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The Truven Health Blog


The latest healthcare topics from a trusted, proven, and unbiased source.


Medicaid Program Integrity: Fighting Fraud in a Managed Care Environment


By David Nelson/Monday, July 14, 2014
David Nelson imageA recently published study by the Government Accounting Office identified a need for states to ramp up their efforts to assure Medicaid program integrity under managed care. Although a majority of Medicaid beneficiaries are now enrolled with managed care organizations (MCOs), and payments for those plans are growing at a faster rate than fee-for-service (FFS) expenditures, some states are just now beginning to shift their program integrity focus from FFS to managed care. 

Traditionally, Medicaid has fought FFS fraud, waste, abuse, and overpayment by applying edits and algorithms to claims in prepayment, and using data mining, investigation, and recovery modeling and analytics in post payment. More recently, Medicaid has stepped up fraud-prevention efforts by expanding the use of prepay predictive analytics and implementing provider credentialing and stringent ongoing provider surveillance, as required under the Affordable Care Act (ACA). 

Best-practice Medicaid agencies have increased their managed care program integrity efforts through more comprehensive oversight of their contracted MCOs. They are collecting and validating encounter data, which allows them to perform advanced analytics to find fraud, waste, and abuse, and they are performing checks to ensure proper Medicaid administration. These agencies examine the full continuum of managed care fraud and abuse vulnerabilities:
  • Traditional FFS issues, such as over-utilization and billing for unnecessary or unused services
  • FFS/Managed Care crossover issues, including double billing and payment for ineligible recipients, such as prisoners and those with certain medical conditions or who are enrolled in certain waiver programs
  • Managed care operational issues, such as inaccurate encounter claims, under-utilization, and cherry-picking patients
  • Managed care financial auditing to ensure that MCOs accurately account for and categorize costs incurred and capitation rates are premised upon correct information
Medicaid agencies need to be diligent stewards of their managed care contracts. While managed care adds new complexities and challenges for monitoring program integrity, the rapid growth in managed care enrollment adds to the urgency of putting in place effective oversight mechanisms. 

Critical Success Factors
As we look across best-practice Medicaid agencies, several critical success factors have been shown to produce significant results for the integrity of the program under managed care. Some of these critical success factors are:
  • Encounter data accuracy and completeness
  • Contract provisions and rules to support managed care payment integrity
  • Capitation payment review
  • Data analytics examining MCO services and comparing MCO utilization to FFS
  • Inter-MCO comparisons and analytics
  • Managed care organization auditing (both financial and operational)
By incorporating such success factors, Medicaid agencies can avoid common fraud, waste, and abuse pitfalls under managed care and improve the integrity of the program.

Truven Health Analytics™ has been helping managed care organizations in all of these dimensions for several years. Our experts have advised 20 states over the past 15 years about managed care encounter data strategy, and our program integrity experts have been delivering recoveries to Medicaid agencies for three decades. In fact, IDC MarketScape recently named us an industry leader in fraud, waste, and abuse solutions.*

For more information, please contact me at david.nelson@truvenhealth.com.

David Nelson
Vice President, Market Planning & Strategy

Managing Medicaid Managed Care and Encounter Data


By David Nelson/Monday, May 19, 2014
David Nelson imageMedicaid agencies have increasingly turned to managed care organizations (MCOs) to deal with the tremendous increase in enrollment driven by the Affordable Care Act (ACA). The Centers for Medicare and Medicaid Services (CMS) released an Encounter Data Toolkit in November of 2013 to assist states with the operational task of managing the data streams from their MCO contractors. 

While most states are collecting encounter data, many face challenges in assessing the quality of data, and some still lack the confidence in their data to use it for rate setting, quality improvement, or public reporting. Over the past 15 years, Truven Health has helped nearly 20 states with their managed care programs and encounter data quality and completeness. We have assisted agencies with encounter data and managed care at all points of the encounter data process, including plan selection and evaluation, data collection, edit revisions, data quality improvement, and using data for plan management.

