HealthCare Resolution Services, Inc.’s Post

🏛️ ‘Safe, Secure, and Trustworthy’ 👩⚕️🤖 The Biden Administration released guidance this week on artificial intelligence (#AI). So what does it mean for healthcare? Among other things, it calls for enhancing patient data privacy, strengthening regulatory oversight, eliminating bias, and accelerating R&D. Read our blog to learn more 👇

Discover how to safeguard patient privacy in clinical trials with Generative AI! Latest blog by Gramener - A Straive Company covers key regulations, impacts on Pharma and MedTech, and innovative solutions like Gramener's #AInonymize. Stay compliant and protect sensitive health data. Read now! #GenerativeAI #PatientPrivacy #DataProtection #HealthcareCompliance

When I first heard of AI being used in healthcare, I immediately thought of how risky that can be for privacy concerns. Check out this article to see how policymakers are planning to protect your data as AI continues to evolve in 2024 and forward. https://lnkd.in/eN6jzFtz

Artificial Intelligence in Healthcare and How to Comply with HIPAA & State Privacy Laws Here are some key nuggets from the podcast: 1. Podcast Name: "Counsel That Cares" 2. Special Guests: HIPAA Certification: Certified HIPAA Privacy Security Expert (CHPSE) and healthcare privacy attorneys, Beth Pitman and Shannon Hartsfield. 3. Case Study: The Dinerstein v. Google case, which seems to have been highly publicized and possibly revolves around the sharing of PHI. 4. Main Concern: The challenges and nuances of complying with HIPAA and state privacy laws when sharing PHI for research, particularly for the development of AI in healthcare. 🎙️Counsel That Cares Podcast Highlights🎙️ Hosted by Morgan Ribeiro, the episode dives deep into the Dinerstein v. Google case, discussing the sharing of public health information for AI research. 🔑 Key Takeaways: 1. Limited Data Set: HIPAA allows a specific amount of patient data to be shared for research purposes. However, this isn't completely de-identified. 2. Potential Risk: Even if data is de-identified when shared, there's concern that companies like Google, with vast amounts of data, might be able to re-identify it. 3. HIPAA Guidelines: Compliance remains crucial when health systems and tech giants collaborate. Ensuring any shared data adheres to HIPAA's regulations is paramount. 4. Re-identification Allegations: The plaintiff alleges that Google, given its massive data arsenal, might re-identify patients from the limited data set provided. 🤔 As partnerships between tech companies and health systems grow, navigating patient privacy in the digital age becomes even more challenging. The evolution of these collaborations and how they adhere to patient privacy laws is something to closely monitor. For a deeper dive, be sure to check out the full podcast episode: https://lnkd.in/gtC9YEVZ . . . #HIPAA #HealthcareTech #AI #DataPrivacy Danish Bhatti Muhammad Fareed Khan Suri Mian Muhammad Ali Akram Babar Rao MD, FAAD Waleed Choudhary Pashmeen Lakhani

While AI has proven valuable in the industry, its application in healthcare carries under-discussed risks. This widespread adoption necessitates more data, much of it sensitive and valuable patient information. This influx of data raises several significant concerns.   Read more via HIT Consultant Media: https://bit.ly/47MTQcI | #AIGuardrails #AIinHealthcare #HealthData #Interoperability

Patient data collected by health care providers, shared by patients or pulled from non-health entities like Google and Apple can be used to train clinical AI tools. But the country’s eminent health care data privacy regulation, HIPAA does not apply to non-health companies that collect health-related data. In our recent episode, we hear from AI expert and University of Michigan Law School professor Nicholson Price about why artificial intelligence could diminish health data privacy by making it easier to identify individuals and infer health information from non-health data. But stronger protections for privacy could weaken the development of clinical AI tools by making it harder to access large amounts of representative data. Learn more: https://lnkd.in/e3MyNRXb

AI's potential in #healthcare is enormous! From diagnosis to drug discovery, it's a game-changer. But with great power comes great responsibility. Discover how to strike the perfect balance between #innovation and #patientdataprivacy in our latest blog. 🔒 Learn about data security challenges, privacy concerns, and regulatory #compliance. 🛡️ Explore strategies like data encryption, access control, ethical AI, and patient consent. 🌐 Dive into the future of AI-driven healthcare with interoperability and collaboration. Check out the full article on the #Mocingbird blog - https://hubs.li/Q026WGvd0 . . #HealthcareAI #DataPrivacy #AIInnovation #EthicalAI #HealthTech #DataSecurity #PatientPrivacy #HealthcareTechnology #HealthcareSecurity

Exciting times in healthcare innovation! A recent article by TechTarget highlights the transformative potential of synthetic data in healthcare, and MDClone is right at the forefront. Our innovative approach is not only enhancing clinical research but also ensuring robust data privacy and security. It’s exciting that MDClone is leading the way in leveraging synthetic data to drive meaningful advancements in healthcare!   Check out the full article to learn more about these high-value use cases and the incredible work being done by MDClone and others in the field.  https://lnkd.in/eaeSDuCr.

Digital Personal Data Protection Act 2023 (DPDPA) has significant implications for life sciences and health care sector. Key considerations for the sector are: 1️⃣ Establish a patient centric consent process for data gathering 2️⃣ Build trust and transperancy over data processing and governance 3️⃣ Third party collobration and data governance 4️⃣ Data governance mechanism for emerging services such as telemedicine, medical tourism, use of AL, ML and AI Read more at : https://lnkd.in/gQ2gYesC

Navigating the developing healthcare regulatory landscape in 2024 is critical for industry success. Staying ahead entails adjusting to change, from stricter M&A guidelines to the integration of AI and data privacy.