By Vijayashree Natarajan, SVP, Head of Technology
AI in Healthcare: Where It Started & Where It’s Going
Artificial Intelligence (AI) has dominated the headlines over the past few years, especially regarding its application in healthcare. While it may seem like a new technology, AI has existed in some form or fashion since the 1950s.
The Logic Theorist, a program that mimicked human problem-solving, is considered the first AI program. According to Science in the News (a Harvard publication), the Logic Theorist was introduced in 1956 at the Dartmouth Summer Research Project on Artificial Intelligence (DSRPAI).
Fast forward several decades, and large language models along with machine learning and generative image models have reached a level of maturity that has driven AI’s entrance into healthcare. In particular, ChatGPT has shown multiple healthcare use cases, including “research, diagnosis, patient monitoring, and medical education.”
Identifying Risk Opportunities
Leveraging AI in healthcare brings with it many uncertainties, especially with regard to its impact on existing technology systems and revenue cycle operations.
There are many considerations and strategies organizations should prioritize when adopting AI solutions across key areas of the healthcare system.
Technology Risk
Minimizing manual workflows and reducing administrative burdens are two primary benefits of AI in healthcare settings, and many organizations have begun implementing technology solutions to streamline operational processes.
However, with AI technology transformation comes risks surrounding:
- developing and/or hiring a team to manage data privacy and security
- ensuring humans are in the loop for complex decision-making
- integrating seamless handoffs into efficient processes
- predictive analytics accuracy
- expertise in cleansing and managing sufficient volumes of data for model development, training, and continuous optimization
- system disruptions
- implementation costs
Healthcare organizations must pursue an AI approach that accounts for these areas of risk to prevent workflow delays, data breaches, and suboptimal technology utilization or adoption.
This means establishing standards and protocols, including:
- Data Governance Policies like role-based access controls and regular audits to ensure the integrity, confidentiality, and availability of sensitive data.
- System Disruption Contingency Plans that include scenarios involving AI system failures. Ensure these plans are tested regularly and updated to accommodate new technological integrations.
- Staff Training and Support that covers both the technical aspects of the AI systems and the organizational changes that come with digital transformation.
Revenue Cycle Risk
With skyrocketing expenses, staff shortages, and sluggish margins, many organizations are taking drastic measures to try to achieve pre-pandemic revenue levels.
Implementing AI helps automate and optimize revenue cycle processes to improve cash flow and reimbursement while reducing denials and write-offs. Additionally, it reduces friction across functions – leading to better experiences for patients, providers, and administrators.
However, given the complex, multi-tiered nature of the revenue cycle, there are many opportunities for disruption when new tools are introduced.
The biggest risk AI poses to the revenue cycle is the negative financial impact when errors occur. If your organization does not have the proper guardrails established, you become vulnerable to delayed or lost revenue, billing system outages, and halted operations.
Below are a few ways to set up essential frameworks that mitigate revenue cycle risk for your organization.
- Timely Monitoring and Reporting Tools to track AI performance and the health of revenue cycle processes continuously – including dashboards covering anomalies and trends that could signify issues needing swift resolution.
- Dedicated AI Oversight Team, including experts from IT, billing, compliance, and clinical operations to ensure all aspects of the revenue cycle are considered in AI deployment.
- Predictive Analytics to foresee potential delays or problematic patterns in revenue cycles before they become critical issues.
- Generative AI to automate and optimize complex processes, and create efficiencies to expedite claim resolution—while meeting security, compliance, and data requirements.
The Increasing Importance of AI Partnerships
A 2023 survey by Bain & Company found that three out of four health leaders believe generative AI has the ability to “reshape the industry,” but just 6% have created an AI strategy.
Despite the significant potential AI offers the healthcare industry, few health systems have prioritized deploying the resources and initiatives to onboard new solutions in a comprehensive way that accounts for the many layers of risk it brings.
Partnering with industry experts offers an alternative approach, helping organizations gain all the benefits of AI faster and with less effort.
When choosing a partner, organizations should look for one that can demonstrate leadership in healthcare digital transformation. Some qualifications to consider include:
- Extensive experience in technology and RCM risk management
- Deep expertise with AI use cases for administrative and financial operations
- Employment of the latest technology, including AI and its associated tools
- A highly trained global workforce adept in using AI, as well as multiple healthcare information systems
- An automation-first approach to proactively identify opportunities for leveraging AI tools to manage risk
- Customized tools to meet the unique needs of the organization
The Journey Forward
As AI evolves, payers and providers must evolve along with it.
When you find the right partner for your AI solution deployment, your organization can reduce the need for large investments in new infrastructure while maximizing the benefits of AI.
Omega Healthcare provides the strategic partnership you need. We listen to understand your concerns, incorporate your feedback, and guide you to data-informed solutions.
We bring together people, processes, and technology to create intelligent solutions that ensure speed, accuracy, and compliance across clinical, administrative, and revenue cycle areas.
Learn how your organization can thrive in the era of AI by downloading our white paper, Revolutionizing Revenue Cycle Management: Unleashing the Power of Automation through RPA.