Medicare EPMs. Using Data to Paint a Clearer Picture

Transcription

1 Medicare EPMs Using Data to Paint a Clearer Picture

2 Copyright, Disclaimer and Terms of Use Copyright 2017, BESLER. All rights reserved. The material contained within this presentation is proprietary. Reproduction without permission is strictly prohibited. This document may not be copied, reproduced in any manner or format or furnished to others, and derivative works that comment on or otherwise explain it or assist in its implementation may not be prepared, copied, published and distributed, in whole or in part, without written permission of BESLER. This document may not be modified in any way, (such as, for example, removing the copyright notice or references to BESLER or other organizations). This presentation does not represent legal advice. The information herein is valid for the date of the presentation only.

3 Medicare Episode Payment Models

4 Takeaway from today s discussion The EPM programs are constantly evolving CMS is not providing enough information for you to take meaningful action. What you can do to stay ahead of the curve.

5 Medicare Episode Payment Models Recap and update

6 About the Programs CJR MS-DRGs 469 & 470 Participating hospitals are responsible for the total costs of the inpatient admission and all treatment 90 days post-discharge CJR (Comprehensive Care for Joint Replacement) is a mandatory bundled payment model in 67 MSAs (4/1/16-12/31/20) *Proposed: 34 MSA s starting in year program (4/1/16-12/31/20)

7 Program Details and Changes Target determined by a blend of the participating hospitals costs and the regional cost (1/3 rd, 2/3 rd, 100%) Discount determined by the participating hospitals Total Composite Score on Quality ( ) Risk/reward capped at 5% PY1&2, 10% in PY3 and 20% in PY4&5 *no payback in PY1 2 Reconciliations - NPRA

8 Working with available data Making use of data you already have

9 Data files available through CJR portal Patient demographics Diagnosis information Acute claims data (includes anchor admission, readmissions, LTAC) HHA claims data SNF claims data (includes swing bed) Physician and Anesthesia claims data Part B claims data Rehab claims data

10 Evaluating Cost Compared to Target

11 ALOS and Profitability by Physician

12 Post Acute Impact on Target Price

13 What s wrong with this picture? Using other data of take it a step further

14 ALOS and Variance by Physician

15 Variance by Post Acute Provider

16 Variance by Discharge Status Code

17 Standard Analytic Files (5 years) Inpatient, Outpatient, SNF, HHA, Hospice and Physician Roughly 12M Inpatient claims, 160M Outpatient claims, 5M SNF, 6M HHA and millions of hospice and physician claims (per year) Deidentified at the patient level but contain enough demographic information to analyze meaningful trends Allows you to take the provider specific CJR/EPM data provided by CMS analyze it at the regional and national levels

18 ALOS and Variance by Physician

19 ALOS and Variance by Physician

20 Variance by Post Acute Provider

21 Variance by Post Acute Provider

22 Variance by Discharge Status Code

23 Variance by Discharge Status Code

24 Moving beyond the CMS data

25 Regional and National Benchmarking LOS Comparison Average (with fracture) 469 (no fracture) 470 (with fracture) 470 (no fracture) Facility W/S Central National

26 Variance of DRG Transfers 80% Qualified DRG Transfer Episodes % 60% 50% 40% 30% 20% 10% 0% Facility National W/S Central

27 MCC Frequencies

28 Maria talks about quality data

29 Impact of Quality

30 Quality Trends

31 Using technology to fill in the gaps

32 Shortcomings of CMS Data The data CMS provides is somewhat complex taken in the format they provide Negative trends, once published, may take years to correct Providers need a tool to harnesses people s natural ability to spot visual patterns, reveal opportunities, identify trends and most importantly, make data-driven decisions. There is no ability for advanced planning

33 Drilling down

34 Drilling down

35 BESLER EPM Scorecard Acute facility scorecard listing key metrics to help providers understand their risk when it comes to Medicare s CJR programs Predicts CMS total spend Provides a facility with their quality scores Provides data on their total at risk dollars under the mandatory program

36 Sample Hospital Scorecard

37 CMI and the effect on EPM CMS assigns a unique weight to each DRG The weights are intended to account for cost variations between different types of treatments A hospital case mix index, or CMI is the relative average of all cases assigned a DRG for a given year and is a good metric to determine how CMS adjusts DRG payments to the facility Besler uses the national benchmark data to calculate a CMI for each DRG combination allowing our analysts to determine if a specific diagnosis is being reimbursed at a reasonable rate compared to other facilities within the comparison region

38 Heatmap

39 Tying it all together

40 Estimate your Composite Quality Score before Reconciliation Start with the raw data from hospital compare Calculate the weighted value and national percentile per the Final Rule Create a final score card that shows the expected Quality Category

41 Ely will talk about data and such

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43 Thank you Learn more at