How ASC Data Analytics Can Benefit Your Facility: Part 2 of 3

By April 11, 2018 June 11th, 2019 ASC Management
How ASC Data Analytics Can Benefit Your Facility: Part 2 of 3

(Part 1 introduces the topic as it applies to ASCs, Part 2 provides examples of how analytics can be beneficial in the ASC arena, and Part 3 will walk through the evaluation process to determine when analytics is a good fit for an organization)

In this second installment of our ASC data analytics blog, we will examine specific ways an analytics program can benefit an ASC. While not every type of report mentioned here may be applicable or beneficial to every facility, the following examples will provide a broad base for understanding the potential benefits an ASC analytics program can provide.

ASC Data Analytics Report #1: Case Cost Analysis

The first category of essential ASC data analytics is case cost analysis. Simply put, case cost analysis determines the cost to complete an individual case. With this number determined, the cost of a case can be subtracted from the revenue generated by that case to obtain the associated profit (or loss). Though determining the profit/loss margin of a single case rarely tells a complete story, logically grouping cases into different “pools” can begin to reveal performance of different segments within an ASC. Grouping cases by procedure type, specialty, surgeon, or payor can reveal performance trends.

Although most ASCs likely know their cost per case at a high level already – total operating expenses divided by number of cases – the true value of adding a formal analytics component comes from the ability to drill down into the data. Going beneath the surface allows ASC leadership to identify specific, meaningful areas of concern that can be improved upon to enhance the overall performance of the facility.

Components of a Case Cost Analysis: Supply Cost

An analytics-led case costing report is driven by details. Our initial definition of case cost analysis mentioned “determining the cost to complete an individual case.” Merely examining the expenses identified on an income statement or general ledger will reveal facility-wide trends. However, that will not stratify the data to provide the level of detail needed to make a valid comparison between case types (the “pools” we noted previously). For example, a basic pain procedure shouldn’t be assigned the same case cost as a complex orthopaedic procedure. For true case costing insight, expenses need to be directly tied to individual cases.

To obtain specificity in a case cost analysis, one would typically rely on the ASC’s inventory management system to determine the per-case supply cost. Reviewing surgeon preference cards by procedure type may also be used if the inventory management process at a facility lacks per-case specificity. This should provide an accurate accounting of the various supplies used for each procedure, as well as, the total supply cost per case. Supply cost differences between surgeons or procedure types are immensely important in providing analysis points when reviewing differences in total profitability later in the process.

Components of a Case Cost Analysis: Staff Cost

In addition to supplies, staff time is an important consideration in detailed case cost analysis. Most facilities use a case log to track time individual staff members spend on a specific case. By totaling individual employee costs associated with the episode of care, direct staff cost per case can be identified.

Components of a Case Cost Analysis: Overhead Allocation

While supplies and staffing make up most of the direct costs for a case, facilities should also assess the impact overhead expenses have on their overall profitability. Overhead allocation can also be completed at the case level. This can be done by determining the total amount of fixed costs for a given period and assigning a portion of these costs to each case. Some facilities may choose to assign an equal overhead value for each case. Other facilities may choose to allocate overhead based on a formula representing the relative utilization of a fixed expense (e.g. allocation of overhead based on OR time, total case time, etc.). Using this methodology, a complex orthopaedic case is assigned a higher overhead expense per case than a quick pain procedure. This makes sense when one considers that an orthopaedic case uses relatively more of the rent, utilities, etc., than a pain case. When an ASC desires to understand the true total costs of each of their cases, providing a logical overhead value assignment is a necessary component.

For most facilities, it isn’t possible to track every staff minute and supply back to every patient with 100% accuracy. Typically, the total direct costs (supplies, staff) that can be tied back to an individual case are lower than the direct costs shown on an income statement. The difference in the two amounts is the unallocated variable expense. Unallocated variable expenses often arise from the aggregation of small expenses (pens, tissues, hand soap, etc.) that are difficult to track and attribute to individual cases. These expenses can be distributed on the case level using the same methodology as the overhead distribution.

Interpreting the Case Cost Data

At this point, all the expenses for the facility – clinical supplies, staff, overhead, and unallocated variable expenses – are now linked back to individual cases. Instead of one generic cost per case, each case has its own unique, true cost. When the costs per case are subtracted from the revenue generated by each case, the actual profitability of that case is revealed.

All this data can be sorted, grouped, and filtered in a myriad of ways. With each new view of the data, analytical insights begin to jump off the page.

Cases previously thought to be highly profitably may prove the opposite due to high supply, staff, or overhead costs. Physicians who have been historically viewed as producers of low revenue per case may actually be contributing significantly to the facility’s profit due to lower-than-expected expenses. Entire specialties and payors may be viewed in a new light. The data may reveal that improvement in just a few key procedure types could have a dramatic impact on the overall profitability of a center. The list of potential findings is limitless.

ASC Data Analytics Report #2: Facility Financial Analysis

An ASC data analytics program should be able to provide a routine, comprehensive analysis of a facility’s financial performance. This should include not only reporting current financial metrics, but also comparisons to the same period during the previous year(s), the most recent periods (often called “trailing reports”), and to ASC-specific regional and national benchmarks.

Often, the facility financial analysis can be tied to case cost data. Case cost data can be reported in a combined suite of reports (a dashboard) that provides quick insight into the ASC’s performance. For example, a decrease in overall facility profit may be identified as the result of an increase in lower-profit types of procedures over the same period. Likewise, a decrease in revenue per case but an increase in total ASC profitability – which could be perplexing – may be identified as an increase in procedures with low revenue per case (which dilute the overall facility revenue per case) but a strong profit margin. Adding a data analytics component to standard ASC financial analysis should increase awareness and understanding of the factors influencing an ASC’s financial performance.

ASC Data Analytics Report #3: Clinical Analysis

Adding an ASC data analytics program can also provide benefits to clinical efficiency and patient safety efforts. Case time log data can help paint a picture of efficiency within the OR, as well as provide a workflow analysis of the activities in registration, pre-op, and PACU. An example is a block-utilization report, which details how well a specific surgeon or specialty fills their allotted OR block time. Identifying trends and tweaking block time allocation as necessary can lead to a more efficient, profitable center.

Patient safety data can be gleaned to identify trends that can prevent a bad outcome before it happens. Staffing data is a wonderful resource an analytics program can use to ensure optimal levels of staffing are being utilized. Medication log data is another database that can be tapped into to add to the clinical safety reporting tapestry. For example, analysis of the medication log data may reveal cases where drugs are being prescribed at different stages in the delivery of care that may create unsafe conditions, such as hazardous drug interactions or over-prescription of narcotics. A dedicated analytics program should be able to drive facility profitability, efficiency, and patient safety through enhanced analysis and amalgamation of clinical data.

Investing in an ASC Data Analytics Program

Attaining highly detailed case cost, financial, and clinical efficiency/patient safety insights is a lot of work. Parsing out valuable insights from scattered databases, case logs, and financial reports requires a specialized skillset and experience tailored to the ASC setting for maximum return on investment. The available data often needs to be “scrubbed” (a time-consuming process) to avoid the dreaded “garbage in-garbage out” phenomenon.

As discussed in Part 1 of this series, dedicated analytics programs and personnel are not currently common in many ASCs. Committing the resources necessary to obtain a quality ASC data analytics program must be carefully weighed against the potential benefits. The next part of this series will discuss strategies to help make this determination. As the ASC industry becomes more competitive and pressures from payors continue to rise, the decision to invest in an analytics program is increasingly becoming the correct choice for many ASCs.


Cody Carlin, Director of Data Analytics

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