Master Service Agreements (MSAs) are an important business tool in virtually every industry, and healthcare is no exception. Streamlining business relationships with long-term providers requires solid MSAs that anticipate and address the complete scope of the services the partnership will involve.
In recent years, many factors have contributed to making MSAs more complex. As a result, ensuring MSAs include components that clarify responsibilities and mitigate risks has become more difficult. At the same time, the consequences of MSAs that contain contractual gaps have also increased, carrying the potential for significant financial loss and legal exposure.
To ensure MSAs are well-constructed, a growing number of organizations are turning to tools powered by artificial intelligence. These tools can play a role in various phases of the agreement process, including drafting templates, reviewing language, and identifying gaps and risks.
Addressing the increased complexity of MSAs
Technological innovation in the business world is one of the top factors contributing to the increasing complexity required in MSAs. Today’s tech tools extend a business’s digital footprint through remote access and cloud-based solutions, often involving automated deployment and maintenance. As such, MSAs must address the new wave of security, liability, and scope of service issues resulting from those innovations.
Vendor consolidation is an ongoing trend in the medical space resulting in services like electronic health records, staffing, and cloud services merging under the umbrella of one provider. This is driving significant shifts in negotiating power that now must be addressed in MSAs. As the marketplace for services becomes more limited, businesses must rethink the components necessary to ensure MSAs protect their interest.
The rise of precision medicine requires MSAs to include several new components. Precision medicine involves genetic testing, digital health data collection, and AI analytics, among other evolving practices. To properly manage those practices, MSAs must be expanded to address intellectual property protections, data ownership, and ethical considerations like non-discrimination and equitable access.
Streamlining MSAs through machine learning tools
The first step in developing comprehensive MSAs is ensuring they include all of the relevant contractual components. With the rapid pace of change in today’s business world, a “standard” MSA can quickly become outdated. Regulatory changes involving HIPAA, HITECH amendments, and CMS rules are ongoing. Gaps can appear in MSAs if those changes are not closely tracked and analyzed for factors that may affect obligations.
Machine learning that involves the ongoing analysis of past MSAs and best practice guidelines from across the industry can empower AI tools to generate effective MSA templates. Including the latest regulatory developments in AI training further ensures that AI-generated templates include all necessary elements. The more comprehensive the training, the higher the likelihood that templates will be exhaustive and legally sound.
AI tools can also be used to tailor templates for the business’s specific needs, including careful consideration of the unique vendor risks, liability concerns, legal stipulations, and more. The tools can also update templates dynamically and automatically, staying connected to relevant data sources and revising templates when changes in regulations, industry standards, or services result in gaps or overlap.
For businesses that prefer to use their own internally generated templates, AI-powered tools can be used to conduct MSA reviews, which can be invaluable for ensuring protection against cyber threats and vendor risks. These reviews can also flag areas that pose a threat to regulatory compliance or that pose legal or financial risks, zeroing in on the unique vulnerabilities that may exist due to the specific factors included in the MSA.
AI-powered review tools can also assess whether MSAs clearly stipulate client responsibilities, including defining what clients must do if they fail to adhere to security recommendations. They can also explore how the MSA approaches the limitation of liability — determining if it is in the business’s best interest — and reveal if the contract exposes a business to unexpected out-of-pocket expenses due to an indemnity section that is out of sync with insurance coverage.
Regarding regulatory risk, AI can ascertain whether MSAs include clear language protecting the business from the multitude of risks associated with data privacy requirements. It also can determine if protection involving ransomware and other malicious acts is sufficiently addressed.
Leveraging AI to increase accuracy and efficiency
The widespread adoption of AI-based tools across the business world has much to do with their ability to process large volumes of information at high speeds and with a high degree of accuracy. That capability lends itself well to the process of drafting and evaluating MSAs.
Evaluating MSAs requires analyzing complex and industry-specific contractual terminology and comparing contract provisions with regulations and best practices to identify gaps. AI-powered tools can do this with a high level of accuracy and at a speed not attainable by human reviewers.
Adaptability is another of AI’s strengths, as it can automatically integrate relevant new developments into its evaluation framework, ensuring its review processes are always driven by the most up-to-date information. AI’s ability to quickly integrate new data is also valuable when businesses shift to address new challenges or take advantage of new opportunities.
One of the most valuable skills AI brings to the business world is objectivity. It provides evaluations that are free of the subjectivity humans can inadvertently introduce into review processes while remaining consistent and constantly available — all while never having an off day or a day off.
Ensuring MSAs support organizational growth
MSAs are a critical component of an organization’s operations. They simplify the procurement and billing processes and drive efficiency by defining preferred provider relationships. Those factors contribute significantly to an organization’s ability to scale its operations without lengthy procurement delays.
MSAs also play a critical role in compliance and security, detailing the steps that will be taken to meet regulatory standards and safeguard sensitive data. Without such provisions, vendor arrangements can present significant operational risks to an organization. MSAs mitigate legal, financial, and reputational risk by contractually transferring liabilities to vendors in appropriate ways.
Crafting an MSA that will address risks and empower growth is a complex process that is constantly evolving. Leveraging AI-powered tools to assist in the process allows businesses to streamline and automate the time-consuming and resource-intensive task.
Editor’s Note: Robert Scott is a thought leader in managed services and cloud law serving as the Chief Innovator for his latest venture, Monjur, with a mission to redefine legal services. Robert has been recognized as the Technology Lawyer of the Year by Finance Monthly and carries an AV Rating as Preeminent from Martindale Hubbell. He represents major corporations in strategic IT matters including cloud-based transactions, managed services contracts, data privacy, and cybersecurity risk management. Robert is licensed to practice law in Texas and holds memberships in several professional associations, including the Dallas Bar Association and the Managed Service Providers Alliance Board. He regularly shares his insights on the MSP Zone podcast and is a frequent presenter in the industry.