How AI Can Help with Contract Management

Posted by Gerry Blass
Laptop with graph

By Gerry Blass and Robert F. Porr, CHC

Nearly half of healthcare executives polled in a 2019 Accenture study rank artificial intelligence (AI) as the technology that will have the highest impact on improving their organizations’ operations in the next three years.1 The use of AI for improved patient care diagnostics and precision medicine are widely discussed among clinicians and the public. Unfortunately, little is promoted on the use of AI technology in healthcare for nonclinical operations, including health information management (HIM). In fact, current use cases are found in areas such as finance and billing, medical chart reviews, and patient self service.2

Here, we explore how HIM leaders and teams can apply AI technologies to help manage business associate agreements (BAAs) and payer contracts. We will also discuss the importance of standardized data for AI to work properly, and the potential impacts of AI on HIM staff.

Management of Business Associate Agreements

Most standard BAAs are template-based—especially nondisclosure agreements (NDAs) and purchase contracts—and are prone to human error. Every BAA in an organization should be checked annually for consistency and accuracy. However, lack of time and resources, combined with the large number of agreements, severely limits the ability to perform recommended annual reviews. Review and management of BAAs is a prime example where utilization of AI can be valuable to rapidly identify problem agreements that require further detailed review by a manager, compliance officer, or legal counsel.

AI technologies can be implemented to help answer the following questions:

  • Has a contract expired, or is a contract expiration upcoming? Knowing which contracts have expired or are about to expire helps HIM teams prioritize which BAAs upon which they should focus within a given time frame.
  • Has the covered entity made recent changes to security and compliance procedures? If so, do BAAs reflect the latest changes? Likewise, are the BAAs in compliance with current state and federal regulations regarding data exchange, privacy, and security? Have they been updated to reflect recent changes? AI can be tuned to search for specific language across thousands of documents and identify those that need revisions.
  • Are business associates (BAs) in compliance with required security and data risk assessments per the BAA? Artificial intelligence can be used to scour agreements and other documentation to determine if assessments have been completed per the agreements. Such technology may also be used to reveal trends that identify particular vendors as especially high risk. Again, having this intelligence will help HIM teams focus limited time and resources on the areas of most need.
  • Are downstream BAs covered in the contract and are their agreements up to date? Similarly, AI can be used to look specifically for downstream BA language and flag for any high-risk areas or trends to address.

Not to be excluded, AI technologies themselves are deployed by business associates. It is imperative that healthcare organizations hold AI vendors to the same security and compliance standards as all other BAs.

Management of Payer Agreements

A typical health system may manage hundreds, even thousands, of payer agreements, many of which have components that are negotiated and managed by the HIM team. Ideally, each contract should undergo an annual compliance review, but here again, the volume and limited resources make it nearly impossible to do so.

A study conducted with Stanford University, Duke University School of Law, and University of Southern California compared the length of time and accuracy of legal document review between humans and AI. It took the human staff 92 minutes to review five legal documents. AI technology reviewed the same documents in 26 seconds with a 10 percent higher accuracy rate.3

HIM leaders may consider using AI tools to:

  • Review multiple contracts with the same entity to uncover any inconsistencies
  • Review contracts for compliance with federal or multi-state requirements
  • Review and update data rights accessibility and standards
  • Flag contracts that are up for renewal

With a quicker turnaround time and higher accuracy, the use of AI may also help target areas in payer agreements, such as terms and conditions for release of information, that are ripe for negotiation and could save time and money for the provider.

Data Management, Accuracy, and Governance

For HIM leaders, data management and governance is the potential sweet spot for artificial intelligence. But, the path of data both to and from the healthcare organization needs to be properly managed. For AI to work properly, the data needs to be standardized, normalized, and accurate. Otherwise, any results generated from AI will suffer the same inaccuracies as the original data (in other words: “garbage in, garbage out”).

Right now, the industry as a whole lacks standards for data governance. The push for interoperability, the Internet of Things (IoT), medical devices, health information exchanges (HIEs), and countless electronic health record (EHR) systems all contribute to vast amounts of patient information coming into a provider organization, none of which is normalized or standardized.

A recent research paper on the implications of AI on HIM states, “In AI-enabled healthcare, the underlying organizing schema for health data needs to shift from dates of service to the patient. It may require completely different data architecture to collect, store, process, validate, interpret, and potentially retrieve non-episodic ongoing streams of patient-specific data… Evolving data governance principles are necessary and must be a priority for all healthcare organizations.” The authors go on to say that a key enabler to AI technologies is the development of clear, consistent, and standardized policies and procedures for creating and managing current and emerging sources of data.4

HIM leaders depend on the accuracy and integrity of patient data to enable clinicians to make the most informed decisions about patient care. Indeed, the HIPAA Security Rule requires appropriate administrative, physical, and technical safeguards to ensure the confidentiality, integrity, and security of electronic protected health information.5 What is important to avoid is using information generated by AI that could negatively impact patient care, operations, and billing.

When evaluating the potential use of artificial intelligence tools, HIM leaders should inventory all sources of health information—to and from all BAs and payers—documenting how data comes in, how it is formatted, and how it is used. This type of information will help uncover data governance gaps that may need to be filled before AI can be deployed.

Potential Impacts on Staff

Artificial intelligence tools can be a tremendous support for any department, such as HIM, that requires repetitive, labor-intensive review of high volumes of documentation—such as billing, legal agreements, medical coding, and patient records. Without AI, these types of transactional activities are typically fulfilled by humans, take longer, cost more, and are more susceptible to human error.6 The technology is not meant to replace professional judgement or existing technology investments. Rather, AI applications supplement existing systems and processes to perform labor-intensive work, removing the burden of having higher-trained staff performing elemental tasks and elevating their interaction to more strategic and valuable decision-making functions.

Indeed, the past five years have already seen a change in the types of work that HIM teams perform. Many HIM professionals who previously spent significant time on medical coding and records processing now find themselves in diverse roles related to healthcare leadership, teaching, technology, compliance, quality, and informatics.7

By putting time- and labor-intensive data review in the hands of AI, HIM leaders can more effectively use their time investigating trends, using data-enabled information to make decisions, and actively participating in the development of policies, procedures, and best practices around data governance.8 The advent of artificial intelligence can help accelerate this shift of HIM leaders and their teams into more strategic roles that advocate for data governance and the adoption of AI among clinicians and other operational staff.

  1. Accenture. “Digital Health Tech Vision 2019.” June 4, 2019.
  2. Ibid.
  3. Nicholson, Sibel. “AI Proves to Be 10% Faster and More Accurate Than Top Human Lawyers.” Interesting Engineering. February 27, 2018.
  4. Stanfill, Mary H. and David T. Marc. “Health Information Management: Implications of Artificial Intelligence on Healthcare Data and Information Management.” Yearbook of Medical Informatics. August 2019
  5. US Department of Health and Human Services. The Security Rule.
  6. Accenture. “Digital Health Tech Vision 2019.” June 4, 2019.
  7. The American Health Information Management Association (AHIMA). “Survey Predicts Future HIM Workforce Shifts: HIM Industry Estimates the Job Roles, Skills Needed in the Near Future.” Survey conducted September 11, 2014 to October 3, 2014.
  8. Stanfill, Mary H. and David T. Marc. “Health Information Management: Implications of Artificial Intelligence on Healthcare Data and Information Management.” Yearbook of Medical Informatics. August 2019

Gerry Blass ( is president and CEO of Comply Assistant.

Robert F. Porr ( is principal, Furnace Brook Healthcare Management Advisers, LLC.