With less than six months left before the October 1, 2015 ICD-10 implementation deadline, there is still time to proactively address some issues that will help guide your organization through the transition. By applying comparative analytics to big data, you can increase transparency into the claims lifecycle so you can better assess the effectiveness of your processes, identify areas needing improvement and begin fixing those issues prior to the deadline.

What to Expect

ICD-10 will have an additional 135,000 codes for documenting a patient’s medical status and reason for a doctor’s visit. Based on the additions of these codes, the Centers for Medicare & Medicaid Services (CMS) predicts that claim error rates will be more than two times higher with ICD-10, reaching a high of 6% to 10% in comparison to the current 3% average using ICD-9 codes. CMS is also predicting that denial rates will rise by 100% to 200% and days in A/R will grow by 20% to 40%.

Leverage Comparative Analytics

Comparative analytics allow you to organize big data to better understand its meaning and gain actionable insights from it. Specific to ICD-10, analytics will increase the level of transparency into your medical claims (837 transactions) and remittance data (835 transactions). With transparency, your organizations can peer into vast amounts of data and extract meaning using an unbiased and consistent methodology. The result is apples-to-apples comparisons of data within your organization and against your peers on a state and national level. This provides you with a baseline to better understand where you stand and the actions that you need to take.

Using comparative analytics, organizations should take the following steps prior to ICD-10 implementation:

  • Create Baselines – Gain a better understanding of your current performance metrics by benchmarking billing staff productivity, claim denial rates and payment turnaround times. You can compare these benchmarks to industry averages that rely on historical data or use comparative analytics to get real-time comparisons against peer organizations.
  • Assess Business Impact – Identify current high-dollar or high-volume diagnoses and procedures, as these will have the most impact on your business when you transition to ICD-10. Determine how coding for these will change with ICD-10.

Other steps to take include:

  • Evaluate Filing Rules – Document timely filing rules for each payer to ensure you don’t get denied for slow staff processing. With the ICD-10 transition expected to increase denials, you’ll want to minimize any denials that are within your control.
  • Scorecards – Work with payers to create a scorecard and a real-time feedback process so impacts can be communicated and resolved quickly.

Post Implementation

After the ICD-10 implementation, use your analytics to establish new benchmarks that you can compare against pre-implementation benchmarks. Identify problem areas and seek solutions to minimize the impact of ICD-10 on your organization.

Questions about Analytics and ICD-10?

Contact RemitDATA to learn more about using analytics with big data to help your organization make a successful transition to ICD-10.

ICD-10 Healthcare Comparative Analytics - Request more info