Payer Channel Forecasting and Analysis. Patrick J. Park, PharmD, MBA Director, Business Decision Support Daiichi Sankyo, Inc.

Transcription

1 Payer Channel Forecasting and Analysis Patrick J. Park, PharmD, MBA Director, Business Decision Support Daiichi Sankyo, Inc.

2 Disclaimer The views and opinions expressed in this presentation are those of the presenters and should not be attributed to Daiichi Sankyo, Inc.

3 Agenda Health care and Payer Landscape Impact on GTN Account Level Forecasting Top-down Forecasting Bottoms-up Forecasting Communication

4 Poll Question #1 How much was the Total National Health Expenditures in 2013? A. $874 Million B. $1.5 Billion C. $2.9 Billion D. $5.3 Billion

5 Poll Question #2 What % of Total Health Expenditures ($2.9B) account for Prescription Drug Cost? A. $145 Million (5.0%) B. $271 Million (9.3%) C. $351 Million (12.1%) D. $400 Million (13.8%)

6 Health Care Costs are Rising Total National Health Expenditures = $2.9B in 2013 $2.9B Prescription Drug cost continues to rise. It accounts for 9.3% of total health expenditures $940M (32%) $587M (20%) $271M (9.3%) SOURCE: Peterson-Kaiser Health System Tracker - Healthsystemtracker.org Accessed October, 2015 Rest of the health expenditures include dental, other professional services, home health, nursing care, and other state and local administration cost.

7 Mergers/Acquisition Trends Benefits: To build volume and control costs in health care Improved quality and patient access to care Potential cost reduction Declining reimbursements, increased regulatory demands, and changes in health care act lead to consolidation trend in hospitals and health systems, physicians, and payers There were 25% more health system mergers during than during In Reality: Most studies found that hospital consolidation generally results in higher health costs Multihospital owned physician groups was 19.8% higher than independent, physician owned groups Physician-hospital consolidations do not lead to either improved quality or reduced costs Consolidation results in efficiencies and quality is unclear Martin Gaynor, director of the FTC Bureau of Economics said, We ve seen almost no evidence of real efficiency claims. That doesn t mean it won t happen, but the most recent evidence doesn t support those claims. SOURCE: AAOS Now April 2015 Issue The Synthesis Project New insights from research results June 2012

8 Impact on Hospital Mergers SOURCE: - Accessed October 2015

9 Payer Mergers/Acquisition July 3 announcement that private health insurer Aetna is acquiring rival Humana for $37 billion was the culmination of a frenzy of speculation about consolidation in the US private health insurance industry. Hillary Clinton stated, this is a serious concern and balance of power is moving too far away from consumers Later that month, Anthem announced its long-awaited $54.2 Billion acquisition of Cigna, a bid that took numerous twists and turns before terms were finalized. United Health to buy Catamaran for $12.8 Billion in Cash CVS to buy Omnicare in $12.7 Billion Pharmacy Expansion Deal SOURCE: - Accessed October Accessed October Accessed October 2015

10 Payer Mergers/Acquisition More efficient operations Eliminate duplicative admin cost Reduce redundancies Aetna expects ~$1.25 Billion in cost saving by 2018 with Humana merger Anthem expects ~$2 Billion saving with Cigna acquisition Stronger buying power Improve rate negotiations with providers (pharma, physician) Better clinical management Potentially invest in clinical capabilities Develop cost-effective quality care

11 PBM Mergers/Acquisition SOURCE: Health Strategies Group Access online in October 2015

12 Impact on GTN Sales % Deduction Sales % Deduction Sales % Deduction Gross Sales Commercial % % % Part D % % % Medicaid % % % Coverage Gap % % % Other Financial Adjustments % % % Net Sales % % % GTN 73% 71% 60%

