Google and DiMe launch AI playbook for healthcare

Dime is a leader in health AI integration. Their new playbook is a fantastic resource for health care organizations looking to bring AI to their systems.

Checkout this fantastic resource created by Google for Health on step-by-step best practices on implementing AI in healthcare. What is the value of implementation research? - 80% of AI pilots fail to scale beyond the pilot phase. Pilotitis, a term commonly used in global digital health, describes the tendency to launch small-scale pilot projects without being able to scale or sustain pilots. - Up to 70% of failures stem from people and process issues, not the technology itself. - The #1 driver of clinician dissatisfaction with AI is misalignment between the tool and workflow "Workflow alignment is the linchpin of AI success. The best solutions fit seamlessly into existing practices, supporting clinicians rather than disrupting them." This practical guide includes AI readiness assessments and key steps to get an organization closer to success.

From idea to C-suite buy-in, enterprise clinical AI adoption in healthcare starts with internal champions. Clinicians, administrators, and service line leaders often bridge the gap between pilot programs and system-wide transformation. Our latest blog outlines a practical framework for these leaders to: ✅ Identify clinical and operational opportunities ✅ Build ROI-focused business cases for executives ✅ Align IT, finance, and compliance teams ✅ Drive adoption of AI tools across the health system Learn how empowered internal leaders can turn deep clinical AI from a concept into enterprise-wide impact. https://brnw.ch/21wW3kc #AIInHealthcare #ClinicalAI #EnterpriseAI #BeckersHealthcare

The Playbook: Implementing AI in Healthcare to support health systems looking to adopt and optimize AI responsibly Developed by Digital Medicine Society (DiMe) alongside Google and 30+ partners across healthcare, tech, and policy -> providing a roadmap to scale AI solutions that improve outcomes while keeping equity and trust at the center. https://lnkd.in/e8KA8Mtn

How AI Is Revolutionizing Healthcare 💊 📌 What the article is saying The article explores how AI is transforming the healthcare industry, with companies like Google and IBM leading the way. It discusses the potential of AI to revolutionize patient care and improve medical outcomes. 🔍 What’s new vs. what’s known While AI in healthcare is not a new concept, the article highlights the latest advancements and real-world applications that are pushing the boundaries of what is possible in the industry. 💡 Why this matters now The tension between leveraging AI for efficiency and ensuring patient safety and privacy is crucial now more than ever. As technology advances rapidly, healthcare leaders must navigate this balance to provide the best care possible. ⚖️ Implications by sector 1) Hospitals: AI can streamline operations, improve diagnoses, and enhance patient experiences. 2) Pharma companies: AI can accelerate drug discovery and development processes, leading to innovative treatments. 🧭 How to apply it (practical steps) 1) Invest in AI training for healthcare staff to maximize the technology's potential. 2) Implement AI-powered tools for diagnosis and treatment planning. 3) Collaborate with tech companies to develop personalized healthcare solutions. 4) Prioritize data security and privacy when integrating AI systems into medical practice. 5) Monitor patient outcomes closely to assess the impact of AI interventions. 📏 Metrics to watch • Patient outcomes improvement rate • Adoption rate of AI technologies in healthcare settings • Data security breach incidents • Cost savings achieved through AI implementation ✅ Key takeaways • Embrace AI as a tool to enhance healthcare delivery and patient care. • Ensure a balance between efficiency gains and ethical considerations in AI utilization. • Collaborate with industry partners to drive innovation and leverage AI effectively. How can we ensure that AI remains a force for good in healthcare while addressing potential ethical concerns? Exploring the implications of AI seamlessly navigating the web with minimal human intervention Source: https://lnkd.in/eY3Ze4zd #digitaltransformation #googlecloud #aigovernance

"As healthcare AI solutions grow, the question of how to implement the technology for the benefit of patients, staff, and an organization’s bottom line remains top of mind. For many healthcare systems, AI governance is the answer." https://lnkd.in/es7HWmzK

Artificial Intelligence is transforming healthcare — but success depends on more than just adopting new tools. From the MESH 2025 Innovation Bootcamp, here are some of the biggest takeaways: ✅ Build clear business cases and plan for demonstrable ROI (often within 12 months). ✅ Put robust governance structures in place to combat “solution fatigue” and ensure the right fit. ✅ Layer AI models with human oversight and continuous feedback — like the Swiss cheese model, multiple safeguards make systems stronger. ✅ Plan ahead for privacy, integration, and regulatory challenges to smooth adoption. This article by Arvind Kumar dives deeper into these insights and shows how healthcare leaders can unlock AI’s full potential for patients and providers. #AIinHealthcare #HealthTech #HealthAI

☕ Here’s to more learning, less admin — and maybe even stepping away from the screen for a real coffee break. This first AI for Clinicians series focused on small, practical prompts that make digital change feel lighter — not larger. 📰 Proud to see my take on the NHS “online hospital” featured by LinkedIn News UK 👉 https://bit.ly/3VWSnNm 🧠 And if you missed my BBC-inspired piece on when biological intelligence meets digital 👉 https://bit.ly/4nK5TQF I’m off for a short break next week ☀️ but working on Series 2, packed with more real-world AI tools for clinical life. Follow or connect to stay tuned. ⚖️ The “AI for Clinicians™” series shares educational and administrative uses of AI tools — all examples use synthetic or de-identified text, not real patient data, and are not for clinical decision-making or patient care. #AIforClinicians #DigitalHealth #MicrosoftCopilot #HealthcareInnovation #NHS #GeneralPractice #Wellbeing

5 years, 30+ products, and 8 must-have steps for AI healthcare development. My Nozomi team distilled what really works into this mind map 👇 If you want to dive deeper into all the directions shown on the map, we prepared the AI Library by Nozomi - Digital Health Product Studio, a practical resource hub where we collected: 1. Key resources for AI healthcare development that founders and PMs can actually use. 2. Proven AI features that worked best across 30+ real-world products. 3. Essential AI stack every healthtech product team should start with: • data pipelines and governance tools. • model development & fine-tuning platforms. • compliance & monitoring frameworks. • deployment and interoperability essentials. If you’re creating AI-powered healthcare products, this library will save you months of trial and error and help you scale faster. Drop a comment “AI Library” if you’d like early access to the full document. #aiinhealthcare #aihealth #aidigitalhealth

Most AI health products fail before they launch. Not because of bad data: but because they’re built for systems, not for people. This map from Max Mamoyco captures that truth beautifully. Trust isn’t a deliverable, it’s a design principle. I’d flip step 8 to step 1: think adoption before innovation. If it doesn’t move clinicians, it doesn’t move the market.