How to Utilize Technology in Healthcare

Many healthcare organizations are trying to optimize their workflows without a clear strategy, and that’s where things can go wrong. While serving as the US Navy's chief medical informatics officer (CMIO), I learned important lessons about workflow optimization, strategy, and technology integration. Here’s the truth: Healthcare workflows are intricate and multifaceted. Without the right approach, there’s a risk of: ⏳ Wasting valuable time on redundant tasks 💸 Incurring unnecessary costs 😟 Compromising patient experiences But it doesn’t have to be this way. 🔍 Here’s what you need to know to streamline and optimize your healthcare workflows with AI: 1️⃣ Identify Bottlenecks. First, not all workflow issues are created equally. Some are more critical than others. → Start by pinpointing the areas where inefficiencies are costing you the most. 2️⃣ Leverage AI for Automation. AI can handle routine tasks like appointment scheduling and data entry. → Free up your staff to focus on patient care and complex decision-making. 3️⃣ Enhance Decision-Making with AI. Insights AI can quickly analyze vast amounts of data, offering insights that improve patient outcomes. → Use AI to support clinical decisions and personalize treatment plans. 4️⃣ Improve Communication Channels. AI-driven tools can streamline communication between departments and with patients. → Ensure everyone is on the same page, reducing errors and enhancing patient satisfaction. 5️⃣ Monitor and Adjust Regularly. AI is powerful, but it is not set and forgotten. Continuous monitoring and adjustments are key. → Regularly review your workflows and tweak AI tools for ongoing optimization. Healthcare is challenging enough. Don’t let outdated workflows add to the stress. With a strategic approach, AI can transform your healthcare operations, making them more efficient, cost-effective, and patient-centered. 👉 Are you ready to explore how AI can elevate your healthcare workflows? Let’s discuss the possibilities.

A healthcare company was struggling with low patient compliance and poor communication between providers and patients—leading to suboptimal outcomes and regulatory concerns. How wearable tech is changing remote care: By integrating wearable devices into their Remote Patient Monitoring (RPM) programs, they enabled continuous, real-time collection of patient data—such as heart rate, blood pressure, and glucose levels—directly from patients’ homes. This data was securely transmitted to healthcare professionals, allowing for timely interventions and personalized care plans. Results: - Improved patient compliance with treatment and monitoring plans through reminders and real-time feedback - Reduced hospital readmissions and in-person visits due to early detection and proactive management - Enhanced patient engagement and satisfaction by empowering individuals to take a more active role in their health Real change happens when technology meets strategy. Would this solution work for your organization? #AIinHealthcare #HealthTech #DigitalHealth

Are you looking for best practices in the adoption of AI for healthcare? Get six tips from Kiran Mysore, the chief data and analytics officer at Sutter Health. ·     You should not think about technology first and the allure of AI. You need to lead with the business problem or the clinical care problem you are trying to solve with AI. In some cases, the answer to the problem may not be AI. ·     In cases where AI is a solution to a problem, you need to be very specific about the outcome you want to drive with AI. You must focus on integrating AI into clinical workflows, measuring the outcomes over time, and understanding the improvements you are making against a baseline. ·     AI is very complex. It is rarely a turn-key solution, where you adopt a model and expect it to work. It needs a lot of good, clean data. It needs a lot of talented and skilled professionals to make it work the right way. It needs to be trusted and dependable, which means you must tune the models well so they can function at the highest level. ·     You should try to think about scale on Day 1. Don't wait until a pilot is done, then think about the next step because scaling takes a long time. If you don't think about scale and performance on Day 1, you lose momentum. ·     Utilize best practices across the board. Talk with other healthcare organizations that have adopted AI models to learn from them, so you can capitalize on opportunities and avoid making mistakes. ·     The biggest pitfall is being too optimistic about AI. We are in the early days of AI initiatives. It is rarely going to work exactly as advertised because every health system is unique. You must think about taking an AI capability and challenging the capability. The pitfall is thinking that AI is a silver bullet and it will work for everyone. Read the full HealthLeaders story at https://lnkd.in/dcxMSZSx

