new headcount? Want the full Epic AI feature audit template I use with health system clients? Comment AUDIT and I'll DM the spreadsheet.

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