Most states choose to collect and process managed care data using their Medicaid management information systems (MMIS), for reasons that include the following:
  • The state can leverage the electronic data collection and translation processes already used for fee-for-service (FFS) claims.
  • The MMIS transaction system allows the state to process managed care data on a record-by-record basis, performing such tasks as editing and shadow pricing using procedures/protocols that are familiar because they are also used for FFS data.  
  • All data are maintained in the same system of record. The managed care data are housed with the FFS service data, which allows the Medicaid agency to incorporate all of the data, as needed and appropriate, in federal and state reports.
However, processing managed care data through the MMIS can also have drawbacks. Other states have experienced such issues as:
  • Delays in implementing new processes for managed care data because of the competing demands from FFS claims processing and associated system change orders.
  • Over-rejection of managed care encounters when edits designed for FFS claims processing are inappropriately applied to managed care records, which have already been adjudicated by the health plan.
  • Delays in the ongoing processing of managed care encounter data because persistent data quality issues cause repeated edit failures. This problem can be exacerbated if processes for resubmitting rejected records aren’t well designed and/or well understood and followed by the plans.
  • Inaccurate use or interpretation of managed care data in reporting and analysis because the nuances of encounter data are not accounted for in standard reports or communicated to users performing ad hoc analysis.
To avoid the above problems, states can either make appropriate adjustments to their MMIS systems and processes to fully accommodate encounter data, or consider other system options. States that are planning to re-procure their MMIS systems in the near future have the additional consideration of how much to invest in the existing MMIS system. This is particularly true for states that are moving to statewide, capitated managed care.

Some states have recently asked Truven Health about collecting encounter data directly from their managed care organizations. States could use their data warehouse decision support system (DW/DSS) to collect and process encounter data as either an interim approach or as a longer term process independent of the MMIS. Factors in support of loading the data directly into the DW/DSS include:
  • The DW/DSS is designed to incorporate managed care data – the data model and analytic reporting applications already anticipate the inclusion of managed care data. The DW/DSS provides a single, integrated repository for FFS and managed care data, capable of supporting transformed Medicaid statistical information systems (T-MSIS) and other federal reporting, as well as state-specific reporting needs.
  • By outsourcing this specialized function to a vendor like Truven Health that is highly experienced with encounter data, a state might help speed the availability of the quality data needed for performance monitoring, rate-setting, and public accountability. 
  • Our experience with the validation of managed care data will also help speed improvements in data integrity and increase credibility of the information.
Specifically, Truven Health’s managed care encounter data services, using the DW/DSS would include:
  • Receiving, processing, and translating managed care encounter data
  • Editing encounter data and providing feedback reports to managed care plans for resubmission
  • Storing encounter data and making it accessible for analysis alone or with FFS data
  • Incorporating encounter data into select federal reports
  • Validating and improving encounter data accuracy and completeness
  • An annual in-depth study of the quality of encounter data and development of a Data Quality Improvement Plan with each managed care organization
As Medicaid agencies turn to MCOs to deal with the tremendous increase in enrollment driven by the ACA, they have a partner in their DW/DSS contractors to implement the best practices outlined in the Encounter Data Toolkit. For more information you can contact me at david.nelson@truvenhealth.com.

David Nelson
Vice President, Market Planning & Strategy

Using Algorithms and Predictive Models to Find Abuse and Fraud


By David Nelson/Monday, April 14, 2014
David Nelson imageA critical success factor in any program integrity effort is applying the appropriate algorithms and predictive models in pre-payment and post-payment claims analysis environments. Truven Health Analytics has experience developing and cataloging hundreds of algorithms which have been used (and are currently used) in various state agency, federal agency, health plan and employer operations to detect abusive and fraudulent claims schemes. We have also seen predictive model intelligence growing in the marketplace, and we are helping payers improve their predictive models so that they more effectively fight fraud and identify high risk claims before the claims are paid. While these sophisticated approaches are implemented to find what we didn’t see before, we also see our clients achieving results every year with some of the tried and true detection algorithms. Each year our expert panel – a team that works with payers across the healthcare spectrum every day – selects a set of key algorithms. We just presented a webinar on the Key Algorithms for 2014, and the presentation included:

  •  A new approach to the overuse of modifiers. We focused on modifiers 22, 24, 57, 76, and 77.
  • The device malfunction algorithm which identifies claims where the reason for treatment or services rendered is due to a malfunctioning implanted device
  • Extended DME rental use
  • Over utilization of diabetic supplies
  • Critical care on date of discharge
  • Advanced life support (ALS) transportation without an inpatient stay
  • Hospital acquired conditions
  • Over utilization of lumbar MRIs
  • Lumbar MRI, post lumbar MRI, or CT
Some of these algorithms represent new schemes we are seeing, and some represent schemes that continue to produce analytic results that PI units and Special Investigation Units (SIUs) can take action on and make recoveries. Our team has produced the Key Algorithms list annually since 2003 to support the healthcare payer community that is dedicated to improving integrity and eliminating fraud, waste, and abuse in healthcare. If you would like more information on algorithms and predictive models, feel free to reach me at david.nelson@truvenhealth.com.

David Nelson
Vice President, Market Planning & Strategy

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