𝗜 ❤️ 𝗔𝗜 𝘀𝗰𝗿𝗶𝗯𝗲𝘀, 𝗕𝗨𝗧… This article got me thinking about the people and process changes necessary to fully leverage this tech. Here are 2 key examples: 𝟭. 𝗖𝗵𝗮𝗻𝗴𝗶𝗻𝗴 𝘁𝗵𝗲 “𝗣𝗲𝗼𝗽𝗹𝗲” 𝗔𝗽𝗽𝗿𝗼𝗮𝗰𝗵 Start every encounter by stating: "I'm recording this conversation, and an artificial intelligence system will summarize our discussion. Do you have any questions?" Why? Being upfront about AI use avoids awkward (and potentially heated) conversations as patients become more aware of the tech and encounter hyped-up AI horror stories on the internet. Yes, this takes a bit of time upfront, but skipping it can have significant costs in trust later. 𝗣𝗼𝘁𝗲𝗻𝘁𝗶𝗮𝗹 𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀: 👉 Have an information pamphlet ready for patients with details about AI privacy and accuracy. 👉 Send a message to patients before their appointment explaining the use of AI during their visit. 𝟮. 𝗖𝗵𝗮𝗻𝗴𝗶𝗻𝗴 𝘁𝗵𝗲 “𝗣𝗿𝗼𝗰𝗲𝘀𝘀” 𝗔𝗽𝗽𝗿𝗼𝗮𝗰𝗵 Every encounter should include a quick review of the AI-generated note immediately after the conversation. Why? A quick review following the encounter prevents introducing convincing but incorrect information into medical records. AI can generate subtle, plausible-sounding errors that are easy to miss – especially if editing happens hours later. 𝗣𝗼𝘁𝗲𝗻𝘁𝗶𝗮𝗹 𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀: 👉 Build time buffers into schedules for quick AI note reviews. A portion of the time saved by using AI can be reinvested here. 👉 Provide training to clinicians on how to spot common AI errors or hallucinations. 𝗧𝗵𝗲 𝗕𝗼𝘁𝘁𝗼𝗺 𝗟𝗶𝗻𝗲 Again, I ❤️ this use of AI – it has incredible potential to improve outcomes for both patients and healthcare professionals. 🔑 The key to unlocking this potential is proactive leadership rethinking old ways of working and embedding AI so that it supports clinicians, builds trust, and improves patient outcomes. As always: 𝗟𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽 𝗙𝗶𝗿𝘀𝘁, 𝗧𝗲𝗰𝗵 𝗟𝗮𝘀𝘁! 💪 __________________________________________ (Source in the comments.)

Key strategies for making AI work in healthcare: 💡 Think of AI as a brilliant analyst, not the boss. Use AI's insights to enhance technical solutions - but always filter through clinical expertise. 💡 Context is king. When deploying AI for clinical workflows, success comes from understanding provider workflows, not just efficiency metrics. 💡 Build a culture of healthy skepticism. Teams should challenge AI recommendations. The best innovations emerge from this dialogue. 💡 Keep the human element central. Technology should enhance, not replace, empathy in healthcare delivery. 💡 Use AI strategically. Leverage it for predictive analytics and workflow optimization, while keeping critical patient care decisions in human hands. #HealthcareLeadership #AIinHealthcare #DigitalTransformation #HealthTech #FutureofHealthcare #WisdomAtWork #healthcareonlinkedin

