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Listen to our President, Jamie Cleverley, join Riley Matthews, Lead Product Manager at Experian Health, to discuss the Hospital Price Transparency Rule and what it means for hospitals around the country. What challenges are providers seeing? How are facilities moving forward despite these issues? How is the disclosed machine readable file information being handled? What comes next?

Listen now! 

Have questions about price transparency? Contact us here! You can read our response to the new CMS price transparency guidelines here.

How Do We Measure Hospital Costliness?

Because the majority of a hospital’s revenue is fixed by fee schedule or related to billed charges almost every hospital in the US is vitally concerned with their relative cost position. Quite naturally, hospital executives are interested in a facility wide metric of cost that can be benchmarked with their prior cost position and more importantly against other peer hospitals. For comparison with other hospitals, the use of publicly available data is required unless there is a shared data arrangement in existence. Hospitals located within a defined market area are unlikely to share data with competitor hospitals so public data becomes a necessity.

In general there are three hospital wide cost metrics that have been cited in the literature and used by hospitals:

• Cost per adjusted discharge – adjusted for case-mix and wage index (CAD)
• Cost per adjusted patient day – adjusted for wage index (CPD)
• Hospital Cost IndexTM (HCI)

Cost per adjusted discharge and cost per adjusted patient day have been used for many years in the hospital industry. They were originally developed in an era when 80% to 90% of a hospital’s total revenue came from acute inpatient services. To account for outpatient activity, total discharges or patient days were restated to reflect outpatient volume. For example, a hospital with $100 million of inpatient revenue and 10,000 discharges that also had $20 million of outpatient revenue would restate its total adjusted discharges to 12,000. This adjusted discharge figure of 12,000 would then be divided into total facility cost to create a cost per adjusted discharge. The same methodology would be applied to define the number of adjusted patient days.

In the days when outpatient business was 10% of total revenue, few problems resulted from using an adjusted discharge or adjusted patient day method. However, the average US hospital now has close to 50% of its total business in outpatient areas, and the percentage is growing. While the growing percentage of outpatient revenue is clearly the primary factor that compromises the utility of a cost per adjusted discharge or cost per adjusted patient day methodology, it is not the only problem. Most of these adjusted measures also try to adjust for case-mix complexity through utilization of a case-mix factor. In the absence of an outpatient case-mix measure, most case-mix adjusted measured use an inpatient DRG case-mix index. Because the relative case-mix complexity of inpatient and outpatient services is not uniform, another potential bias is introduced. For example, a hospital with a major cardiac program may have a relatively high inpatient case-mix score, but its outpatient services may be similar to other hospitals. Adjusting its cost per adjusted discharge measure with its high inpatient case mix would make the hospital appear more cost efficient than it really was.

The HCI measure is a cost metric that is derived from three public-use file datasets: Medicare Cost Reports, Medicare Inpatient Claims -Medpar, and Medicare Outpatient Claims-Hospital Outpatient Prospective Payment System (HOPPS). Two basic measures of cost are used to construct the HCI:

1. Medicare Cost per Discharge – Case Mix and Wage Index Adjusted (MCPD)

2. Medicare Cost per Outpatient Visit – Relative Value Unit and Wage Index Adjusted (MCPV)

The HCI is constructed as follows:

MCPD is a good reflection of inpatient cost. Data for computing this measure can be derived from the public-use files: Medpar and Medicare Cost Reports. This process results in a unique publicly available number for most hospitals in the US. The MCPV is used to assess costliness on the outpatient side of hospital operations. We can construct this measure from public-use files – Medicare Outpatient Claims and Medicare Cost Reports – which makes its availability for most US hospitals a reality. To derive the measure, we divide the cost per visit defined through the Departmental Ratio of Cost to Charges (DRCC) extensions by the relative value units (RVU) of the claim. The RVUs for each claim are based upon Medicare Ambulatory Patient Classification (APC) weights or Medicare defined fee payments divided by the hospital’s APC conversion factor.

