Team Mbrace RWJF Hospital Price Transparency Challenge
Purpose: This analysis tries to understand relationships & patterns in hospital-inpatient-data, in context of demographics and quality.
1) CMS Inpatient Pricing Data ( cms.gov )
2) Demographic Data (Census.gov)
3) Hospital Quality Data (ahrq.gov)
Basic Data exploration techniques such as means, median, min, max, percentiles were used across various sections of the data.
Step-1: We first determine the top 10 DRGâ€™s with high charge AND high discharge volumes.
Step-2: We look at the distribution of reimbursement rates and discharges across all states to identify clusters of states with similar reimbursement patterns.
Step-3: We look at relationships between discharges-per-million and 65yrs and older population by state.
Step-4: We look at readmission and mortality rates for Heart Attack, Heart Failure and Pneumonia of providers per state whose quality worse than U.S. National Rate.
1. Clusters of states with similar reimbursement patterns. This helps public understand disparities in payments-to-charge ratio among states
2. Layout of Providers relative to mean charge and payment within each State and HRR, this helps in understanding disparities in Charges and Payments within each state and HRR.
3. Discharges per million 65-and-over population by state by DRG, this helps in understanding DRGs in context of demographics.
4. Bubble graph showing # of providers and discharges per state for Top 10 DRGs, this helps in understanding Healthcare resource distribution.
5. Number of Hospitals whoâ€™s Quality is worse than U.S. National Rate; this visualizes Hospital Quality by State.
6. An example of providers in Hospital Referring Region.