Leveraging Comparative Analytics
Helping payers control healthcare costs through greater transparency
By Brad Hill, Vice President of Payer Solutions, RemitDATA
Payers who believe big data provides all the answers they need to establish competitive pricing are only getting half the picture. Comparative analytics take big data to a new level, allowing payers to achieve reduced costs by providing pricing transparency.
Many organizations believe they already have an analytics solution. However, the missing piece is often the comparative component. Comparative analytics offer the ability to help lower the medical cost of care, enhance member engagement and reduce administrative costs. As a result, payers have the data they need to help reduce their medical cost of healthcare by enabling their members to compare pricing in the ever-changing healthcare services market-delivering information that patients otherwise would not have.
Click here to read more.
And here we are, six months into the ICD-10 conversion. While the headlines continue to trumpet “all is quiet” what is the real story?
We thought it would be interesting to take a look at this six-month period and compare it to a year ago. Below is a snapshot of our data for the last six months (Oct. 1, 2015 – March 31, 2016), which we compared to the same six-month period from the previous year (Oct. 1, 2014 – March 31, 2015) – the results are quite interesting:
- By Type of Service Level I, denial rates appear to be down slightly.
- Processing times are down.
- And claims appear to be getting paid faster.
What we can conclude is that yes – all continues to be quiet with no major issues on the ICD-10 front. But the story that isn’t being told is that denial rates and processing times are down, and claims are getting out the door faster – which we would chalk up to being an overall improvement post-ICD-10.
What remains to be seen is how those may or may not change in October 2016, when the grace period ends. Stay tuned!
WANT TO SEE HOW COMPARATIVE ANALYTICS CAN HELP YOUR BUSINESS?
Coming Soon: TITAN Filter Library is becoming Report Controls
The Filter Library – located on the left side-panel – will now be the Report Controls. The Report Controls Center is more comprehensive and houses both the Report Lens and the Filter Library.
The new design will simplify the user experience and save time.
- The user will be able to select all criteria at once versus making one selection at a time.
- All controls and filters will be centralized to one location.
In addition, users will experience the following updates in the new design:
The Apply Button, will now be Apply Selections.
- The Apply button will be relocated to the top of Report Controls section and renamed Apply Selections.
- As with the previous Apply button, Apply Selections will only be active when a change is made within the Report Controls. This includes any change to Dimension, Date Type, Timeframe or Frequency – in addition to any added filters.
- Once selected, Apply Selections will retrieve the chosen criteria and refresh the report data.
- Apply Saved Filter Set will still immediately apply the saved filter criteria and refresh the report data.
- Clear All Filters will be removed from the Apply Saved Filter Set wrench and made its own button. It will remain inactive until filters have been added or applied.
- Selecting Clear All Filters will remove the filter criteria but not refresh the report data until Apply Selections has been selected.
- Selecting Clear All Filters will not refresh the Filter Category filter counts until Apply Selections is selected.
Fear a RAC audit? Reduce your risk with comparative analytics
If the words “audit” make you break out in a cold sweat, we have good news. You can minimize your risk for a RAC audit by being proactive, knowing what can trigger an audit, knowing what the market is looking for, and digging into your organization’s data and comparing it to your peers to see if you are an outlier. Leveraging comparative analytics is the best place to start.
The best place to begin is with research of your internal data to determine what may trigger an audit. Research and identify ways to increase the transparency of your historical claims data. Comparative analytics can help you analyze large amounts of data to pinpoint potential problems so corrective action and preventative action can be prioritized based on risk.
To learn more about using comparative analytics to help reduce your chance of an RAC audit, check out our article in ADVANCE for Health Information Professionals, or contact us!
Revenue Cycle Management: What to Consider as You Prepare for Alternative Payment Models
Ensure you have clear insight into your practice’s financial picture
The healthcare payments shift away from fee for service to value-based payment models are showing great promise. However, to adopt these new payment models, providers need to take a close look at their businesses, beyond just looking at the bottom line. The best way to obtain a complete financial picture is through comparative analytics. Quality data can help uncover information such as which costs can be controlled, which payers have the highest denials, which claims are being rejected altogether, and other valuable insights.
To best prepare for shifting payment models, practices need to have a clear understanding of their financial picture, and consider the impact an emerging payment model agreement will have on your practice.
The American Medical Association’s “Evaluating and Negotiating Emerging Payment Options” (2012) provides some practical tips and resources that practices should consider as they evaluate proposals, negotiate agreements and manage the revenue cycle associated with a specific payment model. Robert Barbour’s chapter, “How to establish baseline costs,” offers some excellent recommendations and steps on where to begin.
Points to consider:
- Establish baseline costs and know your true costs of conducting business. As you consider risk-based payment models, your practice may require more sophisticated accounting practices than are required under fee-for-service. Be sure to calculate your true cost of doing business as your baseline for assuming risk.
- Analyze your practice’s revenue cycle. Analyze service costs and reimbursements for each, to determine if you are in-line with your peers.
- By payer, determine whether there are issues in reimbursement for specific payers or if the problem is broader in nature. For example: was there a sudden drop-off in payments from a specific payer? Looking at the data can help solve that mystery.
- Capture data analysis for practice improvement. With emerging payment models, practices not only will need staff with expertise in evaluating data, but also with knowledge in how to make business adjustments necessary to keep the practice profitable. For example, if your costs are exceeding your reimbursements, you’ll need data to prove to payers that your costs cannot be further reduced, reporting that proves your practice is meeting quality and outcome requirements, and potentially reasons for cost discrepancies in what the payer is willing to pay, and what your practice can accept.
Healthcare comparative analytics can help analyze your practice’s financial health by providing insights into how your practice compares to your peers. Do you have a higher percentage of denied claims for a specific service than your peers? Ensuring your business finances are in-line will help ensure success for new payment models. As you consider alternative payment models presented to your practice by payers, take a close look at each, and compare with your revenue cycle to determine whether you can afford to participate in a specific payment program.
Alternative Payment Models: What’s Next?
We hear story after story about patients receiving financially devastating medical bills. If only they knew how much the cost of a procedure can vary, perhaps they could make a more informed decision.
Unfortunately, it’s not that simple. Part of the problem has been traditional fee for service pricing models. Factor in complex payer/provider contract rates and little transparency or consistency from patient to patient, and you have a recipe for potential financial disaster.
With the Affordable Care Act targeting how healthcare is organized, delivered, and paid for, alternative payment models are taking shape – including bundled pricing. As payers begin to invest in implementing more bundled payment initiatives, comparative analytics can help guide them toward the greatest opportunities to impact cost of care. By examining historical claims data, payers can identify their highest volume and highest cost procedures (grouped by episode of care) to establish actual prices. By applying these pricing methodologies, payers can reduce costs with a consumer-driven model that focuses on value-based choices.
Learn more about the future of alternative payment models and what is in store on EMR & EHR’s website.
ICD-10: A Look at Payer Processing Time
As we keep an eye on what the data is revealing, this month we’ll take a look at how payers are doing since the transition to ICD-10.
Our data is showing the national average for payer processing time is 13 days. State-by-state, our data is showing:
- 18 states have payers with processing times longer than the national average
- 20 states that are equal to the national average
- 12 states have payers with processing times shorter than the national average
As we examine denial rates, we are definitely seeing an upward tick in denials across the board between mid-January 2016 and mid-March 2016. Payers also are beginning to take longer to pay claims, as the data reveals below for each:
Evaluating Payment Velocity for Q4 2015
Be sure to check back in April, as we will look at Q1 2016 compared to Q4 2015 statistics.