limitations of traditional approaches leveraging predictive analytics

MethodCare clients that have implemented the charge integrity solution have demonstrated
significant improvements in both charge capture and workflow processes.
With today’s focus on value and quality, the need for healthcare organizations to achieve optimal charge capture
is more important than ever. However, tight budgets, complicated documentation, and ever-changing charge
practices can make capturing every dollar very challenging. Hospitals are especially facing problems in high
dollar areas, such as cardiac, gastrointestinal, and emergency department services, where missed charges can
result in the loss of millions of dollars.
The need to do more with less means hospitals must implement cost-effective solutions that provide the
maximum return. Traditionally, hospitals rely heavily on costly manual review and static, rules-based software
that is not sophisticated enough to identify the greatest revenue opportunity from missed charges or offer the
analytics to assist in proactively curbing revenue leakage. This is because rules-based software:
Does not address a hospital’s specific billing practices
Identifies only the most simplistic binary charge capture issues
Offers broad-based charging assumptions based on high-level trends
The scale of the opportunity for improving charge integrity is significant with the right tools and right intelligence.
MethodCare clients have recaptured as much as $10 million in missed charges in one year by employing a more
sophisticated charge integrity solution.
Clients ranging from community hospitals to large health systems have captured between
$1 million and $10 million annually in missed charges across all departments and patient
types. The solution generates an average ROI of 4 to 1.
The solution’s near real-time reporting analytics has also enabled hospitals to determine
root causes of missed charges, identify opportunities for operational improvements, and
proactively address revenue leakage within clinical departments. Utilizing the solutions
dashboards and reporting analytics health systems have seen a reduction in missed charges
of up to:
70 percent in the emergency department;
60 percent in the cardiac catheterization laboratory;
50 percent in the gastrointestinal laboratory.
Because charging issues can be identified in near real-time, rather than the months after
the system issue was created, the solution has significant applications to baseline charge
practices and ensures that no black holes are created during health information system
upgrades or breakdowns in system interfaces.
Hospitals and health systems have also achieved significant process improvements.
The solution reviews claims nightly on a pre-bill basis, ensuring that claims are sent out
accurately and avoiding additional administrative work required to send a corrected claim.
MethodCare’s cloud-based charge integrity solution leverages predictive analytics to accurately capture every
charge that should appear on a claim. Unlike rules-based tools, MethodCare’s solution relies upon internal
hospital data to identify missed charges. Additionally, the predictive analytic models also identify overcharging
risk, DRG anomalies, and other coding variances.
The solution includes a custom-built model that incorporates a year’s worth of a hospital’s inpatient and
outpatient data, such as diagnosis and procedural codes and patient account and financial information. The
algorithm compares the data in each current claim to the data in the model, predicting what charges should
appear on a claim. The solution then identifies when an anomaly has occurred and a charge that does not
appear on the claim most likely should.
For example, a claim for a spinal fusion procedure that lists an implant(s) may pass the edits of a traditional,
rules-based charge integrity tool. Predictive analytics digs deeper into the data, searching for patterns that
will signal missed charges. If the duration of the procedure was greater than “X” or a specific type of imaging
guidance was used there is a 90 percent chance that another implant was used. Likewise, if the surgeon was
physician A, the likelihood that a specific implant was used rises to 98 percent, but if it was physician B, the
likelihood drops to 30 percent.
Claims with anomalies are flagged, sent to a web-based work list, and reviewed by hospital revenue
integrity staff. The hospital then confirms that the identified charges are properly documented and make the
determination if the charge(s) should be on the claim. If the charge is confirmed, it is added to the claim, and the
claim is sent.
The pre-bill charge capture process also does not add to bill-hold days, which fosters more
timely payment.
The automated process can also streamline the number of staff required to manage charge
integrity issues, enabling clients to capture millions of dollars in missed charges with only
one-half to two FTEs.
Using a tool that is customized to our charge practices, rather than something off the shelf,
has enabled us to more effectively identify missed charges and prevent leaks in revenue,”
says Dave Hennigan, vice president, revenue cycle, Presbyterian Healthcare Services,
Albuquerque. “Even better, the predictive analytics has allowed us to streamline our resources
while protecting our bottom line.
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