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  • 1 Joyce GF, Escarce JJ, Solomon MD et al. Employer drug benefit plans and spending on prescription drugs. JAMA . 2002;288(14):1733-1739. 2. Fairman KA, Motheral BR, Henderson RR. Retrospective, long-term follow-up study of the effect of a three-tier prescription drug copayment system on pharmaceutical and other medical utilization and costs. Clinical Therapeutics . 2003;25(12):3147-3161.
  • As with any predictive modeling, these need to be validated in the real world.
  • Advantage of difference-in-differences method: any change in control group’s medication acquisition reflects changes unrelated to the copayment while any change in the experimental groups’ medication acquisitions reflects both the (same) naturally occurring change plus the impact of the copayment change
  • **Because the actual Intervention group (UM employees) did not face price changes, their utilization of services should have been unaffected
  • The total value of health can only be derived from the sum of the measures of healthcare and pharmacy costs, and productivity including time-away-from-work (absenteeism, short and long term disability and worker’s compensation) and presenteeism,” according to the UM-HMRC’s director, D.W. Edington.
  • Caution, however, should be taken because the results are not statistically significant and are only of directional value – if at all.
  • Although Pitney Bowes and Asheville have the greatest name recognition as employers that have embraced value-based benefit design, they are not alone—far from it. Here are some other U.S. employers that are using value-based benefit design principles in their companies.
  • STATINS: Vijan S, Hayward RA, American College of Physicians. Pharmacologic lipid-lowering therapy in type 2 diabetes mellitus: background paper for the American College of Physicians. Annals of Internal Medicine 2004;140(8):650–658. ASA: Antithrombotic Trialists' Collaboration. Collaborative metaanalysis of randomised trials of antiplatelet therapy for prevention of death, myocardial infarction, and stroke in high risk patients. BMJ 2002;324:71–86. Tight BP Control: Annals review – Sandeep and Rod Tight Blood Glucose Control: ACCORD Metformin in Overweight T2DM: Effect of intensive blood-glucose control with metformin on complications in overweight patients with type 2 diabetes (UKPDS 34). UK Prospective Diabetes Study (UKPDS) Group. Lancet 1998 Sep 12;352(9131): 854-65. ACE/ARBs: HOPE Study Investigators. Effects of an angiotensin-converting enzyme inhibitor, ramipril, on cardiovascular events in high-risk patients. New England Journal of Medicine 2000 342: 145-153. HOPE Study Investigators. Effects of ramipril on cardiovascular and microvascular outcomes in people with diabetes mellitus: result of HOPE study and MICRO-HOPE substudy. Lancet 2000 355: 253-259.
  • Caution, however, should be taken because the results are not statistically significant and are only of directional value – if at all.
  • Caution, however, should be taken because the results are not statistically significant and are only of directional value – if at all.
  • Mort is lower in high comp areas for hip fracture, so its doesn't fit pattern described in slide.
  • Caution, however, should be taken because the results are not statistically significant and are only of directional value – if at all.
  • Intervention population consists of A and B for analyses requiring only pharmacy claims (adherence and uptake). For analyses requiring additional data (non-pharmacy claims, survey data, etc.), intervention group consists of B alone. For all analyses, control group consists of C.
  • All bullet quotes from Fendrick slide presentation – Value-Based Insurance Design –Lessons Learned –accessed on UM Center for VBID website First bullet also in Fendrick –Chernew publication in reference source documents – 01/06

Rosen slides Rosen slides Presentation Transcript

  • Value-Based Insurance Design: Preserving Quality While Containing Cost Presented at the Leonard Davis Institute, University of Pennsylvania April 3, 2009 Funding from University of Michigan Health System, Hartford Foundation, and the Michigan Diabetes Research Training Center (NIDDK) Allison B. Rosen, MD, ScD University of Michigan Center for Value-Based Insurance Design
  • Outline of Talk
    • Background
    • A story of serendipity (and a bit of hard work)
    • UM intervention study – primary outcomes
    • Preliminary secondary analyses
    • Policy implications
      • Locally
      • More broadly
  • Health Care Cost Crisis
    • “ The nation’s long-term fiscal balance will be determined primarily by the future rate of health care cost growth.”
