Session 7 PD, Specialty Pharmacy Pipeline Update. Moderator/Presenter: Kevin James Trapp, FSA, FCIA, MAAA

Transcription

1 Session 7 PD, Specialty Pharmacy Pipeline Update Moderator/Presenter: Kevin James Trapp, FSA, FCIA, MAAA Presenters: Kathryn Bronstein, Ph.D., RN Patrick Gallagher, FSA, FCAS

3 Specialty pharmacy will represent 49% of total pharmacy spend by 2019 US Pharmacy Market Sales by Type (Actual), (Forecast) Sales $B Specialty Other Significant Amount of New Specialty Launches in (23%) (24%) (25%) (28%) (30%) 124 (33%) 144 (37%) 166 (41%) 184 (44%) 203 (47%) 220 (49%) (77%) 240 (76%) 245 (75%) 230 (72%) 232 (70%) 250 (67%) 245 (63%) 239 (59%) 234 (56%) 229 (53%) 229 (51%) Source: Sales estimates from IMS Market Prognosis, IMS Institute. Growth rates from from Artemetrx Walgreen Co. All rights reserved. Proprietary and confidential information. 2

4 U.S. specialty drug spending is predicted to more than double between 2016 and 2020 $401.7B $192.2B $87.1B 121% increase from % increase from PwC Health Research Institute. Medical cost trend: behind the numbers chart-pack.pdf. Published June Accessed September 2, Walgreen Co. All rights reserved. Confidential and proprietary information. 3

5 Dramatic growth of U.S. Specialty Pharmacy spend is creating payer challenges Stakeholders in specialty care identify a variety of complex specialty drug management challenges 1 Specialty drug management challenges Managing oncology Determing value of therapy Managing appropriate use of therapy Coordination across pharmacy/medical benefits Pipeline and new product approvals Shift in site of service* 66% 60% 60% 56% 53% 79% 0% 20% 40% 60% 80% 100% Percentage of plans (N=70) *From provider office to hospital outpatient department. 1. EMD Serono. EMD Serono Specialty Digest, 11 th Edition. Managed Care Strategies for Specialty Pharmaceuticals Walgreen Co. All rights reserved. Proprietary and confidential information. 4

8 Modeling Aggregate Drug Reinsurance

9 Specialty Drug Risk Varies by Payer and Product Specialty Drug Financial Risk for non-government Payers Employer ACO Insurer Group Exchange Medicare Medicaid Integro USA, Inc.,

10 Buying reinsurance: Protect your Frequency or Severity? Large employers purchase stop-loss insurance to protect against catastrophic claims, or severity events. The uncertainty surrounding newly branded drug pricing puts employers at risk of many claimants whose costs are correlated, or frequency events Example: Self-insured employer plan 20,000 members $100M annual budget 100 Year Modeled Severity Event: $5M additional claims 100 Year Modeled Drug Frequency Event: $10M additional claims Integro USA, Inc.,

11 Coverage Options for Specialty Drug Reinsurance Whitelist Blacklist Newly Branded All Pharmacy Specific Excess Integro USA, Inc.,

12 Modeling Aggregate Specialty Drug Risk Timing of release Price Utilization Interaction with other therapies Integro USA, Inc.,

13 Simulation Modeling of Aggregate Specialty Drug Risk Simulation Model for Specialty Rx 1. Drug Facts Source Drug Name Rociletinib (Clovis Oncology) Current Status NDA Filed Drugs.com Anticipated Approval 6/28/2016 Drugs.com Classification Breakthrough TherapyPGx Used for Non-small cell lung cancer (NSCLC). EGFR T790M mutation positive Existing Treatment Tarceva, Gilotrif Express Script Report 2. Assumptions Expected Value Distribution Source (a) Cost $100,000 per year Normal Distribution with CV=0.2 Express Script Report (b) Time available on market in months Uniform between 0 to 8 Months From Anticipated Approval (c) US New Lung Cancer cases 224,210 per year Express Script Report (d) % of NSCLC Cases 85%-90% Cancer.org (e) % of Developing EGFR T790M mutation 5% MyCancerGenome.org (f) Patient Average Life 2 Year <5% 5 year survival rate (g) Frequency of Patients 60 per million (c ) x (d) x (e ) x (f) / US Population 3. Simulation Model Expected Value (h) Population Size 40,000 (i) % of Patient using Rociletinib 60% 4. Simulation Model Output Percentile Drug Cost 50% 27,000 60% 40,000 70% 55,000 80% 75,000 90% 114,000 95% 153,000 Integro USA, Inc.,

