Cash Flow Forecasting and Collections Performance
The ability to forecast cash flow and collections performance is vital to any medical practice. Yet many practices don’t realize they have valuable data at their disposal to improve these processes and increase revenue. Much as Dorothy in The Wizard of Oz realized that happiness lies in her own backyard, the key to success for many practices is to understand how to target and mine their own data and use it to their best advantage. That is why new and dramatically effective collections and performance models are helping to lift the industry out of its “the way we’ve always done it” mindset.
Start with three essentials
At the highest level, forecasting and performance improvements require data about three essential elements of your practice’s billing landscape: 1) your historic Net Collection Ratios (NCRs), 2) the lag time between billing and payment, and 3) the percentage of collections that are insurance vs. private pay. Yet these “buckets” of information are just the beginning to effective collections forecasting and performance. Within each of these three essentials, you should also go from macro-view to a more detailed picture by extracting information about:
- Facility mix—e.g., hospitals vs. imaging centers
- Payer mix
- Place of service mix—inpatient, outpatient, ER
- Demographic zip code analysis
Once you have this data extracted to determine your practice’s unique profile, you can then apply the information to help you to better project cash flows and budget estimates based on growth and collection trends. The information can also go a long way to help you build more effective marketing strategies. Let’s take a look at two ways you can “slice and dice” your data and the applications that are delivering value to successful medical practices today.
View #1: Collections-Payment differential by zip code
Examining your NCRs, your lag times and your insurance/private pay ratios by zip code can reveal much about your practice and impact your strategies to enhance collections performance. For example, you may find particular insurance carriers are more prevalent in one zip code than another—carriers that historically have performed better for you than others. Or you may find a carrier behaves differently in a certain zip code because the employers in that area have better contracts with it. Or maybe a certain zip code houses a major retirement community whose residents are more likely to need your services and more likely to be Medicare patients.
The results of your zip code data analysis might look like this:
- ER Self-Pay Patient in Zip Code XXXX1 – NCR = 6.5%
- ER Self-Pay Patient in Zip Code XXXX2 – NCR = 10.4%
- ER Self-Pay Patient in Zip Code XXXX3 – NCR = 26.1%
- BCBS Inpatient - Patient Portion – in Zip Code XXXX1 – NCR = 23.7%
- BCBS Inpatient - Patient Portion – in Zip Code XXXX2 – NCR = 31.2%
- BCBS Inpatient - Patient Portion – in Zip Code XXXX3 – NCR = 45.9%
A zip code footprint analysis can make all the difference in how you forecast and how you build strategies and methods to improve collections performance in every area of your practice—and that includes your marketing efforts. For example, where do you put your next billboard for the optimum effect? Where do you build a new imaging center? What local businesses do you market your services to? How do you draw more patients from the zip codes that historically have performed better for you?
View #2: Collections-Place of service mix
Your place of service mix is also an important area to examine for improving your forecasting and collections processes. For example, if you find a high percentage of your business is in the ER, then you can utilize your data to work with hospitals in educating ER physicians on what types of tests are appropriate to order and for what reason. Denials by CPT code and referring physician is a particularly useful analysis in communicating possible problem “areas.” This can go a long way to decrease your denial rates and ensure your payment rates for ER services are as high as the inpatient and outpatient areas of your practice. The same thought processes would apply to inpatient work and office work.
Knowing what all of your practice mixes are, and how they are changing is critical in reconciling performance variations from period to period to identify areas of strength and of course, areas that need improvement.
Your profile is constantly changing
Through the ongoing use of data mining approaches like those described here, your practice can gain a better understanding of specific payers and specific markets—and how those payers and markets keep changing. For example, payer and patient lag times and NCRs evolve over time with new technology and changes in economic conditions. As insurance and patient responsibility ratios shift, your own forecasting models will need to evolve, as well.
The industry will continue to change, but one thing will remain constant: Data will always be of the utmost importance. By leveraging the latest data mining and analysis capabilities, your practice can stay ahead of the curve.
Additional Resources on Collections
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