The following pages provide you with a description and example of the type of report content you will receive after submitting your claims data. The data included here are illustrative only, and are not from a single source dataset. Your actual feedback report, including the specific list of episodes and details will differ.
The examples are provided to assist you in interpreting your own report and to highlight key points of focus.
The report is focused on 2 primary areas:
- Understanding cost variation and rates of complications in your episodes of care
- Quantifying the potential savings that can be achieved through reducing the observed variation and complication rates
Future editions of this reporting tool will include analysis of the drivers of intra-episode cost variation among price and utilization as well as insights into high emergency department and inpatient utilization.
Your report will first provide you with a snapshot of the volume and time period of data, the proportion of costs that are captured by the episodes evaluated and total costs and costs per member, per year broken down by claim type.
In the examples above, about 40% of the total medical costs in the dataset were grouped into the listed episodes. The per member/per year costs increased somewhat from 2010 to 2011 for inpatient (IP), outpatient (OP) and professional (PB) services.
A. Is there significant cost variation and incidence of complications within your episodes of care?
This part of your report analyzes claims data to quantify the average costs, variation in costs, and costs attributable to potentially avoidable complications for a set of defined episodes of care. Your report will contain these episodes as well as 25 additional procedural, medical and chronic condition episodes.
The episode of care analyses focus on three aspects:
- Episode Cost Variation: Substantial variation in episode costs may mean provider and/or patient incentives are not working. Variation in episode costs can be due to three factors: the price per unit of service, the quantity of services, and the mix of services. Understanding the contribution of each on total variability would help map out potential interventions. â€¨
- Proportion of Total Costs: Focusing incentives on areas of care that are frequent and costly will have a greater impact. It stands to reason that achieving reductions in costs of expensive episodes will yield greater savings, and improving the quality of care for more common episodes has the opportunity to positively impact a larger segment of the patient population. â€¨
- Complication Rate: One obvious target for improvement is the rate of potentially avoidable complications (PACs) within each episode of care. By focusing on episodes of care where the rate of complications is relatively high, there is the potential for cost savings and improvements in care quality.
Ranking Episodes by Cost Variation, Proportion of Total Costs and PACs
|Episode Type||Average Cost per Episode
|Pregnancy and Delivery||$9,870||0.62||2.3%||14%|
|Gall Bladder Removal||$12,878||0.91||1.1%||12%|
|Coronary Artery Disease||$3,616||2.03||4.8%||23%|
|Chronic Heart Failure||$9,384||2.23||0.7%||62%|
How to Interpret your Episode of Care Cost and PAC Report
The chart above provides a graphic depiction that combines the information on episode specific relative cost, cost variation and complication rates. The chart is ordered from low to high cost variation (left to right). The relative size of the bubble represents the episode costs as a percent of total medical expenditures and the color gradient represents the relative rate of complications with a darker hue indicating a relatively higher complication rate. A logical area of focus would be on episodes of care with the greatest cost variation, highest complication rates and greatest share of the total cost.
The table shows the detail of the metrics for each episode of care. In the example, colonoscopies, coronary artery disease and diabetes make up the largest share of annual costs due to their prevalence. Although the average episode cost for CABG is substantially higher than other episodes, they make up less than 1 percent of annual costs due to their relatively low frequency.
The data indicate that the highest variation in costs is found for chronic care episodes such as chronic obstructive pulmonary disease (COPD) asthma, chronic heart failure, gastro esophageal reflux disease (GERD), hypertension, diabetes and coronary artery disease, while the lowest variation is found for procedural types such as knee and hip replacements, bariatric surgery and coronary artery by-pass graft (CABG).
Generally greater variation is found in episodes where complication rates are higher, indicating that complications may be a significant driver of variation.
B. What are the potential savings that could be acheivied from reducing complication rates and cost variation?
Another way to look at this problem is in terms of the potential savings that could be achieved if the variability in costs was reduced to a “best-in-class” level or a less ambitious trimming of outliers. As such, the sum of the potential savings, divided by the total costs of care, gives a sense of the magnitude of the cost problem at hand and the savings opportunities for each episode.
For the estimates of potential savings we use a methodology that is not overly aggressive and seeks to reduce the costs of the highest 20th percentile of episodes. The methodology determines the 80th percentile of the ratio of the actual episode costs to the expected episode costs. Expected costs are defined as the costs that would be expected given the average costs across the population dataset factoring in the individual patient’s risk factors. This way, the potential savings take into account the relative severity or the risk factors associated with individual patients.
In the example, the 80th percentile ratio of expected to actual is 1.20. In other words, at the 80th percentile, the actual cost is 20 percent above the severity adjusted actual costs. Potential savings are derived from those episodes whose ratio of expected to actual is above 1.20.
Total $ Savings
Potential Savings from Reduced Variation of Costs and PACs
|Episode Type||Number of
|Total Costs||Average Cost
|Coronary Artery Disease||99,654||$360,348,864||$3,616||$48,204,323||13%|
|Chronic Heart Failure||5,926||$55,609,584||$9,384||$9,887,512||18%|
|Prengancy and Delivery||11,696||$115,439,520||$9,870||$28,087,942||24%|
|Gall bladder Removal||7,552||$97,254,656||$12,878||$41,137,465||42%|
The table indicates that if the variation is reduced such that episodes are no more than 20 percent above expected costs, the savings can be substantial. The estimate in this case is more than $561 million or 24% of episode costs. As indicated, the percentage and dollar savings differs by episode type ranging from 11% to as much as 54% of total episode costs.
How can you best address your problems and improve your outcomes?
Potential incentive solutions will depend on your specific cost drivers and episode areas of focus. For example, it might be easier to create an incentive to standardize the number and mix of services used in a procedure by instituting bundled payments than by employing some form of value-based insurance design (VBID). On the other hand, it might be easier to used VBID to move patients from a high-priced provider to a lower priced one than by using payment incentives. The next version of this tool will dig deeper into the price vs. utilization drivers of cost variation. Additionally, several organizations are partnering with HCI3 to become certified to run the ECR analytics and provide even greater in-depth information on the cost variation across specific providers or provider groups. Once an organization has been certifed, it will be listed here.
We invite you to learn more about how to impact costs through the HCI3 Learning Center and Library. The library contains links to reports and other resources that are set up to address specific incentive needs.