    • -- Peter Orszag, Director, Congressional Budget Office Testimony before Senate Budget Committee, June 21, 2007.
  • Value of Care is Poor
    • Substantial underutilization of high value health care services
    • U.S. adults receive only about half of recommended care*
    • For some chronic diseases, like diabetes, patients get fewer than half of needed clinical services*
    *McGlynn et al. N Engl J Med, 2003.
  • Fundamental Health Policy Question
    • How do we organize and finance the health care system to achieve maximum value for what we spend?
    • ***Not: how do we save money?
  • Health Care Cost Crisis: Remedies Must Recognize Cost / Quality Tradeoff
    • Financial incentives to moderate utilization will be a fundamental part of the solution
    • Yet, if not carefully aligned, they may worsen already pervasive problems in quality of care
  • Today’s Talk Will Focus on Chronic Medications
  • Recent Drug Copayment Trends Based Largely on Cost
  • Different Patients Get Different Benefits from Medications NNT to prevent CV event Ellis JJ. J Gen Intern Med 2004;19:639-646. Example: Number needed to treat with statins to prevent one cardiovascular event
  • No Difference in Statin Compliance Stratified by Prevention Category Ellis JJ. J Gen Intern Med 2004;19:639-646. Secondary prevention cohort Primary prevention cohort
  • Statin Discontinuation Rates Stratified by Mean Prescription Copayment Ellis JJ. J Gen Intern Med 2004;19:639-646. $0 to <$10 $10 to <$20 >$20 Copay amount was the most important predictor of drug discontinuation rate No difference between primary and secondary prevention groups
  • Does Cost-Related Medication Underuse Matter?
    • For Employers:
    • Shifting costs to employees reduces employer drug spending
    • However, evidence growing that overall costs may increase
    *For excellent review, see Goldman et al., JAMA 2007;298:61. Fendrick AM, et al. Am J Managed Care, 2001; Rosen AB. Med Care, 2006.
    • For Consumers:
    • Growing evidence* shows that cost-related underuse:
      • Increases adverse outcomes (chronically ill & poor most at risk)
      • Increases health care costs in some cases
  • Getting Services to People Who Need Them: Should the Patient Decide?
    • If increased cost sharing decreases the use of essential medications & leads to worse outcomes, is it appropriate to place the burden of weighing the benefits and costs of medical interventions on the patient?
    • If not, the system should provide some guidance and incentives to promote better decisions
  • Getting Services to People Who Need Them: Value-Based Insurance Design
    • Value-based insurance design has been proposed to realign incentives for value
    • Cost sharing is based on likelihood of benefit, not (solely) the acquisition cost
      • The greater the benefit, the lower the co-pay
    • Such a system would provide financial incentives to targeted patients most likely to benefit from specific therapies
    Fendrick AM. Am J Managed Care, 2001. Rosen AB. Med Care, 2006. Chernew M. Health Affairs, 2007.
  • Numerous VBID Experiments Ongoing: But in Need of Rigorous Evaluation
    • Several employer-based experiments underway with various forms of VBID for different diseases and/or drugs
      • These efforts are largely coming out of the private sector
    • Reported ‘results’ are excellent  over a dozen companies reporting a “positive financial return on investment (ROI)”
    • Few rigorous evaluations exist to support these claims
    • Two basic approaches in use
      • Target services that are high value (e.g., beta blockers)
      • Target patients with select clinical diagnoses (e.g., diabetes)
    • Most employers have taken services approach
    • Example: Marriott International
      • Waived copays for generics and cut branded copays in half
      • Adherence increased from 2% to 4%
      • Medication costs increased -> medical claims decreased by roughly same amount
    • Rigorous evaluation needed of the second flavor of VBID
      • Targeting specific services to specific patients
    Targeting is Critical to Attain Value
  • Benefit Based Copay for ACE-Inhibitors and Angiotensin Receptor Blockers for UM employees with Diabetes Proposal to the Michigan Healthy Community Initiative Task Force July 14, 2005
  • Why Diabetes? Sources: ADA. Economic costs of diabetes in the U.S., 2007. Diabetes Care. 2008;31:1-20. CDC. Diabetes Public Health Resource. http://www.cdc.gov/diabetes/ Accessed on Oct 7, 2008.
