J P Systems, Inc.’s Post

The Healthcare sector is experiencing a change in thinking with the advent of Healthcare 5.0, bringing forth improved patient care and system efficiency. However, this transformation poses significant challenges. The growing digitization of healthcare systems raises concerns about the security and privacy of patient data, making seamless data sharing and collaboration increasingly complex tasks. Additionally, as the volume of healthcare data expands exponentially, efficient handling and analysis become vital for optimizing healthcare delivery and patient outcomes. Addressing these multifaceted issues is crucial for healthcare professionals, IT experts, data scientists, and researchers seeking to fully harness the potential of Healthcare 5.0. https://lnkd.in/dZuNh_4q

Weighing the pros and cons of synthetic healthcare data use Synthetic data is touted as a privacy-preserving alternative to the use of real-world patient information in healthcare analytics. Also, synthetic data mimics real-world patient information without compromising privacy. It's increasingly used in healthcare to improve research, AI model training, and policy analysis, while avoiding issues like data leakage and re-identification. However, challenges remain with data quality, bias, and model validation. As the technology advances, synthetic data holds great promise for healthcare innovation, provided these challenges are addressed.

For healthcare technology folks! The paper (below) showcases how artificial intelligence governance will be shaped going forward. We all know governance model adopted by organizations influences every professional within the org. Link: https://lnkd.in/g-GiXRpr

Healthcare IT Today reached out to Janus Chief Product Officer John Garcia recently to discuss how innovative technologies and data analytics can increase efficiency in healthcare operations. "By leveraging innovative technologies such as predictive modeling, machine learning, and artificial intelligence, payers can sift through vast amounts of data to identify patterns, detect fraudulent activities, and forecast trends in healthcare," John said. Read the full article here: https://lnkd.in/eW6-3Avp

On behalf of IBM healthcare in 2008, I wrote an article for CHIME on data and information sharing and that all systems generally move toward openness. This potentially heretical [at the time] concept was also shared at two healthcare executive roundtables, yet, in 2024 - the well-written article attached from DHI concludes with ... "the future of healthcare lies in connecting the dots, one data point at a time." Sixteen years later, how can this be? Yes, healthcare is complex and healthcare IT in the US has been allowed to become more complex instead of 'more connected.' Yet worldwide finance operates in milliseconds across global boundaries and expectations that far exceed our healthcare laws, privacy and data "standards." The technology must exist! And, in fact, it does and has for twenty years. IBM's DiscoveryLink solution 'connected the dots' between researchers with common interests and solutions. HIMSS' Connectathons and interoperability showcase continue to test and integrate disparate technology systems from around the world. As we step back and reframe the problem.... [Houston] we have a social [human] problem! Technology is not preventing patients [me] from full integration of my data and information - leading to insights and innovation and a cure for my degenerative and progressive, chronic, neurological and incurable [at this time] disease. We have a people problem, not [solely] a technology problem. Boundaries, silos, rules, egos, stock prices, organizational cultures. Why can't we all just get along? Patient Centered, patient engagement is marketing 101. Ask the client! It's my data.....

Delivering healthcare through new technologies faces several challenges: 1. Data Privacy and Security: Ensuring the confidentiality, integrity, and availability of patient data is paramount. Healthcare data is a prime target for cyberattacks, and any breach can have severe consequences. 2. Integration with Existing Systems: New technologies must seamlessly integrate with existing healthcare systems and electronic health records (EHRs). This can be technically complex and costly. 3. Regulatory Compliance: Navigating the regulatory landscape for medical devices and health IT can be challenging. Different regions have varying requirements, making compliance a significant hurdle. 4. User Adoption and Training: Healthcare professionals and patients need to adopt and effectively use new technologies. This requires adequate training and support, and overcoming resistance to change. 5. Interoperability: Ensuring that different technologies and devices can communicate and work together is crucial. Lack of interoperability can lead to fragmented care and data silos. As well, accuracy and precision must be endured when dealing with medical data used in decision making. 6. Access and Equity: Ensuring equitable access to new technologies is crucial. There is a risk that disparities in access could exacerbate existing health inequities. Further, the use of AI and other advanced technologies raises ethical questions around decision-making, patient consent, and the potential for bias in algorithms. 7. Patient Engagement: Engaging patients in the use of new technologies and ensuring they are comfortable and willing to use them is essential for their success. Families are bombarded by differing technical platforms and ensuring patient engagement has never been more difficult. Addressing these challenges requires a multi-faceted approach involving stakeholders from across the healthcare ecosystem.

