“Hospital Compare” Cube Implementation Wendi Welch

“Hospital Compare” Datasets WHAT IS HOSPITAL COMPARE? Hospital Compare has information about the quality of care at over 4,000 Medicare-certified across the country. You can use Hospital Compare to find hospitals and compare the quality of their care.  The information on Hospital Compare:  Helps you make decisions about where you get your health care  Encourages hospitals to improve the quality of care they provide  Maintained by  Centers for Medicare & Medicaid Services (CMS)  Official Datasets:  

Who Else Cares About Hospital Compare? It’s not just for consumers (patients)  This same data is used by Medicare internally to make incentive payments to providers of medical services based on the quality of care:  Pay for Performance (P4P)  Provides what are typically financial incentives to providers to improve the quality of the care they deliver and/or reduce costs. The model gives health care providers the chance for a financial upside – such as a bonus — but no added financial risk, or downside.  By giving an incentive to providers for increasing the quality of care, Medicare reduces base payments for services provided  Improving quality of care should reduce the complications/readmissions/deaths being paid for, resulting in a cost savings  Competitive Advantages  Surrounding or competing hospitals can use this data to compare and benchmark against

Business Objectives  Opportunities to analyze the data for various attributes and find:  Highest Death Rates by Region/State/Counties in Texas  Highest Hospital Acquired Infections Rate by Region/State/Counties in Texas  Lowest Patient Satisfaction Measures by Region/State/Counties in Texas  Highest Rate of Complications by Region/State/Counties in Texas  Highest Rate of Payment for Certain types of procedures by Region/State/Counties in Texas  Highest Rate of Outpatient procedures by Region/State/Counties in Texas.  Trends of Incentive Payments  Etc…

Common Fields Existing between the Scoring Tables  Provider  Address/Location  Score/Measure  Measure ID  Measure Name/Description  National Comparison (for some)  In addition there was a Hospital information table  Data goes back to 2005 – Only 2013 on was imported  Only certain tables/measures were used due to the voluminous nature.

Data Sample

Fields Created for Analysis  Key Fields for each table  Regions and Counties  State Populations  Measure Categories  Time Fields

Some Required Transformations in the Data  Measure IDs/Names changed throughout the years  Hospital Names changed  New Measures or Measures no longer used  Descriptions have changed  Some of the IDs had different formatting  Measures were in different tables

Transformed Data

Snowflake Schema/Table Relationships

Fact Table Structures (only showing non-repetitive fields)

Dimension Table Structures LocationHospitals TimeMeasures National Comparison

SQL SERVER

Cube Structure and Data Source View

Time Dimension

Measures Dimension

Hospitals Dimension

Hospital Dimension (cont’d) Clusters – Or buckets were used for the population attribute so that analysis could be done on states within a population range.

Reports Just a few examples

Outpatient Volume  For Consumers/Patients: Which hospital in Houston does the most of a certain type of outpatient procedure?

Highest Payment Rates

Patient Satisfaction (by hospitals in a particular city)  Which Hospital scored the best for these measures?

Patient Satisfaction (by Region)  Which Hospital scored the best for these measures?

Death Rates for Certain Measures

Death Rates for Certain Measures Using Population Buckets  For those hospitals that received “worse than the national average”, does a state’s population size have any correlation to death rates? Does Ownership Type affect performance?

THANK YOU!