The Truven Health Blog

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Deciding Whether to Implement a TJR Readmissions Intervention Program

By Truven Staff

In my last post related to our bundled payments research series, I discussed how it’s possible to identify the clinical factors that are most predictive for a commercially insured total joint replacement (TJR) patient hospital readmission. That type of identification could be beneficial since one goal of bundled payment models is to reduce costs, including those associated with readmissions.

But even with the ability to identify readmission risk factors, should we? Is using a predictive model better than a random assignment of intervention? And if it is better, is the value of predictive modeling worth the cost of intervention?

To answer these questions, statistical methods are required.

Consider the predictive accuracy of one model: We analyzed the trade-off between sensitivity (the ability to correctly identify high-risk patients) and specificity (the ability to minimize the number of patients incorrectly identified as high risk). The AUC (area under the ROC curve) score was 0.62, which is distinctly better than the 0.50 that represents a random assignment of risk — but still a fair distance from a perfect 1.00 assignment of risk. Nevertheless, this scoring shows that a statistical approach could be used to set a useful threshold for assigning high risk for an intervention program.

To further assess the value of a readmissions model, we then worked from the equation of: Expected Value = Expected Benefit − Expected Cost.

  • Expected cost is the average cost per patient intervention multiplied by the number of interventions. The average cost depends on the mix of interventions and their duration.
  • Expected benefit is the cost of an avoided readmission multiplied by the number avoided. The number avoided is the product of the number of interventions and the probability of success of each intervention.

To test our calculations, we performed a simplified version of how a hospital might assess the value of a model. Somewhat arbitrarily but informed by experience, we chose a cost per intervention of $500, the cost of an avoided readmission of $10,000, and an expected success rate of 50 percent.

We then set a risk threshold at 0.07 (above which the patient will be classified as high risk). We found that the intervention would target 26 patients per thousand at a total cost of $13,000. We would expect three of these patients to be readmitted without intervention, and with a 50-percent success rate, the intervention would prevent 1.5 readmissions or $15,000. That’s an expected net savings of $2,000.

Based on this simple example, the results suggest the accuracy of the model in identifying high-risk patients is marginally sufficient to support a targeted intervention. But actual readmission cost, success rate, and risk threshold will change the results in every instance, so understanding the true experience of each organization is critical to deciding whether to apply an intervention model.

There is much more, of course, to this approach than we’ve shown here. For details and more insights from our bundled payments research, you may want to download our latest brief, Total Joint Replacements in the Commercially Insured Population: Predicting Risk of Readmission.

Bob Kelley

Senior Research Fellow, Advanced Analytics


New Bundled Payments Research: Identifying the Most Predictive Risk Factors for TJR Readmissions

By Truven Staff

As part of our continuing research into bundled payments for commercially insured total joint replacements (TJRs), we recently turned our focus to patient readmissions — which we already know vary in cost and occurrence by geographic area and type of post-acute care a patient receives.

Logical thinking tells us that if we could accurately identify TJR patients who are at high risk for readmission due to certain clinical factors, we could reduce or prevent readmissions. And any change in TJR readmissions could then impact TJR value-based bundled payments. The goal, of course, would be to identify at-risk patients early in the care process, so that they could be targeted for special care or intervention programs.

But can we identify the top clinical risk factors?

To find out, we used TJR claims data from the Truven Health MarketScan® Commercial Database to analyze 84,648 simulated bundles. Each bundle was characterized by more than 35 data attributes, including patient demographics, presence of readmission, post-acute care usage, payments by component service type, comorbidities, utilization of healthcare services in the six months prior to the surgery, and more.

 Across several models, we found that the most predictive risk factors for TJR patient readmissions were:

  • Hospitalizations in the six months prior to the TJR
  • Emergency room visits in the six months prior
  • Unique condition/disease diagnoses in the six months prior

More specifically, when we looked at odds ratios estimated in a logistic regression model, additional significant TJR readmission risk factors were:

  • Number of comorbid, high-stage chronic conditions
  • Number of high-stage acute episodes in prior six months
  • Comorbid cardiovascular disease
  • Comorbid cerebrovascular disease

In a future blog post, we’ll take a look at whether or not using these clinical insights to identify and target at-risk patients provides better results than a random selection of patients.

Full details on this study, and additional findings, are available by downloading our latest research brief, Total Joint Replacements in the Commercially Insured Population: Predicting Risk of Readmission.

Bob Kelley
Senior Research Fellow, Advanced Analytics

 


A Closer Look at Post-Acute Care Variation for Total Joint Replacements

By Truven Staff

 

At Truven Health AnalyticsTM we’ve been researching cost variation in simulated bundled payments for privately insured total joint replacement (TJR) patients for several months now. (Visit the landing page for more information and recently released briefs.)

In an earlier blog post, we reported that cost differences across U.S. Census regions for the post-acute care portion of a bundle ranged from an average of $3,907 to $5,292.

 

I’d like to make a few additional points about these differences.

First, there is no apparent link between hospitalization cost and post-acute care cost.

We know from our previous research that anchor hospitalization costs were the main driver of the variation in overall bundle cost. Post-care services were the next most impactful driver. But we’ve found no clear relationship between the average post-acute care cost in a division and the average anchor cost.

The highest cost variation was found in rehabilitation facility costs.

