Transforming Healthcare leveraging Generative AI

Generative AI (Gen AI) rapidly transforms various industries, including healthcare. Generative AI solutions rely on deep learning algorithms to process massive amounts of unstructured/structured medical data and create new content such as audio, text, code, etc. These generative AI solutions can dramatically improve the quality of care, make it more affordable and accessible, and ensure equality in research and care delivery.

This blog outlines the existing and emerging Generative AI use cases across the healthcare industry segments, including Providers, Payers, Pharma firms, MedTech leaders, and Population Health management agencies.

Payers

Payers increasingly use generative AI to cut costs, enhance risk management, and engage members, aiming to provide better coverage at lower consumer expenses.

Claims Management

Gen AI can automate the underwriting and claims management process. Generative AI models can also expedite the resolution of claim denial. It can summarize denial letters, consolidate denial codes, highlight denial reasons, and suggest next steps for denial management.

Healthcare Management

Gen AI solutions can synthesize clinical notes, medical, and referral information for care managers and generate care plans and summaries for members.

Member Services Management

Gen AI Solutions can be used to generate call scripts (Call Center and Online Support) for all nonclinical conversations and create coverage summaries for specific benefits questions. It can also deploy intelligent chatbots and routing to help members with service-related queries.

Provider relationship Management

Generative AI can compare plan/product features and networks. It can generate standard documents like reports, claim denials, welcome letters, new member needs, etc. It can also summarize gaps in provider directories and generate reports for providers and vendors on performance and gap closures.

Providers

Generative AI solutions can transform the entire gamut of Provider businesses, from continuity of care to clinical operations and analytics to corporate functions and consumers.

Continuity of care

Generative AI solutions can create discharge information and post-acute care summaries. It can also generate care summaries for referrals, synthesize custom care notes for physicians, and recommend patient-centric risk considerations based on the patient’s medical history and existing medical literature.

Value-based care

Generative AI can leverage structured and unstructured data to generate educational videos, audio, images, and patient summaries. It improves the overall documentation process and accuracy.

Clinical operations

Generative AI can generate post-visit summaries and care instructions for patients, craft care coordination notes, update EMRs, record dictations, and manage messages for efficient communication. It can develop workflow materials and schedules tailored to specific processes and locations and create educational resources for disease identification and management. Additionally, it can design personalized training programs for clinicians across different specialties.

Reimbursement

Gen AI can populate prior authorization documentation tailored for payers. Gen AI can be leveraged to compile a list of current medical conditions and potential corresponding codes derived from various sources, including voice, electronic medical records (EMRs), text, and other data. Gen AI models can also produce care management summaries that pinpoint coding errors within claims.

Clinical Analytics

Gen AI models can use conversational language for analytics insights. It can leverage AI-driven coding for automation and new code generation.

Corporate functions

Generative AI can address and improve all aspects of a hospital or physician group's corporate functions, for example.

• IT: Code development, cybersecurity test-case generation, quality assurance.
• Procurement: RFP and contract drafting, report generation, vendor communications, and purchase orders based on supply levels.
• Talent: Hiring assistance, offer letters, customized SOPs, new hire education, onboarding, HR and IT chatbots.
• Finance: Financial report generation.
• Other: Reports for regulatory, legal, and compliance.

Pharma Industry

Gen AI can significantly accelerate drug development, improve the chances of success, and reduce research and development costs in the pharmaceutical industry. It also improves clinical trial planning and execution, leading to precise medical therapies.

Drug Discovery and Design

Generative AI models can speed up drug discovery by

• Creating and producing novel molecules with specific attributes for subsequent evaluation in laboratory experiments.
• Anticipating the characteristics of new drug candidates and proteins.
• Producing virtual compounds with strong binding affinity to the target, suitable for cost-effective computer-based testing.
• Predicting potential side effects of novel drugs through an analysis of their molecular structures

Biomarker Discovery

Generative AI aids in identifying biomarkers related to diseases and drug responses. This helps in early disease detection, patient stratification, and the development of targeted therapies.

Medical Image Generation

Gen AI models can also generate medical images for diagnostic purposes.