    • Almost 24 million Americans have diabetes (90–95% Type 2)
    • Diabetes and its complications are a leading source of morbidity, mortality, and costs, as well as lost productivity
    • In 2007, direct medical costs of diabetes were $116 billion, & indirect costs (from reduced productivity) totaled $58 billion
    • Several therapies markedly reduce the risk of complications
    • Yet, these therapies are underutilized in practice
    • Increasing out-of-pocket (OOP) costs an important cause
  • Value Based Insurance Design (VBID) Example: Predictive Modeling
    • Diabetes Mellitus*
      • Medicare first-dollar coverage (co-pays waived) of ACE inhibitors resulted in nearly one million life years gained and a net savings of $7.4 billion over the cohort lifetime
    *Rosen AB, et al. Ann Intern Med. 2005;143:89.
  • Proposal for a Value-Based Insurance Design for UM Employees with Diabetes Michigan Healthy Community Initiative Task Force February 15, 2006
  • Timing is Everything
  • FOD Objectives and Outcomes
    • Objectives:
      • To examine the impact of targeted value-based copayment reductions on the use of evidence-based medications by UM employees and dependents with diabetes
      • To successfully implement VBID program in real world setting
    • Primary outcomes:
      • Medication uptake (or utilization)
      • Medication adherence
    • Secondary outcomes: Health care utilization & expenditures
  • FOD Intervention
    • Targeted copayment reductions for evidence-based therapies:
      • Antihypertensives (lower blood pressure)
      • ACE-Inhibitors & Angiotensin Receptor Blockers (ACE/ARBs)
      • Statins (lower cholesterol)
      • Glycemic agents (lower blood sugar)
      • Antidepressants
    • VBID designed to maintain underlying incentive structure:
      • Tier 1 (Generics) Copays waived
      • Tier 2 (Preferred Brand) Copays reduced 50%
      • Tier 3 (Non-preferred brand) Copays reduced 25%
  • Original Study Timeline July 1, 2005 – June 30, 2007 Q5 Q6 Q7 Q8 Q1 Q2 Q3 Q4 6/30/07 7/1/05 6/30/08 7/1/04 July 1, 2006 FOD Intervention Q5 Q6 Q7 Q8 Q1 Q2 Q3 Q4 **Disenrollment rates increased after M-CARE sale announced. X Sale of M-CARE to BCN announced X BCN officially takes ownership of M-CARE UM Open Enrollment Control Firms Open Enrollment Windows
  • Revised Timeline Used for Evaluation July 1, 2005 to June 30, 2007 Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 6/30/07 7/1/05 6/30/08 7/1/04 July 1, 2006 FOD Intervention Q5 Q6 Q7 Q8 Q1 Q2 Q3 Q4 X POST-PERIOD 7/1/06–6/30/07 PRE-PERIOD 7/1/05–6/30/06 Look-back window to ID study population X Evaluation Window
  • Study Design and Population
    • Study Design: Interrupted time series with concurrent control group
    • Intervention Group (N = 1777)
      • UM employees and dependents with at least one glucose lowering drug filled in the prior year
      • Continuous enrollment in drug benefit for the period of interest
    • Control Group (N = 3273)
      • Employees & dependents of other (non-UM) employers, enrolled in M-CARE, and meeting same inclusion criteria as intervention group
    • Sample Identification: Separate for PRE and POST periods
      • Example: Intervention group sample in PRE period (7/05 – 6/06) includes:
        • UM actives with glycemic agent filled in 7/04 – 6/05 (year before PRE period)
        • Continuously enrolled from 7/05 to 6/06 (entire year of PRE period)
  • Analytic Approach
    • Difference-in-Difference Regression Model
      • Means of predicted values for intervention and control groups
