Seema Pandey

💰🤖 Making the Financial Case for Generative AI in Healthcare and Life Sciences Generative AI has the potential to revolutionize the healthcare and life sciences industries, particularly when it comes to streamlining complex back-office operational workflows. Business and technology leaders can make a compelling financial case for investing in these solutions by highlighting their impact on Net Present Value (NPV) and overall efficiency. Here is how to get started: 1. 🔎 Assessing Current Workflows: Begin by evaluating existing back-office processes that have become overly complex and require significant human intervention. Identify areas where generative AI can help simplify, automate, and optimize these workflows, reducing the need for manual involvement. 2. 💵 Projecting Cost Savings: Estimate the potential cost savings from implementing generative AI solutions, including reduced labor expenses, increased productivity, and lower error rates. Be sure to consider factors like implementation costs, training, and ongoing maintenance when calculating overall savings. 3. 📊 Calculating NPV: Apply the Net Present Value (NPV) method to assess the financial viability of your proposed generative AI investments. By discounting future cash flows to their present value, NPV helps determine whether the projected financial benefits outweigh the initial investment and ongoing costs. 4. 🌟 Highlighting Long-Term Benefits: In addition to cost savings, emphasize the long-term strategic advantages of adopting generative AI for your firm. These may include increased agility, enhanced innovation capabilities, and improved competitiveness in the market. 5. 📚 Building a Compelling Case: Combine the financial analysis with a narrative that illustrates the transformative potential of generative AI for your organization. A well-crafted financial case, supported by data-driven projections and strategic insights, will help secure buy-in from key stakeholders. As always, collaborating with your technology and GSI partners can be incredibly valuable when going through business validation exercises. Your partners likely have specialized expertise, tools, and resources that can complement your own capabilities and accelerate the progress. By tapping into their knowledge and support, you can accelerate the exercise, overcome obstacles, and increase your chances of securing funding. 💬 Share your experiences and strategies for building a financial case for generative AI investments in healthcare and life sciences below! 📢 Subscribe to my newsletter to get access to strategies and practical guidance on accelerating adoption of generative AI within your organization. Get started here: https://lnkd.in/g3bdneR7 #GenerativeAI #FinancialCase #HealthcareInnovation #LifeSciences #pharmaceutical #biopharma #biotech #aws #AmazonBedrock #ChangeManagement #innovation #genai #healthcare #patientcare #ai #clinicaltrial #partnership #aiadoption #coe #ai #customersuccess

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🥂Celebrating Visionary Leaders and Encouraging Action 🚀 McKinsey estimates that Generative AI (GenAI) could generate $60B-$110B a year in economic value for pharma/medical products by boosting productivity, across drug compound identification, development & approval processes, and optimizing product marketing strategies - https://lnkd.in/efJ9Wkrx Many leading healthcare/life sciences organizations are starting to prioritize GenAI education and enablement for their teams. Over the last few week, I have had the pleasure of interacting with a few such visionary leaders who emphasized the importance of up-skilling their teams on GenAI. These leaders were happy to carve out half a day of their and their team’s time to understand GenAI, see multi-modal genAI in action, discuss GenAI hype vs reality, review GenAI adoption journey, and discuss areas where LoB and IT can start adoption exploration for their first MVP (minimal viable product). I couldn't agree more with this forward-thinking approach, and would like to share some action items to inspire leaders, across industries, to follow suit! Ask for your technology and/or GSI partners to conduct ‘Innovation w/ GenAI’ workshops with your cross-functional teams of LoB (line of business) and IT professionals on the fundamentals of GenAI and its various applications within your industry. Make sure these workshops are NOT designed as presentations or marketing services, but an interactive dialog where your teams can ask questions, see real world applications on how GenAI is being used, discuss sensitive topics, understand what a typical GenAI journey looks like, and get to understand the change management aspect of the adoption journey. Next, allow for collaboration between IT and business professionals to exchange ideas and explore GenAI-driven solutions for optimizing tasks and workflows for their most time consuming manual processes. I like to facilitate such sessions using design thinking constructs to allow for collective ideation, grouping, and voting to identify the best candidates for an MVP (minimal viable product). Important side note – I discourage POCs now because the technology has been proven and now being adopted at scale across industries. It’s time for action and accelerated adoption, so start with a MVP and iteratively develop/scale your GenAI application. Finally, provide a safe environment for experimenting with GenAI tools and techniques, allowing teams to develop solutions and evaluate their potential benefits. By setting time/scope/budgetary guardrails you can control the blast radius for safe experimentation and foster a learning culture for accelerated adoption. 💬 How are you enabling your cross-functional teams on GenAI adoption? 📢 Subscribe to my newsletter here: https://lnkd.in/g3bdneR7 #genai #ai #aws

