How Artificial Intelligence Can Aid Post-Merger Integration
More than just a buzzword, artificial intelligence is already proving to be a game changer for organizations across a variety of industries—despite being in its infancy stage.
Building off digital transformation, AI empowers organizations to leverage vast of amounts of data that is collected and generated. Using machine learning, AI enables mountains of data to be analyzed for trends and insights at rates much faster than what any human can deliver.
For example, wealth management companies utilize AI and algorithms to scan data in the markets to predict the best stock or portfolio based on preferences. Advertisers use AI to target consumers by seeking out specific audience characteristics.
In the healthcare industry, AI has the potential to significantly change patient outcomes with faster, more accurate diagnoses. AI-powered, technology-utilizing machine learning is slowly entering the market to improve analytics and research. Two examples include leveraging data to find new links between genetic codes and the ability to detect and highlight abnormalities in medical imaging systems like X-rays and MRIs.
Operational departments within the healthcare industry also benefit from AI. This is welcome news, especially for health systems and hospitals involved in post-merger integrations.
For the past several years, healthcare merger and acquisition activity has dominated headlines. Some of the more notable deals include CVS Health’s $69 billion acquisition of Aetna in November 2018 and Catholic Health Initiatives $29 billion merger with Dignity Health in 2019, which formed one of the country’s largest health systems, CommonSpirit Health.
With these deals now closed, a new challenge begins—post-merger integrations. During this stage, assets, personnel and business activities of the two companies are combined. Post-merger integration is also where the true value of AI can be realized, particularly when dealing with labor-intensive processes like contract management, credentialing and provider enrollment.
During a merger or acquisition, a newly formed entity can be left to deal with easily tens of thousands, if not millions, of contracts. Contracts likely include, but are not limited to, payer and physician contracts, plumbing, sutures, linens and more. During the post-merger integration stage each contract must be reviewed to assess status and a HIPAA business associate agreement analysis must be performed. AI-powered contract management systems greatly speed this process while providing unprecedented levels of contract visibility, compliance and risk mitigation.
Using AI with machine learning, contract terms and conditions are identified and BAA audits performed. Contracts without the required BAA are flagged for immediate follow-up to ensure one is created. Otherwise, each business associate that does not have a BAA is a risk for non-compliance is identified. This can easily add up to hundreds of thousands, even millions, of dollars in fines for a large hospital or health system.
Integration chaos is expected fallout from post-merger integrations, and it can quickly become overwhelming. This is particularly true when trying to navigate thousands of contracts. When not managed accurately, the financial implication of non-compliance can be devastating.
The typical error rate is 10 percent of total contracts, with fines averaging $31,000 per violation (per the Department of Health and Human Services).
To put this into perspective, if a hospital has 1,500 contracts and 180 contracts (roughly 12 percent) are missing BAAs, the fine potential is greater than $500,000. The larger the hospital or health system, the greater the risk.
AI-powered contract management systems provide an easy solution to the traditionally complex, and often costly, integration phase. With the right solution, streamlining the contract management process, and mitigating risks and fines, can be achieved.
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