The healthcare and life sciences industry has been making rapid advancements for several years, but it is slow and time-consuming. This has led to a delay in the innovation of new products and healthcare services. But now researchers have the most effective tool – Generative AI. It provides potential opportunities to accelerate health services.
Patients seek advanced healthcare solutions and want to choose the best providers. With Generative AI, healthcare professionals and organizations are better equipped to improve quality, innovation, cost efficiencies, and patient outcomes.
Healthcare organizations alone have approximately 30% of the world’s data. Healthcare and life sciences organizations generate vast amounts of data, including patient records, medical images, electronic health records, genomic information, related research papers, and clinical trial data. Just storing this data is not enough; rather, it can be used as a catalyst for discovering insights, advancing research, and innovations.
Generative AI solutions will allow organizations to process and analyze that data to extract knowledge and insights faster and with better quality. The recent McKinsey survey found that “ 85 percent of respondents—leaders from payers, health systems, and healthcare services and technology (HST) groups—are exploring or already using the technology.” This indicates the rapid implementation and use of Gen AI in leading healthcare and life sciences organizations.
This blog explores the potential use of generative AI in healthcare and life sciences, explaining key risks involved in using Gen AI. Furthermore, we also discuss Snowflake’s AI Data Cloud and Kasmo’s effective solutions to modernize operations and personalize patient care.
How Healthcare Organizations are Using Gen AI
Clinical Decision-Making
Generative AI is highly effective in processing complicated information and accurately identifying health risks for a patient. It is a virtual teammate helping healthcare providers to offer individualized patient care. In addition, gen AI not only helps with diagnosis but also suggests individualized treatment options, providing patient-centered care. Gen AI utilizes huge databases for medical knowledge and current data to suggest therapies and data-driven clinical decisions to save medical professionals’ valuable time.
Improved Care Management
Patient care management is complex and needs more caution. Gen AI uses volumes of data and considers multiple factors for better patient care management. It also analyzes and compares real-time patient data and suggests next actions. The health data is further used to create personalized care plans and help manage chronic diseases by monitoring their health status and adopting the best suitable treatment plans.
Personalize Patient Experiences
Healthcare organizations must adopt value-based care models to provide personalized and effective patient care. Using data, Gen AI offers healthcare payers and providers an opportunity to examine patient preferences, behaviors, sentiments, and health status to create customized care plans and visits. This analysis helps to describe a comprehensive plan with a highly targeted and relevant patient care journey.
How Healthcare Organizations are Using Gen AI
Accelerate Drug Discovery
Life sciences R&D is costly and requires several years. Generative AI can sift through large bodies of biomedical data, such as genetic data and clinical trials, to discover interactions, provide new drug targets, and determine drug safety and efficacy, accelerating drug development. Generative AI also has the potential to speed up personalized medicine based on large bodies of clinical data to tailor patient treatment.
Commercial Use
Generative AI helps in the effective marketing of new drugs. It helps healthcare businesses to create marketing presentations, advertisements, health-related informative posts, and other promotions. Thus, gen AI is transforming healthcare marketing to enable more targeted, efficient, and personalized patient engagement.
Knowledge Management
The life sciences sector is prone to continuous changes, making it difficult for professionals to cope with the latest trends. Here, life sciences organizations can use generative AI effectively for researching, documenting, categorizing, analyzing data, and gaining insights, etc. Generative AI also manages vast health data, helping in trend analysis and enabling better decision-making.
Risks to Consider When Using Generative AI
Data Breaches
Data threats and breaches lead to data security violations. Data breaches occur when sensitive data and patient confidentiality are accessed without authorization. This harms patient privacy, financial stability, and operations. To prevent data breaches, life sciences and healthcare organizations need to implement robust security measures to gain patient trust.
Ethical Considerations
Using Gen AI also brings ethical considerations on how the data is being stored, used, and monitored. To meet these copyright and intellectual property concerns, life sciences and health organizations need to adopt ethical policies respecting patients’ information, consent, and confidentiality.