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💡📈 Building a Strong Business Case for GenAI Investment Few Healthcare and Life Sciences organizations have begun adopting GenAI across their operations, and are already seeing tangible benefits (https://shorturl.at/fgrPZ). Initial reported use cases are focused on efficiently extracting and searching for relevant information within notes, reports, and other documents, and creating personal employee productivity tasks (https://shorturl.at/beqR1). Adoption of GenAI is particularly high in the areas of operations, research, and administrative tasks. 🙄 While GenAI adoption is surging, many use cases continue to mimic the user experience of ChatGPT. It's almost as if the industry is being constrained by the first mover, rather than exploring the full potential of these powerful AI models. Still, most firms continue to struggle to convince stakeholders to invest in GenAI. As leaders, you need to be able to showcase its potential impact on your organization and balance implementation costs against the cost of maintaining the status quo. Here are key points to consider: 1. 💰 Cost Comparison: Analyze the upfront and ongoing costs of implementing GenAI versus maintaining current processes, highlighting potential long-term savings and benefits. 2. 📊 Return on Investment (ROI): Calculate the overall financial return from implementing GenAI, considering factors like cost savings, productivity gains, and revenue increases. Use this data to justify the investment. 3. 🏆 Value-Driven Metrics: Focus on metrics that demonstrate GenAI's impact on business value, such as increased customer satisfaction, improved decision-making, and enhanced product/service quality. 4. 📲 Scalability and Flexibility: Evaluate GenAI's ability to scale alongside your business and adapt to changing needs, enabling future growth and cost savings through automation and efficiency gains. 5. 🛡 Risk Mitigation: Assess potential risks and challenges associated with GenAI implementation, such as integration issues or data privacy concerns. Develop strategies to mitigate these risks and ensure a successful rollout. Five-Step Framework for Building a GenAI Business Case: 🕵‍♀️ Identify Opportunities: Pinpoint areas that can benefit from GenAI, focusing on tasks or processes that are time-consuming, repetitive, or require creative input. 📊 Estimate Impact: Quantify the potential benefits of GenAI, using key metrics to support your estimates. 🚧 Assess Risks and Challenges: Identify potential risks and challenges and develop strategies to mitigate them. 🗺 Develop a Roadmap: Create a detailed implementation roadmap that outlines the steps required to integrate GenAI into your organization. 🔍 Monitor and Evaluate: Measure the success of your GenAI implementation using key metrics and success indicators, adjusting your strategy as needed. 💬 Share your experiences on building a business case for GenAI! 📢 Subscribe to my newsletter here: https://lnkd.in/g3bdneR7 #genai #ai #aws

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🏥🌟 Common GenAI Adoption Challenges Generative AI (GenAI) is transforming healthcare and life sciences, but adoption poses various challenges. Despite these hurdles, progress has been made, and the industry's resilience proves we can turn challenges into opportunities. With continued collaboration and commitment to responsible GenAI adoption, we can accelerate innovation and improve patient outcomes. Here's an honest and sincere look at navigating common GenAI barriers: 1. 🔎 Legal Challenges: Many enterprises are concerned about legal issues with large language model (LLM) providers using their data and prompts to train models. In most cases, this is not happening. For a detailed discussion, reach out to your technology partners. Easy to resolve through a structured deep dive session. 2.💡 Intellectual Property: Protecting IP is crucial. Companies are developing clear guidelines and collaborating with IP experts to navigate licensing, patenting, and copyright issues. Most technology partners are are offering some level of indemnification for customers using their GenAI LLMs. Important to dive into the details of protection offered. 3. 📜 Regulatory and Compliance: While complex, industry leaders are working with legal experts to ensure compliance and shape the regulatory landscape. Commitment to ethical guidelines and data privacy is key for responsible GenAI adoption. 4. 📚 Skill Gaps: Continued emphasis on upskilling and reskilling will ensure we thrive in the age of GenAI. As always, I would recommend you speak with your technology and GSI partners to understand how they can help upskill your business and technology employees. 5. 💼 Lack of Clear ROI: We've made progress in demonstrating GenAI's value through successful use cases. To strengthen the business case, let's focus on quantifying outcomes and using key metrics to monitor success - https://shorturl.at/lwBQU 6. 🐙 LLM Selection: As the industry continues to define needs and evaluate options, collaborations with AI experts and technology providers are essential for making informed LLM decisions. Refer to my earlier post on LLM KPIs to consider - https://shorturl.at/fjGTZ 7. 🛡 Fear of Reputation Damage: Prioritizing responsible GenAI use, transparency, and ethical decision-making can mitigate reputation risks. As mentioned previously, it's advisable to initially leverage GenAI for internal operational and administrative use cases. This allows you to experiment safely and build operational expertise before exploring GenAI for use cases involving your key stakeholders, both internal and external. 💬 Share your experiences and insights on navigating GenAI challenges in healthcare and life sciences in the comments below! 📢 Subscribe to my newsletter to get access to strategies and practical guidance on accelerating adoption of generative AI within your organization. Get started here: https://lnkd.in/g3bdneR7 #genai #ai #aws #HealthcareInnovation #LifeSciences

