Drilling down into ICD-10 data

The deadline healthcare providers anticipated with a mixture of dread and grim determination has passed. The Centers for Medicare and Medicaid (CMS) now requires that you use ICD-10 diagnostic coding for claims submissions.

Some healthcare organizations  prepared for months to make the transition,  while others scrambled at the last moment and hope for the best. Whatever their level of readiness, U.S. healthcare providers now are living in an ICD-10 world, and it is critical to their revenue cycles that they uncover and fix problems that could lead to claims delays and denials.

The Centers for Medicare and Medicaid Services (CMS) has predicted that ICD-10 could have a negative effect on healthcare provider revenue for up to two years, with denial rates doubling or tripling, accounts receivables increasing 20% to 40%, and claim error rates climbing 6% to 10%.

The best way for providers to assess the impact of ICD-10 assessment is to figure out what information they need before collecting data. Among the questions to ask in your organization are:

·      How do we separate our problems from payers’?

·      Can we quickly find ICD-10 process problems by department?

·      Can we quickly identify patterns to avoid denials?

The answer to these and other questions resides in the data that providers compile and analyze. Specifically, providers should focus on top denials, claims edit analyses, reimbursement trends, and payer performance. Drilling down into this data can help trace errors that impact the revenue cycle back to the source – a particular clinician, coder, code or procedure.

The process of analyzing the effect of ICD-10 on a healthcare provider’s revenue cycle should be ongoing. The hospitals and practices that likely will be most successful at limiting the negative impact of ICD-10 on billing, claims and revenue are those that 1) invested the most time and resources into preparation for the transition, and 2) are experienced in using data analytics.

For example, in the graphic above, analytics is used to identify the specific group in a cardiology department responsible for a disproportionate percentage of errors, along with an estimate of the opportunity cost.

Unfortunately, healthcare providers with analytics expertise are in the minority.

Nearly two-thirds of providers (66.3%) responding to a 2014 HIStalk poll report doing little to “use available data to make improvements” to their revenue cycles. For these providers, adapting to ICD-10 will be an even greater challenge.

Still, it’s never too late – until it is. Healthcare providers not fully prepared lacking analytics experience still can get back into the game. But they need a clear strategy, an understanding of what to look for, and the right tools to overcome the revenue challenges of ICD-10.

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