Our study found substantial differences across divisions in the average cost by type of post-acute care service a patient received. For home healthcare costs, the difference in the average cost per patient was just $1,300. For skilled nursing facility care, the difference was more than $5,000. And for care at an inpatient rehabilitation facility, the difference was more than $10,500 per patient.

This information definitely points to the importance of discharging a patient to the right care option to keep costs down, while still providing the best care and achieving the best outcomes.

 Of course, regional preferences play a role.

Because of our study’s large sample size, it is unlikely that post-acute cost variations result from differences in patient characteristics. However, simple geographic-area preferences — such as historical patterns, post-acute care facility availability, or health plan contract rules and payment rates — could play a role. More research would be needed to identify those patterns.

You can read more about our findings by downloading the full research brief, Bundled Pricing for Total Joint Replacements in the Commercially Insured Population: Cost Variation Insights by Bundled Care Components.

Stay tuned for a new brief coming soon on the role of readmissions in TJR bundled costs.

Bob Kelley
Senior Research Fellow, Advanced Analytics


Joint Replacement Post-Acute Care and Readmissions: Variations Represent Opportunity to Improve Bundled Cost

By Truven Staff

In our continuing research at Truven Health AnalyticsTM into bundled payments for commercially-insured total joint replacement (TJR) patients, we’ve uncovered some additional insights this month. The research is based on simulated bundles that include the entire episode of care from surgery through 90 days post-discharge; the data is from the Truven Health MarketScan® commercial claims database, analyzed across U.S. Census divisions.

Length-of-Stay Finding

We found significant variation in the effect of anchor hospitalization length of stay on total bundled costs. The average impact varied from $313 per additional day in the anchor facility (after initial day of hospitalization) or 1 percent of the base price in the East North Central division, to $1,944 or 6.2 percent of the base price in the Pacific division.

 

Post-Acute Care Impact

We also found differences in average bundled cost across regions for post-acute care services, from $3,907 to $5,292 — a difference of nearly $1,400. In addition, the study identified significant variation in the average bundled cost by type of post-acute care received by patients (for instance, home health services versus a skilled nursing facility). The highest average patient cost was for care at a rehabilitation facility — the option that also had the greatest variability in cost across divisions.

And About Those Readmission Rates …

We also found that patients with multiple types of post-acute care had higher readmission rates. The combinations of rehab facility and home health, and skilled nursing and rehab, had similar readmission rates at 10.5 percent and 9.2 percent, respectively. What’s not known is whether these patients were at higher risk of readmission prior to discharge, or if the risk increased during post-acute care. We hope to tackle that question in future research.

So What’s the Key Takeaway?

All of this analysis points to the importance of discharge planning and directing patients to the appropriate care option when the goal is to reduce bundled costs for TJR, while maintaining high levels of quality and patient outcomes. While costs associated with post-acute care and readmissions were only a fraction of the total bundled costs for the commercial population, they were subject to substantial variability — representing perhaps an important opportunity to better manage results.

 

For more insights from this study, you can download the new research brief, Bundled Pricing for Total Joint Replacements in the Commercially Insured Population: Cost Variation Insights by Bundled Care Components, here.

 

Bob Kelley
Senior Research Fellow
Advanced Analytics

 

 


Makeup of TJR Bundled Costs in Commercially Insured Differs From Medicare Population Bundles

By Truven Staff

As part of the Truven Health AnalyticsTM continuing research series into total joint replacement (TJR) bundled costs for commercially insured patients (age 45 to 64), we’ve found that readmissions make up a small percentage of average total bundled costs — 2.1 percent (just $760 on average per patient). That appears to be true no matter what region of the U.S. patients are located.

The average percentage of total bundled costs due to post-acute care is also fairly low, although higher than readmissions, at 12.7 percent. The average percentage among U.S. Census divisions ranges from 10.8 percent (Mountain Division) to 14.5 percent (East South Central), which shows a bit more cost variability than readmissions.

 

Our simulated commercial bundles included inpatient hospitalization, post-acute care, and readmission costs.

 

Here’s a very quick look at what we found:

These findings are in contrast to projections for Medicare’s older population. For example, additional Truven Health analysis of simulated TJR bundles for one large hospital showed that 21 percent of the Medicare total bundled cost was for post-acute care compared to less than 8 percent in the commercially insured bundles — with almost 14 percent versus 4 percent for skilled nursing facility costs alone.

 

Of course, it’s not unexpected that an older, 65+ Medicare population would have a higher likelihood of serious comorbid conditions and a greater need for post-surgical support. However, the Centers for Medicare & Medicaid Services predict that most of the cost-savings for the Medicare population and its new Comprehensive Care for Joint Replacement (CJR) Model will originate from improvements in post-acute care and readmissions costs after reducing cost variation through bundling.

 

The savings opportunities appear to be far less obvious in the commercial population.

 

For more details on our data, methodology, and other findings, you can download the complete research brief, Bundled Pricing for Total Joint Replacements (TJRs) in the Commercially Insured Population: Geographic Variation and Cost-Driver Insights.

 

Our next brief will cover an analysis of the impact of length of stay and post-acute care decisions on bundled commercial costs for TJR patients. If you’d like to be alerted via email when that brief is released, you can provide us with your information via interest.truvenhealth.com/BundledPaymentsWP.

Bob Kelley
Senior Research Fellow, Advanced Analytics

 

 

 


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