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💡 📖 Demystifying AI Decisions in Healthcare and Life Sciences: The Power of Explainable AI As healthcare and life sciences organizations increasingly adopt AI, ensuring trust and transparency in AI-driven decisions becomes crucial. Explainable AI (XAI) - a powerful approach that enables stakeholders to understand how AI models make predictions and reach conclusions. A recent research paper by Stephanie Baker and Wei Xiang (2023) explores how explainability creates trustworthy and socially responsible artificial intelligence. To learn more, access the article here: https://lnkd.in/e6TE4ADR Key benefits of XAI for healthcare and life sciences organizations include: 1. 🤝 Trust Building: XAI helps build trust in AI systems by providing visibility into the decision-making process, leading to increased confidence among patients, clinicians, and regulators. 2. 😇 Ethical AI Adoption: By ensuring AI decisions are explainable, XAI facilitates ethical AI usage, minimizing unintended consequences and potential biases. 3. ⚖ Regulatory Compliance: XAI enables organizations to demonstrate compliance with evolving regulations and guidelines, such as GDPR and FDA recommendations, which emphasize transparency and interpretability. Implementing XAI requires collaboration between data scientists, clinicians, and regulatory experts to develop interpretable models and user-friendly explanations. As generative AI becomes more mainstream within healthcare and life sciences organizations, business and technology leaders would benefit by analyzing which LLMs (prompts, design patterns, and platforms) assist with XAI, and if the outcomes of their applications aligns with their corporate Responsible AI policy. As always, learn by doing - talk to your technology and strategy partners to work with you on a POC (proof of concept) that aims to prove XAI that aligns with your responsible AI policy. 💬 Share your strategies for integrating XAI and promoting transparency in AI-driven healthcare and life sciences solutions below! #ExplainableAI #XAI #Healthcare #LifeSciences #Trust #Transparency #EthicalAI #GenerativeAI #HealthcareInnovation #pharmaceutical #biopharma #biotech #aws #AmazonBedrock #ChangeManagement #innovation #genai #lifesciences #patientcare #ai #clinicalresearch #clinicaltrial #partnership #aiadoption #coe #ai #customersuccess 📢 Subscribe to my newsletter to get access to strategies and practical guidance on accelerating adoption of generative AI within your organization. Get started here: https://lnkd.in/g3bdneR7

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A Christmas Miracle: A Data disaster averted by Arun Divakaran A real-life story of a major Data migration problem crashing a Healthcare company's Production systems, amidst their new Healthcare Portal Launch. The true story underlines how gaps in Leadership, and the ineffective adoption of Risk management & Project management processes can rapidly lead to disaster. https://lnkd.in/ggxGSRJW #Agile #ProjectManagement #CrisisProjects #RiskManagement

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In the ever-evolving healthcare landscape, digital transformation is more than just integrating new technologies. It's about strategically navigating the complexities of hospital processes and empowering human stakeholders. Our latest article, penned by Dr. Gaurav J. Kumar, Medical Director, Dedalus delves into the critical themes and challenges of digital transformation in hospitals. Discover how strategic planning can turn IT investments into tangible returns and revolutionize patient care. 🔗 https://lnkd.in/gHHRQS8T #DigitalTransformation #HealthcareInnovation #HospitalManagement #ITInvestments #PatientCare #TechInHealthcare #HospitalTech #StrategicPlanning #healthcareindustry #europeanhhm #EHHM