14 Example Whitelist Simulation Model The first method of delivery for Specialty RX reinsurance is a targeted model, wherein the reinsurer and broker will maintain a whitelist of drugs that might be introduced in the contract period and could materially impact the reinsured s drug costs for the year. Under this model, only agreed upon drugs would be covered. This product is not intended to eliminate increasing drug costs. Instead, the product will address newly branded drugs that might cost catastrophically more than expected. In order to price the risk, a sample benchmark report is generated, which identifies upcoming pipeline drugs and the likely cost of these to the specific client. In this sample benchmark report, we calculate that newly branded drugs will cost this health plan $33.7 million net of its specific reinsurance. This is based on assumptions about: the future annual cost of each drug an estimate of how many patients in the plan s population suffer from this condition (determined by looking at historical use of competing therapies and/or macro data about the prevalence of a condition) an estimate of how many patients will actually be treated during the future period Integro USA, Inc.,

15 This page left intentionally blank Integro USA, Inc.,

16 Estimating Trend Concerns with public studies Motivation for bias Timing Population Skewness of the distribution Known unknowns Legislative risk Population specific risk Prior authorization protocols Consumer incentives Advertising campaigns Pricing risk Integro USA, Inc.,

17 Takeaways Stop-loss buyers can more efficiently transfer risk by considering both severity and frequency risk When aggregate stop-loss is expensive, aggregate drug risk (re)insurance is a good complement to specific stop-loss. Reinsurance contracts vary in the list of drugs covered and ground-up vs. excess Ground-up modeling of individual named drugs is difficult but lends itself well to simulation models PBMs publish good information to help parameterize models, but it is important to know their shortcomings Integro USA, Inc.,

18 Reinsuring Rx Risk Kevin Trapp, FSA, MAAA 007PD Specialty Pharmacy Pipeline Update 6/15/2016

19 Reinsuring Rx Risk - Key Considerations Issues medical reinsurers need to evaluate when approaching Rx aggregate exposures Considerations Key Questions 1 Capacity And Risk Appetite What financial exposure to Rx Aggregate losses is the organization willing to take? 2 3 Credibility of Experience Trend Assumption What is the variability in Rx excess layer loss projections? Can better estimates be obtained by incorporating other information? How reliable are publicly available trend reports? Are there biases in the trend projections? Are Rx claims comparable to ground up Rx trends? 4 Volatility What are the parameter risks you are being exposed to? 18

20 1 Capacity and Risk Appetite Evaluate financial risk across all Rx reinsurance treaties Consideration in evaluating risk in Rx reinsurance Rx trends are correlated between populations Unanticipated adoption of a blockbuster drug may create losses across all treaties in the same year Blockbuster drugs affect the entire nation at once Reinsuring different geographic areas does not reduced the risk Financial impact of a blockbuster drug would vary between treaties based upon the prevalence of condition being treated Reinsurance Treaty #1 106% 104% 102% 100% 98% 96% 94% 92% 98% Drug Does Not Launch Reinsurance Treaty #2 96% 94% Reinsurance Treaty #3 Illustrative impacted of a new drug launch 106% 104% 102% 100% 98% 94% 92% 106% 104% 102% 100% 98% 96% 94% 92% Drug Does Not Launch 98% Drug Does Not Launch 102% Blockbuster Drug Launches 104% Blockbuster Drug Launches 105% Blockbuster Drug Launches Expected claims cost Expected claims cost Expected claims cost 19

21 2 Credibility of Experience Determine the reinsurance organization s approach to credibility for this exposure Current Year s Experience Although ground up Rx claims experience is typically fully credible with only a few thousand member months, the large deductible significantly reduces the credibility of the experience Seasonality of the data and memberships changes may also impact the credibility of the data Multiple Year s Experience Credibility may be increased by including multiple year s of experience This requires developing Rx trend assumptions for prior years Due to new introductions of drugs and patent expirations, prior year s data will be less relevant Manual Rates There is no commercially available rate manual for Rx excess layer aggregate exposure Creating your own manual is difficult as data needs to be standardized for a variety of factors It will be difficult to assess to applicability of the manual due to the difference in prevalence of certain diseases between the manual and a particular client Careful analysis is needed to construct the organization s credibility approach

