How Dexur Helps Hospitals Improve Quality and Performance Outcomes


Want to know more about Dexur's Capabilities? Get In Touch


By: Sharath Joji  Jul. 12, 2021

Hospitals face multiple challenges in monitoring CMS programmes and improving performance across various prescribed measures. These challenges include delay in retroactive CMS Value Based Purchasing (VBP) measure scores, complexity in replicating CMS algorithms, requirement of advanced technical insight for latest adjustment projections, lack of essential data to reconcile CMS methods, and managing stacked up information released by CMS.

Dexur is an approved purchaser of CMS Medicare claims data and helps hospitals to overcome these challenges by producing more recent and updated data. Dexur also replicates CMS algorithms using advanced technical skills, tracking a patient journey longitudinally to ensure in-hospital and post discharge data, and deep diving on specific DRGs that are driving the factors affecting various scores. Dexur combines data, technology, and advisory to effectively assist hospitals in elevating their quality and value programs.

Following are the broad areas where Dexur can help Hospitals in improving their quality outcomes and performance:

1. VBP Predictions, Monitoring & Benchmarks

Dexur calculates and predicts the VBP adjustment factor and VBP payment impact on hospitals by replicating the CMS algorithm. Predictions are made by considering baseline and performance time periods as suggested by CMS for each individual measure.

Another way Dexur helps to monitor overall VBP score and individual measure scores is by providing both automated simulator and manual calculator for creating various scenarios. Hospitals can use these tools to choose suitable scenarios for improving their VBP adjustment factor and payment impact.

2. Episode Cost Monitoring (VBP, MSPB & BPCI-A)

Dexur helps hospitals monitor episode costs for Medicare Spending Per Beneficiary (MSPB) (25% weightage in CMS's VBP program) and Bundled Payments for Care Improvement- Advanced (BPCI-A). Dexur breaks down episode costs into various categories including index cost, rehospitalization cost, SNF cost, Home Health cost, and Hospice cost. The post discharge rates which are a major driving factor in the increase/decrease of total costs are also analyzed by Dexur.

Dexur has developed a calculator which demonstrates the impact of MSPB episode cost reduction on VBP payment adjustment. The reduction in MSPB costs can be calculated using following four different levers:

Hospitals who are episode initiators in BPCI-A program can monitor their clinical episode service line group selections for the latest period and also understand a breakdown of their episode costs.

3. Readmissions Analytics and Improvement

Increase in readmission rates can not only adversely affect the episode costs and VBP score, but also result in payment reduction from Hospital Readmissions Reduction Program (HRRP). Dexur helps hospitals to monitor readmission rates and causes by calculating readmission rate progression on both rolling 12 months and rolling 3 years basis.

Dexur's HRRP scenario calculator helps hospitals in understanding the rate of reduction in readmissions for each measure, thereby avoiding the overall reduction in payments. Dexur also tracks readmission of patients to other hospitals for specific DRG groups. A detailed report of the patient journey is created to point out the causes of readmission.

Readmission rates are categorized into readmission within 3 days, 7 days, 15 days, 30 days, 60 days, and 90 days post discharge. Dexur also does disease-specific impact analysis that helps in monitoring the causes of readmissions.

4. Post Acute Care Provider Benchmarks

Tracking post acute care costs is significant for hospitals in their study of episode costs. Dexur benchmarks the costs incurred towards post acute care facilities (nursing homes, home health agencies, hospices) for all quarters of the year upto the latest period. Dexur also compares the cost of care for all major post acute care partners with that of national average at the DRG level.

5. Mortality Rates Analytics and Improvement

Increase in mortality rate could be disadvantageous to hospitals as it will have a negative impact on their VBP score and CMS star rating. Dexur helps in monitoring increase in Mortality rates by tracking the various mortality measures for both 12 months and 3 years rolling period.

6. CMS Star Rating Prediction, Monitoring & Benchmarks

Dexur does CMS Star Rating predictions by replicating CMS algorithms, thereby assisting hospitals in improving their Star Rating score. For Star Rating predictions, Hospital quality measures have been grouped into five broad categories. These measure scores are calculated based on time period and time lag under each measure. The group measure score is then standardized and weighted to calculate the hospital's summary score. Dexur uses the k-means clustering method used by CMS to predict the exact star rating results.

7. Hospital Quality Outcomes Benchmarks

Dexur benchmarks hospital quality outcomes to predict the variables like average length of stay, readmission rate, mortality rate, discharge rates to post-acute care facilities, etc. for patients admitted to the hospital. Predictions can be filtered based on the patient's DRG group, race, and age group during any given sample period. Filters can also be used to understand complications and to check if they are Diabetic. These hospital quality outcomes are compared to state and national values so that healthcare providers can get a better analysis of their performance.

8. Physician Benchmarks

Physician benchmarks help hospitals in monitoring their performance, assess hospitalizations, and evaluate their quality outcomes. Dexur facilitates physician benchmarks by providing detailed reports of inpatient outcomes concerning each DRG group and even specific DRGs. This report also offers outpatient physician referrals data of all operating and attending physicians. Dexur uses a scatter plot to help hospitals compare physicians for all/particular DRG groups based on various metrics.