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AI Doctors are Coming AI-powered CarePods are revolutionizing the industry with cutting-edge precision and efficiency. Here's how: ① Accurate Diagnostics → Reduces human error for precise results. ② Personalized Health Plans → Tailored solutions for optimal outcomes. ③ Continuous Monitoring → Tracks health in real-time for proactive care. ④ Secure Data Transmission → Ensures patient privacy with robust encryption. ⑤ Scalable Deployment → Accessible to more people, democratizing quality care. Why is AI the future of healthcare? ☑ Provides consistent care ☑ Reduces wait times ☑ Frees up human doctors for complex cases ☑ Enhances patient experience and care Optimal health comes from continuous monitoring Would you use one? #healthcare #ai #aistrategy

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Finding the right vein is a struggle And patients getting poked around for the same is stressful. To find the vein is like playing hide-and-seek sometimes which is not at all fun. However, that struggle could be solved soon with this innovation. This see-through vein technology lets doctors find the vein in a go. No more guessing games, just smooth and right IV placement every time. Isn't that amazing? What do you think? Seth Rainford, MBA Charlie Mamrak Manish Ahuja #MedicalInnovation #HealthTech #Healthcare #PowerofTech #Tech #FutureOfHealthcare

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Check out Monica Weekes' blog about our recent Executive Forum and the topic of payer-provider convergence.

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HSBlox, Inc's CEO (Rahul Sharma) discusses the importance of data digitization for successful implementations of Value-Based Programs. For healthcare organizations to fully realize the cost savings and quality improvement goals of #VBC, they must be able to do the following:  • Utilize a data-driven digital infrastructure that supports a multi-stakeholder "network of networks," which includes different payment capabilities.  • Attain data interoperability to facilitate permissioned data-sharing.  • Build longitudinal healthcare records that patients can supplement with their personal data.  • Draw insights from patient data and external data sets to guide clinical decision-making.  • Create user-friendly, data driven workflows for various healthcare stakeholders. #vbc, #vbaforvbc, #vba , #valuebasedcare, #alternativepayments, #wholepersoncare, #contractbuilder, #valuebasedinfrastructure, #dataengineering, #datascience, #interoperability, #fhir , #hl7 , #edi , #unstructureddata Lynn Carroll, Deepti Sharma ,CPC CMHP, Mohan Badkundri, Karthik Kanakaraj, Kimberly Shepard, Eric D. Young, John Layne, Carl King, Amol Bapat, MD, FACC, Michael Roach https://lnkd.in/gejMbd9A

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HSBlox, Inc's CEO (Rahul Sharma) discusses the importance of data digitization for successful implementations of Value-Based Programs. For healthcare organizations to fully realize the cost savings and quality improvement goals of #VBC, they must be able to do the following:  • Utilize a data-driven digital infrastructure that supports a multi-stakeholder "network of networks," which includes different payment capabilities.  • Attain data interoperability to facilitate permissioned data-sharing.  • Build longitudinal healthcare records that patients can supplement with their personal data.  • Draw insights from patient data and external data sets to guide clinical decision-making.  • Create user-friendly, data driven workflows for various healthcare stakeholders. #vbc, #vbaforvbc, #vba , #valuebasedcare, #alternativepayments, #wholepersoncare, #contractbuilder, #valuebasedinfrastructure, #dataengineering, #datascience, #interoperability, #fhir , #hl7 , #edi , #unstructureddata Rahul Sharma, Lynn Carroll, Deepti Sharma ,CPC CMHP, Mohan Badkundri, Karthik Kanakaraj, Kimberly Shepard, Eric D. Young, John Layne, Carl King, Amol Bapat, MD, FACC, Michael Roach https://lnkd.in/gejMbd9A

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Compute plays a central role in India's AI mission with a significant allocation of funding dedicated to building compute capacity. Viewed as a technology stack encompassing hardware, software, and infrastructure layers, compute is a key component in driving innovation and progress. India's national compute strategy focuses on optimizing and maximizing the country's compute capacity through collaboration with the private sector. Policymakers are advised to articulate clear objectives, gather reliable data, and study global models to ensure an informed and effective compute strategy for India's future. #AI #Compute #Technology #India #NationalStrategy #Innovation #Collaboration https://lnkd.in/gCuAm6y5

