As the industry moves toward the purposeful adoption of generative AI advancements, there are three key considerations that can help guide effective implementation:
1. A Well-Defined Organizational Data Framework Can Close AI Gaps
Establishing a clear data framework will help healthcare organizations better prioritize business opportunities and technology use cases as well as identify gaps in data strategy. Data strategy is key to the effective application of generative AI, which can help automate code development, enhance data protection and governance, and accelerate insight generation at the point of care.
According to the World Economic Forum, nearly 97% of data produced by hospitals each year goes unused because it is trapped in unstructured formats. Healthcare organizations that have a clear data strategy in the cloud will have a significant advantage to drive better outcomes, with the ability to securely and compliantly use the available data at unprecedented speed. A comprehensive set of capabilities is required to harness this data, including:
- Mindset: Data strategy, goals and resources
- People: Team skills, data literacy and advocacy
- Process: Data management, governance, security and use processes
- Technology: Data and AI/ML platform, and architecture
Prioritizing AI awareness and training at all levels and job roles in the organization can drive better decision-making, improve effectiveness and increase satisfaction among employees and patients. Organizations can access free generative AI skills training to help upskill and support their workforce. Many of the trainings can offer a learning experience in virtual hospital settings, giving learners the opportunity to build skills in real-world scenarios.
PREPARE: Demystify artificial intelligence adoption for your healthcare organization.
2. Consider Productivity Use Cases to Start Your Gen AI Journey
Applications for back-office functions and administrative task burdens are perfect examples of the value of AI in healthcare: driving efficiencies for clinicians. Hospitals face efficiency challenges such as delays relaying information to patients due to inefficient prior authorization processes, extracting clinical data from unstructured reports, difficulty managing operating room schedules, and care coordination related to readmissions. AI-enabled natural language processing can instantly extract essential clinical data to generate real-time prior authorization submissions to payers; machine learning can optimize operating room scheduling; and predictive analytics can pinpoint at-risk patients in order to provide prompt outreach and intervention.
With the evolution of generative AI, provider organizations now have additional resources to rapidly classify, extract and analyze data at scale across complex and disparate care records and clinical documents. For example, generative AI solutions related to document generation and form-filling can assist with patient discharge management by driving streamlined processes that save time and money, as evidenced by organizations such as Centene Corporation.
Genomics England, a leader in human genome research, is developing a solution using generative AI to enable researchers to quickly process millions of pages of literature to surface potential gene disease associations faster than manual review alone, with 20 potential clinically relevant associations already identified. Healthcare providers are already exploring similar approaches across a wide variety of clinical review and synthesis use cases, including automated clinical coding, guideline summarization and personalization of care information.
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Fujita Health University, the largest private medical university in Japan, is using generative AI to explore possible improvements to doctor workflows. This pilot project evaluated the feasibility of using generative AI capabilities to generate discharge summaries, which are critical medical records that capture a patient’s treatment history and diagnosis during their hospital stay. With generative AI on Amazon Web Services, Fujita reduced the time required for discharge summaries by up to 90%, bringing it down to approximately 1 minute per patient.
Fifty-seven percent of clinicians have reported that excessive documentation contributes to burnout. Generative AI solutions such as AWS HealthScribe are equipped with speech recognition to automatically create robust transcripts, extract key details (e.g., medical terms and medications) and create summaries from doctor-patient discussions. Generative AI enables efficient extraction and summarization of clinical details using large language models, and organizations such as Pieces Technologies and 3M can now build and deploy secure clinical solutions quickly so healthcare organizations can focus on delivering differentiated experiences for their employees and patients.
3. A Responsible AI Framework Supports Mission-Based Organizations
AWS provides a robust framework for responsible AI deployment to help customers prioritize the privacy and security of user data, and monitor and mitigate potential biases. AWS HealthScribe is a HIPAA-eligible service that allows organizations to securely store and transform their data into a queryable format at petabyte scale, and further analyze this data using machine learning models. As generative AI matures and its use within healthcare becomes more widespread, AWS will continue to develop generative AI on a global scale so that providers, patients and healthcare agencies have access to secure tools for a variety of use cases.
Jump-Start Generative AI Exploration
AWS provides support for highly innovative, mission-critical projects that leverage generative AI to produce scaled, repeatable solutions that accelerate mission achievement and may impact the entire industry. Through programs such as the AWS IMAGINE Grant: The Pathfinder - Generative AI Award, nonprofit healthcare organizations may receive unrestricted cash funding, AWS promotional credit, AWS marketing support and implementation support from the AWS Generative AI Innovation Center to translate their generative AI ideas into action. The AWS Worldwide Public Sector Generative AI Impact Initiative is another program available to healthcare organizations that provides AWS promotional credit so organizations can experiment with the company’s generative AI services.
