Tuesday, January 31, 2023

BAD DATA IS COSTING MEDICAID BILLIONS

MEDICAID DATA TPL THIRD PARTY LIABILITY COB COORDINATION OF BENEFITS SYRTIS SOLUTIONS

Medicaid currently fails at providing a system that efficiently and accurately stores and utilizes member data. As Medicaid is a joint state and federally run program, there are many problems with coordinating data platforms. Different states have their own unique data processing and storing, and while federal Medicaid data can reveal a clearer picture of consistent problems across state lines, lack of communication and data sharing produces significant barriers. While technology has advanced, gaps in existing data or errors in computation have direct consequences to the swift identification of third party liability (TPL), resulting in costly reimbursement strategies for Medicaid. The lack of uniformity in these systems prevents Medicaid from functioning smoothly.

One of the major challenges facing Medicaid is the lack of quality TPL data. In testimony before Congress in 2012, HHS Regional Inspector General Ann Maxwell delivered an alarmingly unfavorable evaluation pertaining to the reliability of data federal and state authorities use to identify overpayments and fraud in the Medicaid program. She stated, "much of the data used to identify improper payments is not current, available, complete, [or] accurate." A decade later, the exact same issues with TPL data that Maxwell outlined in her testimony to congress exist today. Apart from simple mistakes at the point of service with providers, there are fundamental problems in the health care data used by the Medicaid program that result in the loss of literally billions of dollars a year.

STATE DATA ISSUES

Each state Medicaid agency (SMA) is responsible for delegation of funds and detecting TPL through their own data sources. That being said, states have differing policies and benefits for Medicaid enrollees, producing inconsistent results. State policies may have existing gaps in information or may be so complicated that they are virtually impossible to navigate, leading to administration frustration. The Medicaid Management Information System (MMIS) works to centralize information and uses patient identification numbers to help with payment delegation. That being said, because of the large Medicaid population, in addition to continual churn, these datasets can be cumbersome and create missing information that causes difficult identification of TPL. Furthermore, Medicaid information is not communicated across state lines, creating repetitive errors that could be avoided. Health care organizations may share patient data with Medicaid for payment purposes, but the various types of data management could be an issue when trying to translate to Medicaid-specific forms.

FEDERAL DATA ISSUES

While states may send routine reports to federal Medicaid agencies, a working federal database may have a hard time deciphering the varying information from different SMAs. Data can be lost, infrequently collected, or incorrect across state lines. An individual in one state could move to an adjoining state and lose specific Medicaid benefits. Data might only show a small piece of the big picture and can not properly address the nuances of a social program and the problems that persist across states. Federal guidelines may only guide overarching procedures, and not have control over individual states' Medicaid programs and policies. This disjunction of administration proves difficult when trying to accurately find TPL data for not only individuals, but also states and federal overview.

Data sharing is therefore an efficient and effective way to decrease the number of inconsistencies between states and local organizations that require Medicaid payment. Nevertheless, a slew of issues stem from data sharing in totality. Even within states, health care organizations are hesitant to share patient data. Sacred protected health information (PHI) delegates immense responsibility to hospitals, providers, and care coordinators to handle data cautiously. Even if organizations are willing to share patient data, unique technology systems across health care do not always capture the same data or translate it in the same way. SMAs are responsible to intake this information and identify TPL, which increases difficulty when trying to smooth operations. This reluctance to share information translates to state and federal Medicaid agency issues. Sharing large amounts of diverse data has been troublesome and leads to inconsistent data and high costs to the Medicaid program.

For years Medicaid has struggled to effectively store and utilize program beneficiary data due to disparate data platforms and the inability to accurately share Medicaid data between states and the federal government. Moreover, much of the healthcare data that Medicaid plans do have access to is leading to billions of dollars in improper payments each year. Without having reliable, complete, and accurate TPL data, Medicaid plans will continue to make claims payments in error and rely on costly reimbursement strategies. Plan administrators must look to true TPL technology solutions for additional efficiency and cost avoidance opportunities to protect the program's valuable resources and ensure that plan members receive the care they need.


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Friday, January 6, 2023

MEDICAID NEWS FROM 2022

2022 MEDICAID - A YEAR IN REVIEW SYRTIS SOLUTIONS

Syrtis Solutions publishes an annual Medicaid summary to help you stay informed. The yearly roundup concentrates on highlights, analysis, and legislation that pertains to Medicaid program integrity, cost avoidance, coordination of benefits, third party liability, improper payments, fraud, waste, and abuse. Below is a summary of 2022's Medicaid developments.

Thursday, January 5, 2023

DECEMBER MEDICAID NEWS

 

Syrtis Solutions sends out a monthly Medicaid news summary to help you stay informed. The monthly summary focuses on developments, analysis, and legislation that relates to Medicaid integrity, cost avoidance, coordination of benefits, third party liability, improper payments, fraud, waste, and abuse. Below is a list of last month's important Medicaid news.