Leading the Business of Healthcare
RCM Advisor

Quarter 3 2023 - Volume 28, ISSUE 3

Opportunities and Challenges for Medical Billing Companies with Artificial Intelligence

Compliance Issues

By Chad Schiffman

There are several opportunities and areas within the healthcare industry where artificial intelligence (AI) is rapidly growing. For example, Microsoft and Epic recently announced plans to integrate generative AI into Epic’s electronic health record (EHR) software. According to the announcement, the focus is to deliver an array of generative AI-powered solutions integrated with Epic to increase productivity, enhance patient care, and improve the financial integrity of health systems globally.   

There are other reports indicating the potential impact AI will have on the healthcare industry. According to a report by Grand View Research, the global healthcare AI market size was valued at $4.9 billion in 2020 and is expected to grow at a compound annual growth rate of 43.8% from 2021 to 2028. The same report predicts that the healthcare AI market will reach a value of $114.9 billion by 2025. Other reports estimate that by 2026, AI will save the healthcare industry up to $150 billion annually within the US healthcare economy.  

What About Medical Billing Companies?  

There are exciting opportunities for the use of AI in medical billing that offer numerous benefits, including improved efficiencies, accuracy, and cost-effectiveness. However, with opportunities come challenges. One of the biggest challenges is ensuring the appropriate use of AI. Here are some recommended guidelines to consider:  

  1. Compliance with Regulatory Requirements: Ensure that the processes with the organization’s AI will be used to adhere to applicable healthcare regulations, such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States or similar data protection laws in other countries. 
  2. Data Quality and Integrity: AI algorithms rely on accurate and reliable data to make billing decisions. Maintain high standards of data quality and integrity, including data validation, cleaning, and regular audits. Ensure that data used for billing purposes is up-to-date, complete, and free from errors or biases.
  3. Transparency and Explainability: AI systems used in medical billing should provide transparency and explanations for their decisions. This will require reviewing and making sure billing processes and algorithms are understandable; to the healthcare providers using them, the billing and coding staff assigning codes and submitting for reimbursement, and the patients when they are billed. 
  4. Human Oversight and Expertise: While AI can automate many billing processes, human oversight and expertise remain essential. Maintain a human review and validation process to ensure that AI-generated billing codes, claims, and reimbursements are accurate and appropriate. Human experts should be involved in handling complex or exceptional cases.
  5. Monitoring and Improvement: Regularly monitor the performance of AI systems in medical billing and promptly address any issues or errors. Implement mechanisms to collect feedback from healthcare providers, patients, and billing personnel to identify areas for improvement. Regularly updating and refining the AI algorithms may be necessary to enhance accuracy and efficiency.
  6. Collaboration and Communication: Foster collaboration and communication among stakeholders involved in medical billing. Maintain open channels of communication to address concerns, provide clarification, and ensure a shared understanding of the AI systems’ purpose, capabilities, and limitations.
  7. Ethical Considerations: Consider the ethical implications of using AI in medical billing. Ensure that the use of AI aligns with ethical principles, including patient autonomy, privacy, and well-being. Avoid using AI systems that could compromise patient trust or undermine the integrity of the billing process.
  8. Training and Education: Provide adequate training and education to billing personnel and other stakeholders who use AI in medical billing. Ensure that they understand the purpose, benefits, and limitations of AI systems and that they can effectively utilize and interpret AI-generated billing information. 
  9. Secure Data Storage: It is important to ensure that the data used in AI for medical billing and coding is securely stored. This includes using encryption and access controls to limit who can access the data. 
  10. Regular Security Risk Assessments: Regular security risk assessments should be promptly conducted to identify and address vulnerabilities.
  11. Business Associates and Other Vendor Management: It is essential to vet business associates and other vendors providing services that utilize AI for medical billing and coding to ensure that adequate security measures are in place. This includes the execution of a Business Associate Agreement, reviewing vendor security policies, and conducting regular security assessments.

In Summary  

“A good use of technology simplifies things related to workforce and workflow,” said Chero Goswami, Chief Information Officer at UW Health. His comments were included in the Microsoft and Epic announcement. For medical billing companies, the use of AI may provide simplification for the workforce when it comes to day-to-day workflow and processes. Billing companies should evaluate current processes, review what opportunities are available, and determine whether any challenges for the appropriate use of AI can be reasonably addressed. If and when AI will be utilized in your organization, implement a policy that will set expectations for its deployment and maintenance. 

Chad Schiffman joined Healthcare Compliance Pros (HCP) in 2014 as the director of compliance. He has more than 20 years of experience in healthcare, information technology and compliance consulting services. Chad is primarily involved in consulting with healthcare clients about their HIPAA and HIPAA HITECH-related issues including breach determination, breach mitigation and corporate OIG and CMS compliance.