Quick Pulses of Full Conversation: Tachyons, Soundbites, Takeaways..
AI's Impact on Healthcare Jobs and Workflows
no i think it's going to be a huge impact um and i we've been watching it for a while especially because i'm an interoperability you know and i'm smack in the middle of every type of workflow there is within healthcare that's involving tech because everyone wants to connect to another system so i've been in the middle of these conversations for the past 11 years and we're definitely watching that happen um i you know It's a hard balance, right? You don't want to put everybody out or a lot of people out of a job. However, one of the benefits is, is that you can automate some very manual tasks for individuals. You can start utilizing the brilliant people you have on staff to actually do some like higher level work and more engaging work that could probably do a lot better for the organization. So there is a catch 22 of it is benefit of it. But there's been organizations worrying about this for some time.
The Role of AI in Healthcare Interoperability
yeah i i think obviously ai has a huge promise uh in healthcare tech obviously it's all the rage right now but i think it also has its place for interoperability as well you know a lot of interoperability historically is a lot of manual work right like these v2 interfaces having to map everything takes a lot of time um and resources uh whether it's in-house or outsource and so it becomes a lot of cumbersome manual work and that's a lot of money spent um for these companies that are tech enabled services if you will so ai really is beneficial uh previously i was at an org where i called it the boring ai where they took it very they just took all the various sources of information coming in and structured it into one type of proprietary format um so it was hugely beneficial because Healthcare data, whether it's HL7, CCDA, and all these other formats, we kind of follow an 80-20 rule where 80% of it is structured because here's what we've deemed and 20% is whatever you feel like. And when you try to do reporting and analytics and all these other things off of it, it's messy. You're losing data and everything else. And so there's this 20% that's just a lot of manual work that has to go into it. So the boring AI aspect was super beneficial in that and helping structure it and getting that into it. Where generative AI, I think, can really come into play is, you know, we were at Health.
Caution Against 'Snake Oil' in Healthcare AI
And if that changes the diagnosis and it was found to be hallucinating or something else like that, you wanna make sure you have all your ducks in a row. And sometimes these groups from outside of healthcare that are walking in promising to transform it, that don't understand it, there may be some lack of best practices coming into it that may affect the patient life. So that's where the caution comes from. And I've met a lot of the snake oil people, the vaporware people over the years, and you can spot them, but their pitch is so good.
Emergence of Sustainability Directors in Healthcare
I'm really interested to see where we go with that because that is going to factor into a lot of decisions of whether it's that brick and mortar location where their data centers are located and how they're doing certain things and how do they minimize their costs. So if your spend with AWS is so much because of certain aspects of it, there are better ways to store your data. There's better ways to have your data done a certain way, in essence, taking up less energy. And so all that I believe will factor into how we see it. So I think we will see some, I don't know if we'll get to a chief energy officer at a hospital one day or something like that, but I think that will factor into some type of spend at a health system or in other organizations. I think that will absolutely be part of it. You know, I'm glad you brought that up. In fact, we're in discussion to do more sustainability, and there are about 45 titled sustainability directors at health systems hospitals. So we hope to be doing some more of that. That's awesome. And so I would imagine, so what is that job title? You know, it's like this chief AI officer is sort of like with the, like you said, the energy officer or whether it be sustainability.
Admiring a Charismatic Leader at B.Well
But that's why it's so strong. And so every time I'm in a room with her, I'm like starstruck because of how engaging she is. She really knows the business. I jokingly say she's the quintessential. She could sell a snow cone to a snowman in the Arctic and a hundred percent. They needed it because she's just so charismatic, but because the power and the experience that she has, And she obviously wouldn't do it unless the snowman actually needed it. But in the same respects, like it's just an amazing personality to be there with. And so super happy to be like learning from her on that front. Yeah. Well, that's an awesome story. And I know she's really excited to have you because you're, you know, like I said, you know, in our in the green room, it's just solid. It was it's great to meet you at health and just, you know, you're you're a solid person.