        • Uptake: measured once in PRE year & once in POST year
        • Adherence: at quarterly intervals before and after program
      • Bootstrapped SEs for differences & difference-in-differences
    • Generalized Estimating Equations (GEEs)
      • Accounts for correlation of multiple measures in same person
    • Control Variables:
      • Baseline age, gender, employee/dependent, comorbidity score, neighborhood median household income, # medications
  • Difference-in-Difference Framework Co-Pay Reductions Begin Pre-Period Post-Period Medication Adherence Feb 2002 EFFECT = Difference in Difference (D-in-D) Diff . Diff. 50% 100% Control Group Co-Pay Reduction Group (FOD)
  • Definitions – Primary Outcomes
    • Utilization: At least one pharmacy fill of the medication at any time during the one year period
      • Pre – year: 7/1/05 to 6/30/06
      • Post – year: 7/1/06 to 6/30/07
    • Adherence: Use prescription and days supplied data to assess days with available medications per quarter (Medical Possession Ratio, MPR)
      • Adjust for partial eligibility over the quarter
      • Adjust for inpatient admission
      • Adjust for medication switching
  • Standard Adherence Approach This group is ignored regardless of any indications for treatment Standard approach requires at least one pharmacy claim to calculate adherence.
  • Focus on Diabetes: Baseline Characteristics *Median household income by zip code **Significant at p<0.05   Evaluation POST Group   Intervention Control Sample Size 1777 3273 Female Gender 57.6% 54.0%** Mean Age 46.2 46.8 Employee 63.0% 64.2%** Child 4.7% 4.6% Spouse 30.8% 30.8% Other 1.4% 0.4% Income* $55,447 $55,608 Charlson Score 1.43 1.46
  • FOD Intervention Significantly Increased Uptake of Medications in All Drug Classes *All significant (p<0.001) RELATIVE UPTAKE INCREASED BY 5% TO 9% Baseline Uptake (FOD) Absolute Increase % reduction in non-users Metformin 65.4% 3.2% 9.1% ACE/ARB 55.0% 4.7% 10.4% Statins 55.9% 5.2% 11.8% SSRIs 22.0% 1.8% N.A. 0 2 4 6 8 10 Metformin ACE/ARB Statins SSRIs Increase in Uptake (%)
  • FOD Intervention Increased Adherence to the Highest Value Medications (ACE/ARBS & Statins) *NS, ◊ p<0.001, † p=0.067 ADHERENCE TO ACE/ARBs & STATINs INCREASED SUBSTANTIALLY Baseline MPR (%) Absolute Increase in MPR (%) % Reduction in non-adherence Metformin* 71.3% 2.5% 8.6% ACE/ARB ◊ 82.3% 7.2% 40.6% Statins † 78.3% 4.1% 18.6% SSRIs* 69.0% 5.1% 16.5% 0 2 4 6 8 10 Metformin ACE/ARB Statins SSRIs Increase in Adherence (%)
  • Secondary Outcomes: Costs
    • Expenditures
      • Pharmacy, non-pharmacy, total
      • Expenditure analyses complicated by co-interventions
        • I.e. other policy changes occurring during the study time frame which impact UM expenditures but not controls’
  • Unanticipated ‘Co-Interventions’ Made Evaluation of Actual Costs Difficult Q1 Q2 Q3 Q4 6/30/07 7/1/05 July 1, 2006 FOD Intervention *Intervention group OOP costs unaffected; evaluation ∴ applied industry standardized unit prices to changes in utilization due to FOD intervention Q5 Q6 Q7 Q8 OOP = Out-of-pocket UM PBM Renegotiated (Pharm Costs ) 1/1/06 BCN Pricing Went Into Effect (Non-pharm Costs ) 1/1/07
  • Focus On Diabetes Financial Effects  Very Preliminary $0 $200 $400 $600 $800 Intervention Control Intervention Control Mean Quarterly Expenditures ($ per member per quarter) Pharmacy Spending Non-Pharmacy Spending $63 $35 – $112 – $95 $28 – $18 Pharmacy was a little more costly -Diff-of-Diff +$28 Non-Pharmacy was a little less costly -Diff-of-Diff –$18 Overall was a little more costly -Diff-of-Diff +$10 Preliminary Story: *Note: Cost estimates are per member per quarter pre post pre post pre post pre post
