The Powerful Combo of BI Solutions and Comparative Analytics

We are lucky to be operating in a world where data and intelligence are readily available…at our fingertips. It makes all of us more accountable, and gives us the ability to deliver reliable results to healthcare organizations looking for ways to be more profitable and more productive.

That said, there are two types of data solutions that can help you define your future:

  1. Business Intelligence Solutions
  2. Comparative Data Solutions.

Although the differences might seem subtle, it is important to understand those differences.  An organization needs to ensure that their BI solution has comparative analytics and/or can align with a comparative analytics solution.

To be clear, Business Intelligence (BI) is a term that encompasses all knowledge we seek – current and historical business data that helps you to achieve a solid outlook.

Comparative analytics takes business intelligence to another level, building upon the concept of BI, taking data a step further by enabling an organization to compare the performance of their data to that of their peers.

Combine the two and… begin to define the future of your organization.

Read the full story to see for yourself.

Denials Management: How to Create an Action Plan with Comparative Analytics

Does your denial management plan provide you the necessary data to work through the root cause?

Author: Amber Civitarese & Stacie Bon

It’s a common problem seen in practices nationwide: the billing department sees an uptick in denials. The billing manager expresses concern to the clinic manager, who provides what he or she feels is the root cause for these denials. The billing manager chases down what they believe is the solution, only to realize months later that what they “thought” was causing the bulk of denials is in fact only a minor issue and not the driving reason at all. Their “root cause” was based on guesswork, and the reason for the high denials remains a mystery.

Claim denials are one of the largest areas of lost revenue for healthcare organizations. Nationally, U.S. hospitals lost approximately $42.8 billion in uncompensated care – care provided for which no payment is received – in 2014, according to Health Forum, AHA Annual Survey Data, 1990-2014, January 2016 update.

Implementing a denial management process

The first step in implementing a denial management process is to assess the causes and evaluate trends in denials. For example, perhaps claims sent to a specific insurer are frequently denied, or a particular diagnosis code is causing a high denial rate.

To get to the root cause of denial issues, practices need to implement a denial management process that leverages comparative data to reveal the true reasons for denials. Key points to consider include:

  • Managing high-cost claims associated with high dollar procedures
  • Evaluating time spent on high-volume denials, including reworked claims that per claim are not expensive, but drain resources while working to resolve
  • Identify hidden cost denials – billing for procedures that the practice expects to be denied and will never appeal the denial, and as a result, consistently inflate their A/R
  • The ability to identify trends in payer denials, including implementing a simple method for tracking and monitoring payer denials
  • Implementing a simple process for sharing payer denial trends data with your payer provider rep to resolve denials that may be occurring due to incorrect processing on the payer side

Leveraging healthcare comparative data can help you establish benchmarks and baseline standards needed to create a denial management plan. Comparative analytics can track denial trends to identify problem areas and develop corrective actions. For example: are claims being submitted with the correct code? Is the front office staff billing properly? Without good data, any potential resolutions are based solely on guesswork.

Here is a step-by-step guide that can be useful in implementing a denial management plan:

Step 1:  Identify claims that are taking longer to be paid due to an increase in denials.

Step 2:  Compare the denial rate year over year.

Step 3:  Trend denials by reason code and specialty compared to state and national averages. For example, if top denials are all related to eligibility, work with staff to determine what part of the process is breaking down.  Confirm employees are checking eligibility during patient registration or prior to. Depending on your process, your practice might benefit from purchasing a tool to assist in automated eligibility checks.

Step 4:  Evaluate high volume or high dollar procedures, evaluating key areas such as length of time to process a claim, whether or not that time is increasing, and how it compares to state and national averages.  After evaluating the data, if you find delays in getting claims posted in the PM system, look at other business processes to determine reasons for the delays.

Step 5:  Check the average time it takes for payers to process your claims.  If the average time is increasing, review your data against state and national averages to determine if others are experiencing the same spike. 

Step 6:  Prioritize issues based on the greatest ROI and review workflow to ensure best practices are implemented and followed. 

And, on an ongoing basis:

  • Make denials management a team effort between your billing departments, front desk and coders/physicians.
  • Ensure your team is communicating clearly, and work with the front line staff to help them manage denials by providing them with relevant data to help manage denials.
  • Be sure your billing department is approaching the front desk and coders with an action plan that contains relevant data and identifies next steps.
  • Schedule a meeting, create a joint solution and monitor the outcome as a cohesive team.

While the reasons for claim denials can vary, being proactive in implementing a claim denials management process that leverages actual data instead of guesswork can save your practice millions of dollars in otherwise lost revenue.

This Article was first published in Billing, the Journal of the Healthcare Billing and Management Association, Vol. 21, May 2016.

ICD-10: June Year-Over-Year Report

While we presented the mid-year report card which included June 2016 data based on date of service, we thought it ICD-10 Healthcare Comparative Analytics - Request more info
would be interesting to compare June 2016 with stats from one year ago, based on check date. This will illustrate
how the industry is doing based on claims processed in June. Here’s what we found:

In almost every category – from DME to procedures and imaging – the denial rates were down from June 2015.
July_2016_ICD_Service_level_RemitDATA_Comparative Analytics

Processing time: this category was especially of interest, as our data is reflecting an overall reduction in staff processing time.
Payers are processing claims 3 days slower this year than in 2015, but staff processing time is 5 days faster.
In almost every category – from DME to procedures and imaging – the denial rates were down from June 2015.      
July_2016_ICD_processing_RemitDATA_Comparative Analytics

Remittance velocity: Another interesting find, in that claims are being paid faster during June 2016 than during June 2015
– with only 16.3% reaching into the 61+ category.
July_2016_ICD_remittance_RemitDATA_Comparative Analytics

The data continues to be of interest, as one would assume ICD-10 to slow things down.
But, important to note that the year isn’t over yet and claims are still rolling in.
We’ll continue to monitor the data, check back again soon.


