Access to accurate, comprehensive data is paramount for driving informed decision-making and improving patient outcomes in healthcare. Machine Readable Files (MRFs) stand at the forefront of this data revolution, offering structured datasets packed with invaluable insights into healthcare services, procedures and costs.
In this blog, we’ll delve into the transformative power of MRFs and examine why they should be used by Payers and Providers, as well as real-world consequences of not using them.
Potential Strategic Uses of MRFs by Payers
Payers stand at the forefront of decision-making, balancing cost-effectiveness and providing members with the best care at the best price and delivering optimal outcomes. This makes MRFs an indispensable tool, offering a trove of data-driven insights.
Benchmarking for better prices
Payers can utilize MRFs to compare their current Provider pricing against competitors’ rates. By benchmarking their rates, Payers can ensure they offer competitive pricing to attract both Providers and members. This comparison helps identify areas where rates may need adjustment to remain competitive. The challenge, however, lies in a lack of standardization that leads to potentially inaccurate conclusions when the data is not approached cautiously.
Additionally, regional variations in healthcare costs and the severity of patients’ illnesses can impact pricing. By adjusting base rates for these factors, Payers can ensure fair and consistent pricing across different geographic regions and patient populations.
For example, if a Payer collaborates with multiple Providers to manage the care of patients with chronic diseases, Payers can leverage MRFs and implement severity indexing algorithms to stratify patients based on disease severity. Additionally, the Payer implements base rate adjustments to ensure fair reimbursement rates based on patient risk profiles. This delivers informed decision-making and provides stakeholders with objective measures of performance.
Negotiating Rates Using MRFs
MRFs provide Payers with valuable insights into marketplace pricing trends. By analyzing this data, Payers can see where certain procedures are consistently priced lower in the market, allowing them to leverage this information during negotiations to secure favorable rates.
For example, if members use a particular lab for a blood draw, the Payer can access the MRF data available to see the other labs in the area and determine how much those labs charge and are willing to accept for a blood draw.
And so, when it comes to the preferred lab that the Payer wants to work with, they can leverage that information. They could approach the lab and say that they have been paying $250 for each blood draw, but four other labs within the same ZIP code are willing to accept $175. This knowledge can open a conversation for price negotiation, leveraging the fact that they don’t want to drive members to these other labs.
The Critical Significance of Accurate Data
In any healthcare negotiation, the importance of using up-to-date data cannot be overstated. The validity and precision of MRF data are cornerstones for fostering trust, transparency, and successful outcomes, and are key components for Payers to adhere to their fiduciary responsibilities.
Credibility and Trust: Accurate MRF data establishes confidence between Payers and Providers during negotiations. Both parties rely on this data to make informed decisions regarding pricing, reimbursement, and contract terms. Inaccurate or unreliable data can undermine trust and lead to contentious negotiations.
Risk Mitigation: The goal of risk mitigation in the context of MRFs is to facilitate data exchange and interoperability in healthcare systems. Measures may include implementing robust data security, ensuring data integrity, and establishing data governance frameworks to ensure compliance with regulatory requirements.
Legal and Regulatory Compliance: Ensuring the accuracy of MRF data is essential for complying with legal and regulatory requirements governing healthcare transactions. Regulatory bodies may impose penalties or sanctions for using inaccurate data in negotiations, further emphasizing the importance of data validation.
Consequences of Breaching Fiduciary Responsibility
Inaction in response to evolving regulatory demands can have profound financial and fiduciary consequences within the healthcare industry. For instance, consider the recent lawsuit involving Johnson & Johnson, wherein plan participants alleged a breach of the plan sponsor’s fiduciary duty for failing to make prudent purchasing decisions on behalf of the plan.
Johnson & Johnson, a prominent healthcare corporation, faced a significant legal challenge with a proposed class-action lawsuit regarding its employee health plans. Filed in New Jersey federal court, the lawsuit accuses Johnson & Johnson of breaching its fiduciary duty under the federal Employee Retirement Income Security Act of 1974 (ERISA) by failing to negotiate lower prices for prescription drugs within its self-funded health plans.
The lawsuit alleges that Johnson & Johnson’s health plans pay inflated prices to pharmacy benefit managers for generic drugs, resulting in substantial overpayments that directly impact workers’ out-of-pocket costs. According to Reuters:
The plans, for example, pay $1,629 for a 90-pill prescription of HIV antiviral drug abacavir-lamivudine that costs pharmacies about $180, according to the complaint. And while prescriptions of teriflunomide, used to treat multiple sclerosis, typically cost no more than $77 out of pocket, Johnson & Johnson’s health plans pay $10,200, the lawsuit claims.1
This disparity raises concerns about fiduciary responsibilities and prudent management of employee benefit plans.
A common response from organizations such as these is that they lack the necessary tools to ensure optimal pricing and compliance, which is incorrect. Technology to utilize MRFs exists, as well as tools to best utilize them for more informed decision-making, benchmarking, negotiation, and compliance monitoring within healthcare organizations.
Failure to leverage MRFs and other modern technologies for data-driven insights can lead to several detrimental outcomes such as:
Financial Repercussions: Plan sponsors may face significant financial penalties, as seen in the case of Johnson & Johnson, where alleged regulatory non-compliance resulted in substantial legal challenges and potential liabilities. In fact, those individuals with the authority to make decisions on behalf of the plan can even face personal liability for breaches of their fiduciary duty to plan participants.
Loss of Trust and Reputation: Healthcare entities risk damaging their reputation and losing the trust of members and stakeholders if they are perceived as not acting in the best interests of plan participants by failing to ensure competitive pricing and transparent operations.
Increased Regulatory Scrutiny: In an era of heightened regulatory oversight, healthcare organizations that do not embrace data-driven approaches for compliance monitoring may attract increased scrutiny from regulatory bodies, leading to further legal challenges and potential sanctions.
Missed Opportunities for Optimization: Without leveraging MRFs and other data-driven tools, healthcare entities may miss out on opportunities to optimize resource allocation, negotiate better pricing with vendors, and improve overall efficiency and effectiveness in managing employee benefit plans.
Accuracy and completeness of data are the foundation for informed decision-making, effective negotiations, and optimal patient care. By meticulously validating data integrity, stakeholders can instill confidence in the reliability and relevance of information utilized across various facets of the healthcare ecosystem. Comprehensive validation safeguards against inaccuracies, mitigates risks, and upholds the integrity of data-driven processes.
Make Data-Backed Decisions with MacroHealth
As the industry continues to innovate and adapt, integrating real-time data analytics, machine learning, and interoperable systems holds promise for optimizing negotiation processes and enhancing collaboration between stakeholders. The tools to fully utilize MRFs are here and it’s time for organizations to make use of them, lest they face severe consequences by breaching their fiduciary responsibilities.
The MacroHealth Intelligent Exchange™ platform can help you lower healthcare costs, achieve better margins, and foster membership growth. By leveraging MRFs for benchmarking, MacroHealth equips you with the ability to optimize your network by confidently make data-backed decisions. Watch our exclusive demo video to explore the transformative capabilities of MacroHealth.
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