MedTech Industry

Generative AI can potentially enable the development of personalized and patient-centric devices, including software that supports preventive maintenance and repairs.

Patient-centric devices

Generative AI can optimize the design and customization of medical devices like prosthetics and implants, tailoring them to individual patient requirements. Additionally, MedTech companies are integrating remote monitoring capabilities into pacemakers and implantable defibrillators through this technology.

Brain Health

Some platforms utilize generative AI models to analyze electroencephalography (EEG) signals for predicting and monitoring brain aging. This platform offers insights and tools to aid in diagnosing, preventing, or mitigating cognitive decline among patients with mental health and neurodegenerative disorders.

Surgical Support

Generative AI models can provide real-time, on-demand surgical insights and guide medical workflows inside the operating room.

Population Health Management

Government ministries and other health organizations can harness generative AI to enhance resource planning and allocation, anticipate public health requirements and interventions, and execute programs more efficiently.

Public Health Monitoring

Generative AI-powered tools have the potential to monitor public health and optimize resource allocation and forecasting based on health data. Government organizations could also apply it during drug safety and efficacy evaluations. Public health organizations like Doctors Without Borders could also utilize generative AI to forecast outbreaks and efficiently mobilize resources to mitigate their impact.

Managing Pandemics

Gen AI-powered tools can be used to develop an early warning system for COVID-19 variants. Structural modeling of the SARS-CoV-2 protein combined with generative AI capabilities allows the system to proactively alert researchers, vaccine developers, health authorities, and policymakers.

Managing Potential Risks and Bias

While generative AI technology shows promise, exercising caution in the near term is essential. There are several inherent risks that healthcare providers must address before widespread adoption can take place.

Biased Results

Generative AI results may inherit biases from the underlying data. Generative AI companies should appoint experts to review and correct bias using techniques like oversampling and statistical adjustments. Gen AI may inherit biases from data, necessitating expert oversight and bias correction techniques.

Incorrect Results

As AI models evolve, they can occasionally produce incorrect results, a phenomenon known as hallucination. Providers should prioritize transparency and human review of AI-generated outputs to mitigate this.

Data Privacy

Given the sensitivity of patient health data, companies offering generative AI solutions should establish clear data ownership agreements with partners, enhance cybersecurity measures, and explore the use of synthetic data beyond existing sources.

Lack of trust

Generative AI often operates as a black box, which may raise user concerns. Healthcare organizations must enhance trust and adoption by explaining algorithm operation and how specific data informs prognosis.

Misuse or Overdependence

Patients might overly rely on generative AI information. Hospitals, clinicians, and payers should communicate clear guidelines for using AI-generated insights, emphasizing that they are recommendations rather than mandates.

How to start your Gen AI journey

Health IT Leaders must embrace Generative AI for healthcare transformation. This involves exploring innovative offerings, investing in robust data systems, building internal expertise, fostering ecosystem integration, and collaborating closely with regulatory agencies to ensure compliance and safety.

Generative AI encompasses uncertainties and risks, yet it also can significantly enhance efficiency, elevate the quality of care, and generate value for healthcare organizations. This is why leaders must chart a course to leverage this technology, commencing today.

• This involves exploring innovative offerings and business models powered by generative AI. Simultaneously, investing in robust data systems is crucial, channeling resources into data management and analysis tools capable of effectively harnessing vast and diverse datasets.
• Investments in capabilities are also essential. This includes recruiting in-house experts who can provide guidance, implement generative AI initiatives, and oversee their progress. Training key stakeholders in utilizing generative AI for informed decision-making is also critical.
• Integration with the broader ecosystem is equally vital, necessitating the establishment of data interoperability, foundational systems, and offerings conducive to generative AI. Close coordination with regulatory agencies, which is imperative to co-develop safe and effective solutions that align with federal compliance and standards.

In conclusion, Generative AI holds the potential to revolutionize healthcare, making it more accessible, efficient, and patient-centric. As CXOs, it's imperative to recognize and leverage the opportunities this technology offers while addressing the associated challenges responsibly. Embracing Generative AI today can pave the way for a brighter and more effective future in healthcare.