Processing times, denial rates, cash flow and alternative payment models — all just a few of the many business challenges healthcare organizations face. As providers identify areas in which to focus their efforts and maximize performance, a growing number are investing in business intelligence (BI) solutions featuring comparative analytics. These solutions help organizations identify areas of the business in which improvements will offer the greatest ROI.
As organizations evaluate analytics solutions, we’re offering some insight into how BI and comparative analytics solutions compare, and how providers can leverage each to solve business challenges.
Business Intelligence (BI) Solutions
BI solutions take a historic view of data, and typically focus on a consistent set of metrics to measure past performance against what an organization is experiencing today and leverage this information to guide business planning.
BI solutions consist of querying, reporting, and Online Analytical Processing (OLAP) to provide an inside look into scenarios that help uncover what happened and how often. BI solutions allow organizations to collect, maintain, and organize data to help identify insights and key metrics, such as key performance indicators (KPIs).
Common uses of BI solutions include measuring accounts receivable (A/R) days, assessing internal performance metrics, measuring payer payment turnaround rates, evaluating cost measures, reviewing patient prescription adherence, as well as monitoring clinical pathway compliance.
Comparative Analytics Solutions
Comparative analytics solutions build 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. This added level of information helps organizations better understand the performance of their business, create reasonable benchmarks, and prioritize initiatives based on potential ROI.
In addition to enhancing the KPIs presented by traditional BI solutions, common uses of comparative analytics solutions include measuring reimbursement rates against benchmarked data and the use of real-time data to benchmark against peer indicators. A few key areas to monitor include:
- claim denial rates
- denial reasons
- deviations in coding and claim types
- staff productivity
- payer performance
More timely data enables more accurate comparisons that reflect what is happening in real-time, so it can be corrected or modified immediately, before any negative financial impact is realized.
Here are a few scenarios in which providers leveraged comparative analytics to help improve business performance:
Tracking Denials by Payer Group
Providers spend hours working through denials received from their payers. Oftentimes they lack the ability to identify why denials are occurring or which payers are denying which procedures.
To truly understand what is occurring providers need solutions that allow them to drill down further into the data to help them resolve and prevent denials.
For example, a provider received numerous claim denials from their Medicaid payer with a claim adjudication reason code of CO4. The provider needed to resubmit the claims within a set time period with the correct modifier in order to be reimbursed.
Leveraging comparative healthcare analytics, the provider created a report identifying all denials by payer within a specific time period. They were able to filter the denials by the CO4 adjustment code and realized that their peers were also experiencing the same denials.
These solutions allowed the provider to promptly identify key data points to determine how often specific service lines are being returned, whether the volume of denials is increasing or decreasing and if their peers are seeing the same denial trends.
Uncovering Spikes in Denials or Billing Patterns
A provider experienced a spike in denial rates – this is not uncommon. In these instances, the provider needed the ability to identify whether the spike was only occurring within their practice or if their peers were also experiencing the same spikes. The provider also needed to determine if the same spikes occurred in previous years.
Comparative analytics can help a provider better understand denial spikes and begin to address them based on the level of priority and ROI.
In this specific example, the provider was able to trend billed service lines by payer group to identify and reduce spikes in billing and denials. This level of data allowed the provider to identify spikes in the number of lines billed and/or the number of lines denied – enabling them to resolve any potential issues more quickly.
Leveraging comparative analytics, the provider created an overview to show the total number of service lines returned over the last 12 months and trend against their own data for the previous 12 months, while also comparing the previous years’ data to peers in the same specialty.
The Future with Business Intelligence and Comparative Analytics
The future of healthcare organizations depends on how effectively they can quickly measure, compare/interpret and resolve issues within their revenue cycle data. Providers are dealing with changing regulations, and the need to access data in real-time is here to stay. BI solutions with comparative analytics allow providers access to the data they need to identify outliers, create KPIs and prioritize initiatives to improve operations while giving them the time back to deliver quality patient care.
Want to learn more about using comparative analytics to improve your healthcare business? Check out our webinar, Driving Performance Improvement with Comparative Analytics.