Empathy for Californians Affected by Fires
for others who are listening, be kind to those in California right now. I'm in Southern California. You know, my While I luckily haven't been affected directly by the fire because I'm just a few miles south of it, a lot of my childhood that I watched got burned down. And so kindness to those in California, regardless of your political beliefs or anything, because we see a lot of that on social media right now.
Additional References & Resources
Due Diligence Checklist for Implementing Agentic AI in Healthcare
This checklist outlines key considerations for implementing Agentic AI in healthcare to ensure safe, effective, and ethical integration.
I. Governance & Oversight
Establish Clear Permissions & Access Protocols:
Define roles and responsibilities for AI development, deployment, and maintenance.
Implement robust authentication and authorization mechanisms (e.g., multi-factor authentication, role-based access control).
#AIgovernance #cybersecurity
Define Human-in-the-Loop Decision-Making Boundaries:
Clearly outline scenarios requiring human oversight (e.g., critical diagnoses, complex treatments).
Establish clear escalation paths for AI-generated recommendations.
#clinicaldecisionsupport #humaninloop
Create Transparent Accountability Frameworks:
Define clear lines of responsibility for AI system outcomes.
Establish mechanisms for identifying and addressing errors or biases.
#AIethics #accountability
Regular Reporting & Auditing:
Implement regular audits to assess compliance with policies and identify potential issues.
Track key performance indicators (KPIs) and generate regular reports.
#auditing #performancemonitoring
II. Technical Integrity
Validate AI Training Data Comprehensively:
Ensure data is diverse, representative, and free from bias.
Implement rigorous data quality checks and validation processes.
#dataquality #biasmitigation
Implement Continuous Performance Monitoring:
Continuously monitor AI system performance in real-world settings.
Track key metrics and trigger alerts for performance degradation.
#modelperformance #monitoring
Develop Robust Bias Detection & Mitigation Strategies:
Proactively identify and address biases in algorithms and data.
Implement bias mitigation techniques (e.g., fairness constraints, adversarial training).
#fairness #AIbias
Regular System Updates & Maintenance:
Establish a process for regular system updates and maintenance to address bugs, vulnerabilities, and performance issues.
#softwaremaintenance #updates
III. Safety & Ethics
Ensure Patient Privacy & Informed Consent:
Implement robust data privacy and security measures (e.g., encryption, de-identification).
Obtain informed consent from patients before using their data for AI training or treatment.
#HIPAA #GDPR #patientprivacy
Create Clear Escalation Protocols for Uncertain Scenarios:
Develop clear guidelines for handling situations where AI systems encounter uncertainty.
Establish escalation pathways to human clinicians for expert review.
#safety #uncertainty
Maintain Comprehensive Audit Trails of AI Interactions:
Log all AI system interactions, including inputs, outputs, and decision-making processes.
#transparency #traceability
Ethical Considerations in AI Development:
Integrate ethical considerations into all stages of AI development, from data collection to deployment.
#AIethics #responsibleAI
IV. Regulatory Compliance
Align with HIPAA, GDPR, and Other Healthcare Regulations:
Ensure compliance with all relevant healthcare regulations and data privacy laws.
#healthcarecompliance #regulations
Conduct Regular Ethical and Technical Reviews:
Establish a process for regular ethical and technical reviews of AI systems by independent experts.
#ethicsreview #technicalreview
Prioritize Patient Safety and Data Protection:
Make patient safety and data protection the top priorities in all AI development and deployment decisions.
#patientsafety #dataprivacy
Stay Updated on Regulatory Changes:
Continuously monitor and adapt to changes in healthcare regulations and standards.
#regulatoryupdates #compliance
By addressing these aspects, Agentic AI can enable healthcare systems to work cohesively, reduce inefficiencies, improve patient outcomes, and foster innovation across the healthcare ecosystem.
Note: This checklist provides a general framework. Specific requirements and considerations may vary depending on the type of Agentic AI system, the specific healthcare application, and the applicable regulatory landscape.
Disclaimer: This information is for general knowledge and informational purposes only and does not constitute medical advice.
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