Revenue Cycle Management is a Top Challenge for Healthcare Practices

Data is our business. Well, it’s the focal point of our business. We believe data, whether primary research focused, aggregated or anecdotal helps any business make empowered business decisions.

Naturally, we look to data to inform our own business, which is why the survey we conducted among providers, RCM companies and healthcare vendors was so beneficial.

From that survey, we were able to aggregate and report some key findings on the four biggest concerns among healthcare organizations. For example, nearly half of providers (41 percent) cited acquiring new patients and competition as a top concern. More than 50 percent of RCM companies and vendors reported acquiring new customers as a top challenge.

Want to know more? Becker’s Hospital CFO published an article on these key findings from our survey. To learn more, click here.

NEW Claim Level Detail Reports in TITAN

It is a common practice among health plans to review claim level detail when working with 835 data. Providers can now get this same level of information straight from the 835 file, and get a complete view of claim level detail and related adjudication information.

We are proud to announce that this new capability is now available in TITAN!

Here is the low down:

Currently in TITAN, all metrics are based on service line detail. With the addition of claim level detail, you now have access to more metrics along with the service line information you have become accustom to monitoring.

New Reports Based on 835 Metrics include: 

  • Average Claim Processing Time Analysis: Analyze claim counts vs. service line counts to track patterns and reveal issuesClaim Average Processing Time Analysis
  • Claim Denial Analysis – Identify and track denial trends at the claim levelClaim Denial AnalysisClaim Denail Analysis 2
  • Claim Dollar Overview – Determine which payers have the highest or lowest billed amount per claimClaim Dollar Review

These new claim level reports give you access to the following features.

  • New filters including: claim status and claim filing indicator
  • New query logic, such as claim status, enables more clarity and insights
  • Expanded comparative capabilities via 835 database
  • Review overall claim volume and/or dollar totalsReview Your Overall Totals
  • Analyze claim status breakdown by payer
    Analyze a breakdown by Payer
  • View a report of service claim details with service line detailsSee Claim Level Details from the 835 combined with the service line details

If you are a TITAN user, we encourage you to contact us with any questions you might have.

If you are not currently using TITAN, click here so we can show you how healthcare comparative data could help improve your revenue cycle.

RemitDATA’s New Knowledge Center: Tools to Help Solve Your Business Challenges

As a medical practice, chances are you’ve experienced spikes in certain claim denials with very little insight into the root cause. Right?

As a billing company, perhaps your clients need you to pull reimbursement tracking information TODAY, but your systems can’t pull it quickly enough to satisfy. Been there?

And Payers, is it possible that quick data insights might help you better control costs more accurately during the pre-authorization phase – so you have the wherewithal to inform in network surgeons about the huge cost variances within their contracted facilities – redirect surgeons and help your members  lower costs, at high quality locations?

From managing claim denials to navigating the Affordable Care Act, payers, providers, and billing companies alike need help navigating the healthcare ecosystem to ensure a healthy bottom line.

RemitDATA is responding to your needs with information and news you can use. Our new Knowledge Center gives you access to case studies, videos, white papers, webinars, podcasts and more. Access these resources  to better understand how your peers are solving some of their business challenges and how you can do the same.

You’ll find:

  • Use cases from current TITAN users, who share their challenges and solutions to help save time, reduce frustration and improve business operations.
  • Best practices and tips through white papers, webinars, podcasts, and videos.
  • Valuable insights and data from RemitDATA experts.
  • And other critical information.

For access, visit

ICD-10: 2016 Mid-Year Report

Good news on the ICD-10 front, the data continues to reveal a decrease in claims processing and payment times.

At the mid-year mark, our data is reflecting a steady decrease in claims processing and payment velocity. Reviewing average processing time from January 2016 through mid-June 2016, we are noting that:

  • Average staff processing time has shown a steady decrease during the year, with average staff processing time in January of 17 days to an average of 8 days in May.
  • Average payer processing time has decreased throughout the year, with an average of 15 days in January to 12 days in May.
  • Total claims processing time was reduced by nearly 60%, with total processing time of 32 days in January to 12 days in June.

 Processing Time ICD-10 June Blog

Payment velocity data also reveals excellent news for providers: as of June, our data is reflecting that on average nearly 80% of all claims are being paid within 30 days.

Remittance Velocity ICD-10 Blog June

However, denial rates are holding relatively steady. June denial rates are 1% less than January.

Denial Rate ICD-10 Blog June

It’s important to note that claims are still rolling in, especially for May and June, so the numbers may vary, though we don’t expect any major changes. As we move closer to October 2016, when the expected grace period for specificity on ICD-10 codes ends, will the data show huge shifts? Or, will we see the data continue to stay steady?

We will continue to monitor the data as October approaches. Stay tuned.

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