Getting the Most Out of Benchmarking and Key Performance Indicators (KPIs)

With the ever-growing financial challenges that all healthcare organizations now face, how can the various performance indicators be best utilized to increase cash flow, reduce bad-debt charge-offs and improve overall revenue cycle performance? Although there are many factors and undertakings that may be needed within an organization to get the revenue cycle to peak performance (technology needs, training needs, payer relationships, employee incentive programs, etc.), the ongoing need for increased / financial class specific benchmarking data will increase as operating margins decrease.

For example, payers that make up a very small percentage of total gross patient revenue may not be getting analyzed and evaluated like larger payers; however, there could be significant dollars in lost recovery within these smaller payer groups affecting the revenue cycle. Even HARA (the benchmark in hospital receivables) doesn’t break out payers such as workers compensation, Tricare or motor vehicle claims into their own financial class. With less and less resources available, there is no longer the luxury available to only look at some areas of the revenue cycle. More benchmarking and utilization of additional key performance indicators (KPIs) to help identify areas that need improvement, along with the ability to drill-down into these identified problem areas may be necessary to design effective solutions to get and keep the revenue cycle at peak performance.

KEY PERFORMANCE INDICATORS

Days in A/R

With technology increasing, along with the higher volumes of data available, benchmarking and KPIs shouldn’t only be looked at as a tool for financial performance improvement, but also for process performance improvement. As we analyze different KPIs, we may find that our organization is not performing at best-practice standards due to process and operational changes needed. For example, if our overall A/R days are higher than our peers, we need to know the specifics on what is causing that problem. We may find out that our A/R days are out of line primarily due to not having an electronic exchange with a specific payer whose volume has grown over the past year. This is why it is necessary to look not just at overall A/R days, but A/R days by payer class. An organizations’ overall A/R days may look fine, but that may be due to a much higher Medicare mix, or a lower self-pay population than their peers. We need to be looking at all payers to establish key performance indicators for each payer type to make sure we are operating as closely to best practice standards for all of them, not just in aggregate. Once we know what the benchmark should be for each payer, we can then quickly identify areas that may need attention, and also monitor ongoing performance.

Payer Mix

As mentioned previously, knowing the breakdown of where an organization’s revenue is coming from, how a change in mix will effect overall A/R days, having KPIs for each payer type, and then utilizing those KPIs to identify trends can help improve or maintain optimal performance. For example, if your commercial payer gross A/R days average around 60 days, and then slowly starts growing, you are now alerted that a problem is developing within this payer class rather than just identifying that overall days are growing. If you only looked at overall A/R days, your growing commercial A/R days may not be recognized due to another payer class performing better than normal, thus offsetting gross A/R days in aggregate. By recognizing trends and developing problems early in the cycle, the identification of the specific causes can be addressed and dealt with as soon as possible. With the advent of Consumer Directed Health Plans, self-pay days may start to grow for many organizations; thus, affecting cash-flow, bad-debt, outsourcing, etc. However, by recognizing this trend early in the cycle, and by having KPIs for this payer group, action can be taken tailored specifically to the self pay group.

Cost to Collect

The Hospital Accounts Receivable Analysis (HARA) reports healthcare organizations’ cost to collect by bed size, geographic location, geographic settings, etc. However, it does not report cost to collect by payer group. Since this number is an aggregate across all payer mixes, it makes it difficult to recognize what is causing the cost increases or decreases driving this aggregate number. Most organizations agree that it is less costly to process a Medicare claim than a self-pay claim for a variety of reasons, but how can they recognize that cost to collect may be increasing due to complex payer contracts or more tools needed to manage the contract (contract management software, additional staff, etc.) from an aggregate number? Without being able to drill-down the cost to collect by payer, making informed decisions becomes more difficult. By looking at cost to collect by financial class, we may spot a trend — identifying growing costs in a specific area. For example, if we have set a best practice cost to collect number for our commercial payer financial class, and then notice that it has started to grow, we can now drill down to find out what has caused it to grow. We may identify that a certain commercial payer has added more administrative tasks to its contract (more hoops to jump through) thus driving up our costs in this specific financial class. This issue can now be addressed at contract negotiation time. We may notice that cost to collect in certain financial classes is high and can be done more cost-effectively by outsourcing. By utilizing KPIs and benchmarks for all financial classes, and by having the ability to drill down when necessary, we can improve the revenue cycle by making better informed decisions and recognize problems / trends in their early stages. Benchmarking can be a valuable tool.

However, when it comes to cost to collect benchmarking,standardization of what goes into the number may be masking real problems. Some organizations may only include their business office expenses while others may include items like technology costs, overhead, etc. With organizations not being required to report the data the same way, this overall cost to collect percentage can become much less effective for benchmarking purposes. When we prepare our income taxes, the IRS clearly defines what needs to be reported as income and what doesn’t, so everyone would benefit from an industry standard on this issue. There really needs to be an industry standard to address this issue. Along with the ability to identify cost to collect by financial class, there is also the need to identify that as claims age, the costs to collect them also increase. By having benchmarks that identify costs by financial class and the age of a claim, we can now make better decisions regarding resources such as staffing, additional process changes needed, etc.

Collection Ratios

Organizations are able to recognize collection problems by looking at indicators such as overall A/R days, percentage of bad debt, A/R days greater than 90, etc. However, by looking at both gross and net collection ratios by payer, you can establish KPIs by financial class. By setting these up, and then utilizing other KPIs like cost to collect, better decisions can be made regarding improving the revenue cycle. By having the ability to drill down into the details of the data, along with having KPIs by payer (as many as deemed necessary), we can quickly answer questions like: is my overall cost to collect growing due to my payer mix, industry changes, added resources? Is this increased cost to collect a negative factor or a positive one? My cost to collect may be higher than my peers, but my net collection ratio may also be higher; thus, justifying this higher than normal cost to collect My organization could also have a lower than average cost to collect which could indicate a positive factor. However, it could also indicate a negative factor if other KPIs are not where they should be. An organization could also be doing a great job collecting in a particular financial class. However, they may not be doing it cost-effectively. With just looking at KPIs in the aggregate, we cannot answer many of these questions.