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Discover how healthcare payers can harness data-driven insights to promote health equity. Alok Mandal, Vice President of Technology, SBU leadership, provides insights on how technology enablers can provide excellent healthcare at low costs. Read here: https://splr.io/6049YBXt1 #HealthEquity #DataDrivenHealthcare #EngineeringFirst

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AI chatbots within the healthcare industry commonly employ natural language processing (NLP) algorithms to grasp and respond to patient inquiries in a conversational manner. Through the utilization of NLP, these chatbots can analyze and interpret text inputs from patients, offering personalized health advice and guidance based on their individual needs and concerns. This strategy not only reduces the workload of healthcare professionals but also enhances patient engagement by providing relevant and timely assistance. #NLP #HealthTech #AIChatbots #PatientCare #HealthcareInnovation #PatientEngagement.

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I caught up with Nikhil Krishnan of Out-Of-Pocket fame to get his take on the current state of the healthcare technology landscape. Up first: his current thoughts on what's exciting and where there are opportunities for AI-driven solutions. First half of our Q&A below 👇 — 🟩 Q: When it comes to AI, what area are you most excited about? Patient-facing solutions. The AI admin and back-office space has quickly become saturated, and incumbents will always have a distribution advantage here. Which is why I’m actually surprised there aren’t more players entering the patient-facing side. I think the traditional healthcare companies are too nervous to actually go into that patient-facing area. And it's also a regulatory gray area, so if you actually get traction, you can probably help shape how this stuff ultimately gets regulated. So right now, I think the greatest opportunities are for patient-facing AI tools. 🟩 Q: Where specifically do you see whitespace to develop patient-facing solutions? I think there’s still a lot of opportunity on the patient-facing automation side. A great example actually is automated lab results. There has been an issue for the last 3 years that lab results automatically get released to patients, and they see something's abnormal. The patient is trying to figure out what’s going on and what they've read. Part of this is explaining the result, which is something Elaborate is working on, and in some cases, actually, it's really useful for the patient to get that notice immediately with follow up steps, like scheduling a diagnostic. Another area is AI that can autonomously make workflow changes within a local system. Viz.ai is working on this automated workflow piece in the context of situations like stroke care coordination and hypertrophic cardiomyopathy. This requires not only automation in terms of being able to understand the context of multiple datasets, but also make the requisite workflow changes (e.g. escalating to the right specialist). These are particularly useful in time-sensitive areas. 🟩 Q: Any other AI whitespaces? Monitoring of AI models. It's one of the areas that's still unknown in terms of how do you give peace of mind to your buyer? It becomes really hard to actually evaluate and audit a lot of these AI algorithms without some form of data exhaust. I feel like one of the things that will happen is you'll see some form of certifying entity emerge that can give a gold standard to hospitals. 🟩 Q: What else are you thinking about as it pertains to AI? I do think that pricing is one of the more interesting components here. For example, in AI scribing, how you think about pricing changes a lot depending on if you’ve got a human in the loop or not. Because adding a human layer goes from near zero marginal cost to cost scaling linearly. One of the ways that companies will be able to differentiate themselves — especially from incumbents — is the pricing model.

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What’s new when it comes to AI in healthcare? According to Dr. Ashish Atreja, MD, MPH, there's a very important factor: “Here, at least in my 25 years of informatics IT career, this is the first time there is a pull. People are saying ‘We need this. We need this.’ It’s just amazing to see that, especially from clinicians.” In case you missed it, get real-world insights on AI use cases in healthcare from our panel discussion with Lisa Stump, SVP & Chief Information and Digital Transformation Officer at Yale New Haven Health, and Dr. Ashish Atreja, MD, MPH, Chief Information and Digital Health Officer at UC Davis Health: https://bit.ly/3UEfOLw

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Healthcare is brimming with innovation, but many struggle to translate potential into real change. Read the article by John Squeo, SVP, Head of Provider and Healthcare Services, CitiusTech, to know about the challenges and strategies for scaling healthcare innovation. Read here : https://lnkd.in/giA_SwAT #CitiusTech #HealthcareLimitless #HealthcareTechnology #USHealthcare

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