Technical Complexities
Healthcare and Life Sciences companies face several technical complexities, like HIPAA compliance and data privacy, and integrating fragmented data from different sources. This holds back organizations from the effective implementation of AI technologies. Following robust and integrated data security solutions helps to maintain patient data privacy and reduce technical errors.
Bias and Discrimination
Generative AI is trained on larger data volumes, which consist of biases and discriminators. They exacerbate inequities in health and life sciences if not analyzed or addressed. Hence, organizations should implement robust techniques to detect and mitigate bias in gene AI models. Conduct regular audits and evaluations to identify and rectify these biases.
Snowflake AI Data Cloud for Healthcare & Life Sciences
The Snowflake AI Data Cloud for healthcare and Life Sciences provides a unified platform, helping to break data silos, access diverse data types, improve drug discovery, enhance patient care, and operational efficacy. Thus, it enables organizations to conduct complex analytics with patient data while adhering to privacy regulations and deliver better patient outcomes.
Unified Patient 360-degree View
Snowflake provides organizations with a unified platform to gain a 360-degree patient view by consolidating structured, semi-structured, and unstructured data from different sources into a single, scalable system. This 360-degree view helps to provide personalized treatment plans, better communication, and enhanced patient engagement. The AI-powered virtual assistants and chatbots are used to enhance patient care and lower operational costs while ensuring privacy and trust.
Deliver Better Patient Care
Snowflake helps to break down data silos to provide essential insights to elevate patient outcomes. Ensures the secure sharing of data within the organization while maintaining the privacy of sensitive data and following HIPAA, HITECH, and other regulations. With the effective use of AI/ML workloads, businesses can analyze patient data and identify patient risks, predict progression of diseases, and target intervention to deliver better patient care and outcomes.
Healthcare Supply Chain Optimization
Snowflake helps healthcare organizations to proactively manage supply chain risks using a single unified platform. This helps to increase your organizational visibility in the healthcare and life sciences value chain, effective for automation and identifies hidden insights on healthcare supplier events, estimated availability of medicines or equipment, and transportation facilities. Thus, it helps in the timely delivery and maximizes patient care.
How Kasmo Solutions Helps Healthcare and Life Sciences Organizations to Leverage Gen AI?
Implementing Gen AI is essential for healthcare and life sciences organizations. Kasmo – a true-blue Premier Partner of Snowflake, enables you with innovative and patient-centered solutions for secure data management and to use gen AI for better health services.
KasMed AI Agent
KasMed AI Agent is an intelligent medical assistant built by Kasmo using Snowpark Python and Streamlit. It helps to engage with users and provide real-time medical information, advice, or support. Providers can easily gain answers regarding health conditions, diseases, and treatment.
It helps healthcare and life sciences businesses in research and provides educational materials about a wide variety of health topics. The AI Agent helps to summarize complex medical documentation into the most relevant parts of the complex documents in minutes. This helps to save time and helps healthcare professionals focus more on patient care.
KasFlow
Kasflow is a healthcare enterprise data management and migration solution. It helps to gather data from multiple sources like EHRs, billing, and labs into one place. Using Snowflake Openflow, Kasflow provides fast, secure, and smooth workflows to help manage your data in support of analytics and AI projects.
Kasflow allows healthcare organizations to accelerate data migration with ease and drive insights while adhering to data standards. It helps healthcare organizations in seamless data migration, improves data quality, and helps to provide a better patient experience.
Conclusion
Data has immense potential to advance the healthcare sector and level up the game in life sciences. The effective use of data with Gen AI helps organizations unlock multiple opportunities, from analyzing insights for personalized patient care to examining the efficacy of new drug discovery.
Using Snowflake AI Data Cloud and Kasmo’s solutions, healthcare organizations can mitigate challenges in data management and implement gen AI to provide better services. Partnering with Kasmo businesses can access KasMed, an agentic AI that answers complex medical information in a simpler format, thus saving healthcare providers and payers time and effort. Kasflow helps in enterprise data management to enable seamless data migration and deliver better patient care.
