Midas Analytics leverages a robust analytics data warehouse with over 100 million claims, and machine learning based advanced analytics to predict patient-specific risks, deliver population health analytics and support business intelligence for proactive operations improvement.
The Midas Readmission Penalty Forecaster replicates the CMS Readmission Methodology by using national Medicare data to develop predictive analytics, which calculate your hospital’s excess readmission ratios for each clinical cohort within 95% accuracy. In addition, estimated financial penalties are provided to help your stakeholders prioritize which populations are at greatest risk for penalty. In this way, you will know how many readmissions are too many, and which areas to prioritize for improvement before it’s too late.
- Education on the Hospital Readmission Reduction Program
- Quarterly meetings to engage your stakeholders in their predictive performance up to two years before penalties are imposed
- Executive summary of overall hospital or healthcare system performance and estimated financial penalties
- Detailed analysis of each clinical cohort to review readmission patterns and estimated financial penalties for your hospital
- Adjusted readmissions that estimate non-same hospital readmissions not yet available in CMS claims data
- Patient detail file containing the risk factors for patients in each cohort
- Identification of hospitals where readmission events occurred in CMS claims
- Midas account numbers identified for records in CMS files to facilitate case review
Cost of Care Analytics
Today’s healthcare climate is marked by growing pressure to manage costs.
Hospitals now must understand not only where costs are highest, but also how to define cost differences between providers and among various clinical populations.
Our financial analytics solution assists hospitals with assessing and managing the cost of care. Data is retrieved from the hospital’s Cost Accounting System and Charge Master Detail and loaded into the Midas Charge Dictionary. By using a series of indicators, the geometric mean cost of care can be examined for clinical populations. Comparative benchmarks can be integrated into dashboards and the DataVision SmartReport as well as Midas Statit™ PPR (Physician Profile and Review) and Statit piMD™ (Performance Indicator and Management Dashboard).
Also included is the Cost of Care Analytics Toolpack, a Standard Report that produces a Microsoft® Excel® workbook with 14 worksheets that you can use to identify trends and patterns in cost data.
Patient-Centric Risk Model
We’re raising the bar in hospital risk adjustment methodology. We use the power of precision to predict mortality, length of stay (LOS), readmissions, complications and charges.
Midas Risk Adjustment models provide:
- Unbeatable accuracy to identify high risk patients and set performance targets
- Automatic integration into Midas Care Management Reporting
- Greater precision for physician profiling and review
- Risk adjusted comparison by provider specialty
- Patient-level drilldown to verify data