The time has come. ICD-10 is here. Your months and years of ICD-10 preparation will now be put to the test. It is time to stop anticipating ICD-10 and start tracking its impact on your revenue.
Across the country, hospital executives fear the effects of ICD-10 on their revenue, and for good reason. The Centers for Medicare and Medicaid Services (CMS) predicts that hospitals and health systems could see payments decline for up to two years after ICD-10 takes effect.
It doesn’t end there. CMS predicts that:
- Denials could increase by 200%
- Accounts receivables could rise to 40%
- Claim error rates could grow 10%
But you don’t need to go it alone. Data analytics can shine a light on your ICD-10 efforts and help you approach it with confidence. Our advanced analytics enable you to measure, monitor, and benchmark the impact of ICD-10 so you can identify outliers, prevent denials, and protect your bottom line.
Follow these top five tips as you track your ICD-10 performance with data analytics:
Tip #1: Trend and benchmark CMI, unspecified code usage, and secondary diagnosis codes.
Let your data show you how your ICD-10 performance compares to your peers. Say 90% of your peers are coding for a particular secondary diagnosis code but you are not. Understand why that is and take steps to rectify the problem.
Tip #2: Reduce denials by identifying their trends and causes.
It’s a fact. Denials will increase after ICD-10 takes effect. But you can take control over them now, before they pose significant risk to your revenue. When you identify the trends and causes of documentation and coding denials, you can spot where your ICD-10 coding efforts may be going wrong and what you can do to help ensure your claims get paid.
Tip #3: Identify required specificity missing from physician documentation.
ICD-10 is all about specificity. Your physician documentation needs to be specific to make sure you are paid for the complexity of care you provide. Unlike some analytics solutions, our proprietary ICD-10 analysis can identify which documentation concepts are missing and causing a lower level of specificity.
Tip #4: Track coding and billing efficiency trends.
CMS predicts that your accounts receivables will rise. Let your data identify where any bottlenecks may exist in coding and billing. Discover and resolve these bottlenecks to reduce their impact on your revenue.
Tip #5: Mitigate compliance risk related to ICD-10.
Your compliance department must remain diligent after ICD-10 takes effect. ICD-10 will magnify the potential for documentation and coding compliance issues. Let our compliance risk rules engine scan your claims on a daily basis so you can identify potential ICD-10 audit targets and areas of risk.
For more information about how MedeAnalytics can help you measure, monitor, and benchmark the impact of ICD-10 on your revenue, visit www.medeanalytics.com/revenue-integrity or contact us at info@medeanalytics.com.
Be sure to visit us at AHIMA, booth #1443, September 26-30. To schedule a private demonstration, email Katie.Broussard@medeanalytics.com.
Get our take on industry trends
Why It’s Time for Healthcare to Move Toward AI Reporting
Business intelligence (BI) was a dramatic and significant step forward in healthcare industry reporting and a natural transition to artificial intelligence (AI) enabled real-time insights.
Read on...Why Healthcare Should “Double-Down” on Exploring AI-powered BI for Reporting
Many areas in healthcare rely not only on the collection of data but, importantly, the ability to decipher and act upon it. In that intersection, reporting was born.
Read on...Why Health Plans and Employers Need Stop Loss Reporting
Due to rising healthcare costs and the Affordable Care Act removing the ban on capitated benefits coverage, numerous employers with self-insured health plans often purchase stop loss coverage. This coverage is not medical insurance; but rather, it’s a financial and risk management tool that protects the employer from excessive claims.
Read on...Bridge the Payer/Provider Data Gap
Every patient has a plethora of data associated with their health record, which can include decades of enrollments, claims, accounts and charges. Much of this data is not housed within the same institutional, facility or provider database…
Read on...