The real question that still needs to be answered is which measure is a better predictor of actual hospital costliness. In an earlier study of over 2,000 non-teaching hospitals, we examined the correlations between these three cost measures and the hospital’s Medicare margin. A hospital’s margin on Medicare inpatient and outpatient business should provide a surrogate measure of hospital relative cost. Medicare’s payment to acute-care hospitals is prospectively based for both inpatient and outpatient services for most acute-care hospitals so the primary variable impacting profit on Medicare patient s would be cost. We have excluded from our sample of acute-care hospitals all teaching hospitals and all other hospitals not paid on a prospective basis, e.g., critical-access hospitals. Because Medicare payments are fixed, hospitals with higher margins (defined as Medicare payments less Medicare assigned costs divided by Medicare payments) should have more efficient cost structures. . We also excluded disproportional share (DSH) payments. DSH payments are provided because of payer mix and should not be related to actual costs of hospital operations on a unit basis.

To evaluate the relative accuracy of the three cost measures, we performed a number of statistical tests. The HCI had a correlation with Medicare margin that was 67% better than CPD and 48% better than CAD. While all three measures were significantly correlated with Medicare margins, the HCI exhibited a more positive association. The HCI should produce fewer false signals of relative cost position and would be a better predictor of a hospital’s relative cost position.

If you have any questions, or would like to know more, let us know!

Many healthcare providers have become very concerned about their posted charges for specific services and procedures in the new price transparency world in which they live. To this end, it is very common to see providers either reduce existing charges or refrain from price increases in selected areas. One very common result of price reductions is to increase the number of patient claims where a “lesser than” payment provision comes into effect.

Let’s take a closer look at how lesser than language may impact overall payment from a payer to a provider.  Claims that result in lesser than payment are simply situations where the provider’s actual charges are less than the negotiated fee. In general, there are two methods for assessing whether a lesser than payment provision results in any given situation. The first is on an aggregate claim level basis. For example, a specific contract may specify a payment of $17,000 for MSDRG 794 (Neonate with other significant problems). If actual charges for that claim were $13,000, then the payer would make a payment of $13,000 and not the negotiated fee of $17,000. The second type of lesser than is non-aggregate. This is usually at the individual charge code level, e.g., a lab test or imaging procedure. For example, CPT code 82785 (Assay of IGE) may have a negotiated payment rate of $44.00 when performed on an outpatient basis. If the actual price for this test was $39.00, then the payer would make payment at the actual price of $39.00 and not the negotiated fee of $44.00.

Most health care executives do not like to leave money on the table and their first response is often to remove these lesser than issues by selective price increases. While this may seem relatively simple to achieve, it is often not feasible or desirable. Let’s take the easiest type to fix first which is non-aggregate lesser than cases. In the lab test example above, it is very easy to increase the price from $39.00 to $44.00. This may not however be a good strategy even though it is very feasible. This specific test may be highly price sensitive, and your price may already be well above your peers. In addition, the specific lesser than situation might be just one payer with very low volume, so the dollars lost are not significant. In short, the potential gain in revenue must be balanced with community image and possible lost business.

Fixing aggregate level lesser than claims is often much harder to accomplish. Let’s use the neonate claim from above to illustrate this. Any specific review of lesser than neonate claims will show that there are many specific billed services included in these claims, perhaps 50 or more individual charged services or procedures. In most cases, the largest area is the nursery room rate accommodation, and one may be tempted to just raise that one charge code. However, the increases could be very large in many cases. For example, the current Level 1 room rate may be $2,300 and removal of the lesser than situation might require an increase to $5,800. Most likely, this level of increase is unreasonable and would only fix the one lesser than claim. Reviewing all neonate lesser than claims might suggest that other areas are creating the lesser than status such as drugs or lab tests. The actual size of the loss is also important. As discussed above, a few cases from one payer do not make a strong case for price adjustments.