13 What is impacting GTN? Increased in Commercial and Part D rebates WAC Price Increase coupled with Price Protection Government channels with regulated pricing with fixed price contracts Consolidated Payers requesting higher rebates Competitive contracts Government is becoming one of the largest payers Medicare Part D (Coverage Gap) Tricare/ PHS 340B expansion, etc Miscellaneous Returns/ Coupon/ Wholesaler Fees

14 Account Level Forecasting Constant changes in the payer landscape requires to forecast at the account level in order to provide additional visibility into forecast assumptions Payer consolidation Live movements among payers Easy to consolidate to the channel or brand level to see the impact on other channels Clear communication tool with variance analysis

15 Account Level Forecasting Model Flow Actual Gross Sales/Rebates/TRx by Channel/Account TRx Forecast* by Account Change in Access (T2/T3/NC/etc) * How do we forecast TRx? Dollarize TRx using WAC / Unit & Units / TRx Consider Impact of Price Protection Review Contracts to Forecast Rebate Rates Gross Sales Forecast by Account Rebate Rates Forecast Forecast Rebate Dollars Net Sales Forecast by Account How do we forecast TRx by Account?

16 Account Level TRx Forecasting Apply brand growth rates to each and all accounts Apply any formulary status change from T2 1 of 3 to T2 1 of 2 or PB to NPB, etc Review each individual accounts trend line with historical data Apply any formulary status change from T2 1 of 3 to T2 1 of 2 or PB to NPB, etc Aggregate all accounts Reconcile to the top line brand forecast

17 Account Level TRx Forecasting (Top Down) Actual Forecast Total Commercial Account BLUE Account RED Account GREEN Apply overall growth rates to all accounts This creates deviation from its own trend Even though we have the correct rebate rates, the actual rebate dollars can vary significantly from what we accrue

18 Account Level TRx Forecasting (Bottoms Up) Actual Forecast Sum of all Account Trend Total Commercial Account BLUE Account RED Account GREEN Forecast each account individually based on historical trend Aggregate all accounts and compare to the top line forecast Adjust individual account trend after reconciliation

19 Account Level TRx Forecasting Depends on product lifecycle and stage of contract cycle, adapt to bottoms-up/ top-down approach Consider complexity of bottoms-up approach and how much it will contribute to the accuracy of GTN Require greater collaboration between demand forecasting, contract analytics, managed market, pricing strategy, and finance Consider the impact on rebate accrual Variance analysis and communication

20 Forecasting Assumptions Actual Actual Forecast Product A TRx 1.2M 1.26M 1.36M Product Growth (YoY) 2% 5% 8% CVS Health T3 T2 1 of 3 T2 1 of 3 ESI T3 T3 T2 1 of 2 UHC / OptumRx T3 T2 1 of 3 T2 1 of 2 Prime T3 T3 T3 Aetna T3 T2 1 of 3 T2 1 of 2 WAC Price Increase Apr 5%; Sep 5% Apr 5%; Sep 5% Apr 5%; Sep 5% GTN% 75% 70% 65% Gross Sales $100M $120M $130M Net Sales $75M $84M $84M Validate assumptions and get an alignment from the team Build a story to explain changes in assumptions

21 Forecasting Assumptions Actual Actual Forecast Forecast Forecast Gross Sales $100M $120M $130M $140M $150M Net Sales $75M $84M $84M $89M $92M Market Growth +5% +7% +8% +8% +8% Market Share 15% 16% 17% 18% 18% TRx Growth +5% +8% +9% +10% +10% Price / Unit $5.12 $5.63 $6.20 $6.81 $7.50 WAC Price Increase Apr 5%; Sep 5% Apr 5%; Sep 5% Apr 5%; Sep 5% Apr 5%; Sep 5% Apr 5%; Sep 5% GTN% 75% 70% 65% 165% 265% A&P $20M $22M $23M $24M $25M Sales Cost $30M $33M $35M $37M $38M

22 Net Sales Bridge

23 Final Thoughts GTN Forecasting is complex Forecasting is never correct Document assumptions Explain variances Communications Cross functional alignment

24 Questions?