Copyright © 2010 SAS Institute Inc. All rights reserved. Sense & Shape Health Care Demand Laura Squier Oct 17, 2011

2 Copyright © 2010, SAS Institute Inc. All rights reserved. I represent SAS and nothing I state should be interpreted as an endorsement on behalf of CMS. The opinions expressed are my own and do not reflect the view of the Centers for Medicare & Medicaid Services, the Department of Health and Human Services, or the United States government.

3 Copyright © 2010, SAS Institute Inc. All rights reserved. Agenda  Why Forecasting is Becoming Imperative  What Capabilities are Required  Case Study – NC Medicaid  Demonstration  Questions

4 Copyright © 2010, SAS Institute Inc. All rights reserved. The Ability to Sense and Shape Demand  Sense –  Determine what is likely to happen  Shape –  Identify methods, make changes to impact the demand or supply of health care services  Proactively drive demand for health care services, run scenarios to test the impact of various policy changes Enables CMS to Achieve Mission, Vision and Goals

5 Copyright © 2010, SAS Institute Inc. All rights reserved. Why Sense and Shape Demand?  Changing Reimbursements and Payments  Health consumers make deficit fight personal - Oct 4, 2011, Reuters  Attorney advocate group works toward extending Medicare - October 4, 2011 – Daily Local News  Drug lobby says Medicare drug proposal will cost jobs -Oct 4, 2011, The Philadelphia Inquirer  Changing Utilization  Hospital Readmission Rates on the Rise in Older Adults: Study - Oct. 4 - HealthDay News  Innovative Diabetes Prevention Program Available for Free to Overweight Older Adults With Prediabetes in Metro Atlanta – Sept 28, PRNewswire  So-called Medicaid fix likely to create other problems – Oct 5, THE OLYMPIAN Everything Boils down to Quality, Access To, and Cost of Care If We Can Forecast and Simulate, We Can Plan

6 Copyright © 2010, SAS Institute Inc. All rights reserved. Changing Reimbursements and Payments  Forecast how a change will impact payout  Forecast overall payments  Forecast payments for individual services and procedures  Forecast expected reimbursement rates  Estimate the impact on demand, expenditures, quality of care and outcomes  Run scenarios to understand the impact of policy changes  Identify opportunities to make changes  Forecast expected rate increases  For a given plan, estimate the expected rate increase given historical rates, patient population, demographics, coverage, interventions…

7 Copyright © 2010, SAS Institute Inc. All rights reserved. Changing Utilization  Aging population  Increasing chronic diseases  Epidemics  Fraud Use Cases  Forecast expected overall utilization of healthcare services  Forecast at individual service level  Use insights to set policy and introduce new programs  Identify areas where utilization is higher than expected  Identify areas where utilization is lower than expected

8 Copyright © 2010, SAS Institute Inc. All rights reserved. What Capabilities are Required?  Ability to automatically develop the best fit forecasts at multiple levels of hierarchy  Service  Procedure  Diagnosis  Provider  Plan  Drug  State  Differentiates between trend, seasonality and noise  Not just straight line  Ability to run scenarios to determine the impact of a change  Include Events and Interventions  Changes in policy, outbreaks

9 Copyright © 2010, SAS Institute Inc. All rights reserved. NC Division of Medical Assistance (DMA)  Background  Medicaid expenditures $11B or 15% of state budget  Manually intensive, excel based process w/ 110+ worksheets  Needed management or analytical reporting capabilities  Solution  SAS® Forecast Server for forecasting and and SAS® Enterprise Miner for dimensionality reduction and causality determination  Results/Benefit  Governor accepted 80% of forecasts »Compared to 10% in prior process »Forecasts had low error rates “The results of our study have already had significant positive impact on the DMA budgeting and planning process as SAS Forecast Studio has provided DMA staff with electronic visibility into the details of all Medicaid services.” Katz and Waclawski, “The Effect to Socio-Demographic and Econometric Data on Improving Time Series Forecasting of Medicaid Claim Expenditures by Category of Medical Service in the State of North Carolina”

10 Copyright © 2010, SAS Institute Inc. All rights reserved. NC DMA Project Overview  A forecast is generated for all combinations of variables for each level of the hierarchy – 7,331 total time series.  Targets:  Enrolled Eligibles - number of individuals from the eligible pool who will be enrolled.  Recipients - number of unique enrolled eligibles who will receive services.  Claims Expenditures - total claims expenditure dollars.

11 Copyright © 2010, SAS Institute Inc. All rights reserved. Final Candidate Causal Data Variable List  Eligibles for Recipient forecast (at Program Aid Category level)  Recipients for Claims Expenditure forecast (at Program Aid Category level)  Number of Checkwrite processing days per month  NC_Population_Under_Age_65  NC_Population__Age_65___Older  NC_Personal_Income  NC_Births  NC_Employment__Total_Nonfarm  NC_Net_Migration  Chained_Price_Index__Health_Care  NC_Number_Unemployed  NC_Median_Household_Income  NC_Consumer_Price_Index__CPI_

Copyright © 2010 SAS Institute Inc. All rights reserved. Demonstration

13 Copyright © 2010, SAS Institute Inc. All rights reserved. When is Forecast Server a Fit?  Data  Time series data »1 observation per time period for each level »Preferably at least 7 cycles of the value you want to forecast  Multiple levels of hierarchy  Technology  Currently developing forecasts or looking at trends in Excel  Current ETS users  Need forecasting models to be developed rapidly or updated with little human intervention

14 Copyright © 2010, SAS Institute Inc. All rights reserved. Comparison of Forecasting Methods

Copyright © 2010 SAS Institute Inc. All rights reserved. Questions

Copyright © 2010 SAS Institute Inc. All rights reserved. Thanks