So, what is the solution to minimize the loss of revenue from lesser than provisions. The best long-term approach is contract term adjustments. There should be a quid pro quo for specific changes from both parties. If you want a specific lesser than provision removed—or all lesser than provisions removed be prepared to negotiate revised fee schedules in other areas. In this era of price transparency, also recognize that your negotiated rates from one payer may be visible to other payers and might create some new demands for rate changes from payers who may feel their rates are much higher than their competitors. In the absence of agreement between payer and provider, selective price changes may still be your best option.

Have questions? Let us know!

What is the relationship between hospital costs CMS quality rating?

At the time of this writing Medicare has provided incentive payments for improvements in hospital inpatient quality to approximately 3,000 acute care hospitals through its Value Based Purchasing (VBP) program. A number of commercial payers have also introduced VBP programs for payment to their participating hospitals. The unanswered question is do improvements in quality come at a cost, or do they actually reduce cost. While there have been many prior studies, those studies varied in their definition of both cost and quality. Some studies reference cost to the patient while others review cost to the hospital. The studies also used different metrics for defining quality.

In this short blog, we will take a look at the relationship between costs incurred by the hospital and the quality rating provided by CMS in Hospital Compare at their website. Hospitals receive an overall star rating from 1 to5. The overall star rating includes a variety of the more than 100 measures CMS publicly reports, divided into 5 measure groups or categories: Mortality, Safety of Care, Readmission, Patient Experience, and Timely & Effective Care. We have pulled the 2021-star ratings reported for short term acute care hospitals. It should be noted that much of this data relied upon three years of reporting 2016 to 2019. We next pulled cost metrics for those hospitals from 2020 Medicare cost reports. Merging those two data bases provided us with 2,762 hospitals. The quality and cost metrics are shown below.

The table shows that there is a reduction in cost for hospitals with higher quality scores. For example, hospitals with the poorest star rating (1) had a median Hospital Cost Index (HCI) value of 103.2 which was 5 percent above the HCI value of 98.5 for hospitals with a 5-star quality score. The largest variance in the HCI values occurs when the quality score improves from 1 to 2. While cost reductions take place in other quality score changes the variance is much smaller.

The HCI is a metric that combines values for the average cost per discharge indexed to the US average and the average cost per outpatient visit which is also indexed to the US average. Both of these metrics are also adjusted for both case mix variation and cost of living differences.

We also included another metric for hospital cost, Cost per Equivalent Discharge (CPED), to further assess the relationship between quality and cost. The results were a mirror image of the variation observed when the HCI metric was used as the measure of hospital cost. Hospitals with the lowest quality rating had the highest CPED which was 9 percent above hospitals with 2-star rating. While variation between other quality scores showed reduced costs with higher quality scores, the variation was smaller.

Given these results, the question that needs answered is why are costs higher for the lowest quality rated hospitals? The table below shows median net patient revenue and median number of inpatient discharges for each Hospital Compare star rating. The data suggests that the largest hospitals are more likely to have the lowest quality rating. Further, the data suggests that hospitals with higher volumes of inpatient discharges are more likely to have lower Hospital Compare quality ratings. When we ran a simple correlation between quality scores and either net patient revenue or inpatient discharges, we found that both were highly correlated, but inpatient discharges had a higher correlation coefficient (.64) compared to net patient revenue (.56).

While this is a preliminary analysis, there are several key findings. First, larger hospitals –especially those with high volumes of inpatient care-have lower Hospital Compare quality scores. Second, hospitals with the lowest Hospital Compare quality score do have higher levels of cost but variation is much less across the remaining 4 quality levels. One possible explanation for these findings might be a bias in the Hospital Compare quality scoring methodology. A higher percentage of the Hospital Compare quality score is related to inpatient procedures. If larger hospitals treat more severely ill patients, it is possible that the Hospital Compare quality score might not recognize severity of care variation. For example, would death rates for pneumonia patients be higher for larger referral hospitals who might be receiving more severely ill patients? If this is true, larger hospitals might have lower scores in this area.

Have questions about this or want to learn more? Let us know!