Integrating #AI into #Healthcare: A Smarter Approach Inspired by Covey’s 7 Habits AI is transforming healthcare—but successful integration requires a strategic mindset. Stephen R. Covey’s 7 Habits of Highly Effective People provides a powerful framework to guide this process: 🔹 Be Proactive – Stay ahead by exploring AI solutions that enhance patient care and streamline operations. Proactively identify where AI can make a real difference. 🔹 Begin with the End in Mind – Set clear goals for AI integration. Are you aiming for better patient outcomes, increased efficiency, or enhanced diagnostics? A well-defined vision ensures AI aligns with your organization’s mission. 🔹 Put First Things First – Prioritize AI projects with the highest impact. Predictive analytics, AI-assisted imaging, and workflow automation should take precedence over nice-to-have innovations. 🔹 Think Win-Win – Collaboration is key. Engage healthcare professionals, AI developers, and stakeholders to create solutions that benefit everyone—patients, providers, and institutions alike. 🔹 Seek First to Understand, Then to Be Understood – Listen to frontline healthcare staff. Understand their challenges and workflows before introducing AI, ensuring seamless adoption and real value. 🔹 Synergize – AI is not a replacement; it’s an enhancement. When integrated into multidisciplinary teams, AI amplifies decision-making, improves outcomes, and drives innovation. 🔹 Sharpen the Saw – Commit to continuous learning. Stay updated on AI advancements, train healthcare professionals, and regularly refine implementations to maximize impact. By applying these habits, healthcare organizations can navigate AI integration effectively—leading to better patient care, increased efficiency, and a culture of innovation. 💡 Which of these habits do you think is most critical for AI in healthcare? Let’s discuss in the comments!

HealthTech founders can learn a lot from NASA’s recent challenges with the Starliner spacecraft. The challenges in question were setbacks due to technical issues, forcing delays in their mission and raising concerns about safety. I was reading about this and realised health-tech isn’t too different in this context. In aerospace, the sakes are high. Product failure can have huge consequences - in some rare cases, people even lose their lives. HealthTech is the same. So we can learn by studying how NASA handled this situation: ▶ 1. Include multiple layers of safety Just like NASA uses backup systems to keep missions safe, we need to add extra layers of failsafes to our HealthTech products. This means designing devices that don’t compromise the patient even if one part fails. For example - adding extra sensors to a patient monitor to ensure its reliability and safety. ▶ 2. Prioritise simulations and early testing After failing the test run, NASA delayed their mission to work on further tests - and only launched with maximum surety. We too, need to test our products in real world conditions to catch problems. This way, we can fix issues before they affect any patients. ▶ 3. Use failures as a chance to get better NASA’s setbacks with Starliner teach us to see failures as chances to learn and improve. Analyzing what went wrong in our projects, allows us to make our products better and deliver more reliable solutions. By applying these lessons, we can ensure that our HealthTech solutions aren’t just innovative but also safe and reliable. And that helps us maximise our positive impact. #nasa #healthtech #healthcare

Physicians spend up to 6 hours a day logging notes into their EHR. No wonder many physicians spend little time with their patients, and complain of burnout. And, unfortunately this unsustainable trend is only worsening as documentation becomes more rigorous due to increased compliance/liability requirements. THIS is the type of healthcare problem that "Big Tech" is well suited to solve. Fortunately, they agree. Amazon Web Services (AWS) recently announced the launch of HealthScribe. It's a tool that "allows providers to build clinical applications that use speech recognition and generative AI to create transcripts of patient visits, identify key details and create summaries that can be entered into an electronic health record". It's initially being piloted with General Medicine and Orthopedics, but likely to be expanded to broader specialties based on customer feedback. Microsoft & Google also have developed similar products to address the glaring issue. Documentation is just one small piece to a much larger puzzle. But you have to eat the elephant one bite at a time. Decreasing administrative burden on physicians has a trickle down effect on healthcare economics. More patients seen = higher revenues. But the clinical benefits also cannot be ignored. More time in front of patients, and less time in front of a computer screen will undoubtedly have a positive impact on the quality of care. As is always the case, execution of the product will be key to benefit realization. But it's a start. And we must start somewhere. #digitalhealth #EMR #EHR #medtech #medicaldevice #medicaldevices #healthcare #medicine #physician #healthtech