It's clear that while AI remains a focal point, the critical backbone supporting its efficacy is robust data management. The upcoming HIMSS conference is expected to echo this. For healthcare leaders, the priority is leveraging data not just to enhance clinical care but also as a cornerstone for value extraction and strategy development. However, the increasing volume of data available to hospitals, health systems, payers, and other stakeholders introduces complex challenges in data analysis, storage, and security, alongside efficient distribution among providers. As the industry navigates these waters, the conversation around data management strategies and technological innovations becomes more crucial than ever. Let's engage in this dialogue and work towards empowering healthcare with effective data utilization. Read more: https://lnkd.in/eyndB-xu #HealthcareInnovation #DataManagement #AIinHealthcare

Lets talk about Data and Healthcare: While I often share insights about the innovative large-scale applications we're creating, it's crucial to shine a light on the less glamorous yet equally important aspect of our work: the intricate data pipeline and infrastructure. This is the essential "keep the lights on" work that underpins everything we do. Healthcare data is notoriously complex and messy. Let’s take a simple example like a patient's "Race." In Electronic Health Records, this appears as a discrete field. However, the accuracy of this data is often questionable, evident when contrasting the legally documented physician’s notes with the EHR's discrete fields. Correcting these discrepancies isn't straightforward in healthcare. Even with knowledge of inaccuracies, we can't amend them without patient involvement. So much of the reliable healthcare data can only be found in the non-formatted textual note of a physician. Reflect on the far-reaching consequences of this challenge. This is the reason many healthcare professionals raise concerns about AI and machine learning in the space. The integrity of the training dataset is crucial; if not thoroughly vetted and cleansed, it can introduce significant biases and inaccuracies, undermining the reliability of the AI. I was recently discussing healthcare data issues with another colleague, Ben Doremus, centered around variable definitions in healthcare data. Take "re-admission" as an example. This term's definition varies across, and sometimes within, institutions. Or consider the request to "pull all new patients." The interpretation of "new" can differ significantly, especially in a multi-hospital setup. Is it new to a specific hospital, or new to the entire system? Not everyone will define these things the same. There are often definitions as defined by government agencies and reporting groups, but these are often not accepted amongst the actual clinical staff outside of reporting to said agencies. These nuances make building actual reports clinical staff will use and reports that are required by state and federal agencies a challenging task. Despite these challenges, our team has established procedures to manage these complexities internally. We've automated over 20 daily, monthly, and quarterly reports to streamline clinical operations. This is a testament to our team’s commitment to not just innovation in large-scale application development, but also in ensuring the smooth running of day-to-day clinical activities. So, while I don't often post about it, here's to the incredible work done by our team in "keeping the lights on" – managing, analyzing, and reporting complex healthcare data to make a difference every day. #HealthcareData #DataManagement #Teamwork #InnovationInHealthcare

At Oracle, we're using data and AI to improve the care team experience. Revisit this recent webcast to hear how we can help you: https://lnkd.in/ebv4ca87 🧠 Use data to get actionable insights 🔒 Build resilience against cyberattacks 🩺 Restore the joy of practicing medicine

Medical practitioners can tap into vast repositories of medical knowledge instantaneously and make real-time, informed decisions swiftly. Retrieval-augmented generation (RAG) systems enable healthcare providers to retrieve relevant and contextual information from extensive databases quickly. In this article, we delve into the benefits of an RAG system including cost, security, accuracy and performance. Read more here - https://lnkd.in/gGBcVi2S #GenAi #Innovation #AIinHealthcare #HealthTech #HealthcareInnovation #MedicalAI #ArtificialIntelligence #HealthcareTechnology #FutureOfMedicine #RAG