22 3 Trend Assumptions Development of trend assumptions Trend Assumption Development Process Step #1 Review published specialty Rx trend to develop an Rx trend assumption Step #2 Review the population s enrollment information to determine if the enrollment mix has changed, requiring a demographic adjustment Step #3 Review changes to the clients PBM to assess the impact on trend. (Note: the impact on the excess layer may differ from the ground up impact) Step #4 Review the clients changes to its formulary to determine if a change to the trend is warranted Step #5 Other adjustments as needed Outcomes Transparent and easily explainable trend Trend reflects the specific characteristics of the population 21

23 3 Trend Assumptions Development of trend assumptions Population Specific Trend Adjustments ILLUSTRATIVE 20.0% 18.0% 16.0% 14.0% 12.0% 10.0% 8.0% 6.0% 4.0% 2.0% 17.0% 0.5% -1.0% 0.1% 2.0% 18.6% 0.0% Consensus Specialty Rx Trend Enrollment Mix Shifts PBM Change Formulary Change Other Adjustments Pricing Trend Step 1 Step 2 Step 3 Step 4 Step 5 Trend 22

24 4 Volatility In order to assess the exposure around the Rx claims projection a simulation of claims projections needs to be run Considerations and assumptions Simulated Outcomes 1. The Rx claims cost distribution: If using a manual distribution, the distribution needs to be scaled to fit to the historical experience 2. Parameter Risk The assumed error in the Rx trend assumption The parameter risk may be difficult to quantify Distribution 18% 16% 14% 12% 10% 8% 6% 4% 2% 0% Simulated Outcomes Aggregate Claims ILLUSTRATIVE Simulating claims experience to understand of the range of outcomes 23

25 Rx Aggregate Reinsurance Pricing Process A B C Estimate the the Annual Rx Claim Simulate the Claims Volatility Price various attachment points Claims experience rate: Roll up claims by individual claimant Estimate completion for most recent years Set claims distribution and parameter risk assumptions Trended to the effective year Apply coverage interval Apply weighting factors for each year expected claims Blend with manual rate (if applicable) Set attachment points Price risk volatility around attachment points Provide client with various options Provide the client with various attachment point and premium combination options 24

26 A Estimate the Annual Rx Claim Development of claims projection Roll up Rx scripts by individual claimant Trended to the effective year Apply coverage interval Deductible Annual Limit Projected Claims Process is repeated for each year of historical claim experience. Weighting factors are applied to each year s expected claims to arrive at the claim projection 25

27 B Simulate the claims volatility Development of aggregate distribution Start with Single risk continuance curve consistent with annual Rx claim projection Step #1 Convolute across the subject population Step #2 Adjust for uncertainty of estimates (parameter risk) Step #3 Apply stress scenarios Distribution 20% 15% 10% 5% 0% Simulated Outcomes ILLUSTRATIVE Aggregate Claims 26

28 C Price various attachment point options Development of aggregate pricing around various attachment points ILLUSTRATIVE Option Attaching Att Point Expected Coverage Reinsurance Expected Corridor PMPM Att. Point Limit Rate PMPM Premium Rate on Line 1 110% M 5.0M $ K 11.0% 2 115% M 5.0M $ K 6.5% 3 120% M 5.0M $ K 4.5% 4 125% M 5.0M $ K 3.0% Option Comparison Attachment Point Increase Reduction in Premium Premium Reduction vs. Attachment Change 1 to 2 0.5M 225K 45% 2 to 3 0.5M 100K 20% 3 to 4 0.5M 75K 15% 3.0% Illustration of claims outcomes with various Attachment Points Increasing the attachment point reduces the premium while also reducing the likelihood of reimbursement The client can weigh the tradeoff between coverage and premium savings 2.5% 2.0% 1.5% 1.0% 0.5% Option 1 Option 2 Option 3 Option 4 Premium Coverage 0.0% 8M 0M 9M 1M 10M 2M 11M 3M 12M 4M 13M 5M 14M 6M 15M 7M 16M 8M 17M 9M 18M 10M 19M 11M 20M 12M 21M 13M Aggregate RX Claims in 250K xs 50K layer 27