  • Focus on Diabetes: Conclusions
    • Targeted co-pay reductions increased uptake of medications
    • Among those on the medications, non-adherence rates declined substantially for ACE/ARBs and statins
    • VBID-type interventions is a useful adjunct to efforts aimed at increasing patient initiation of and adherence to high value medications
    • Impact on cost remains to be seen
  • Limitations
    • Ideal rate of use is not known
      • Most diabetics should be on statin and ACE/ARB
    • Using ‘supply of medications filled’ as a proxy for adherence may overstate actual adherence
    • Comorbidity measured using claims data may be underestimated
    • ROI not known
  • A Comment on ROI and Cost-Effectiveness
    • Cost-saving: intervention is effective and costs less in the long run than the cost of not intervening
    • Cost-effective: intervention provides a health benefit at an acceptable cost
    • High-value: intervention prevents a significant amount of illness and death and is cost-effective
    Most clinical preventive services are cost-effective; Very few are cost saving
  • Value Based Insurance Design Maximizing Return On Investment
    • Incremental costs of increased use of high value services can be subsidized by:
      • Medical cost offsets
        • Amount saved by preventing adverse events will be directly related to level of clinical targeting
      • Higher cost sharing for services of lower value
      • Enhanced productivity
      • Reduced disability costs
  • What Was the University’s Response?
  • Reporting Results at UM
    • UM the university?
    • Or
    • UM the employer?
  • Reporting Results at UM: Take 2
  • UM as a National Leader of VBID adoption
    • In response to UM program, other employers have adopted programs almost identical to FOD
      • Health Alliance Medical Plan of Illinois
      • Disney Corporation – Abbott Laboratories
      • Quadgraphics – Diabetes America
    • “ Setting an example is not the main means of leading others. It is the only means.”
    • – Albert Einstein
  • Early Approaches to VBID Increased plan sponsor subsidy for several medication classes for diabetics only 2006 Increased plan sponsor subsidy for members on essential drugs. Identify members not on essential drugs for reduced copays. Identify & exclude members with contraindications. 2005 City of Asheville, NC Free medications if adhere to DM program 1997 2002 2006 Increased plan sponsor subsidy for drugs treating asthma, diabetes and hypertension Increased plan sponsor subsidy for diabetes drugs and statins if admitted to ER for heart problem
  • VBID Practitioners . . .
  • How Did Employees Respond?
    • &quot;As a member of the U-M community for nearly 20 years and the mother of a daughter who has suffered from Type 1 Diabetes for 15 years, I celebrate this initiative! Thank you!“
    • “ I was recently diagnosed with Type II diabetes by my primary care physician. Since I already have 4 meds that I fill each month at $20.00 co-pay per month, I couldn't take on two more prescriptions.  She called them into my pharmacy and I never had them filled.  I cannot afford them. I felt it more important to take the Blood Pressure meds.”
  • Which Elements of the Intervention Are Most Important? Number Needed to Treat (NNT) to Prevent One Macrovascular (CVD) Event *Tight glucose control does have important micro vascular benefits (but macrovascular protection higher priority) 40 35 16 14 12 9 Aspirin Statin 2 ry Prevention ACE/ARBs Statin 1 ry Prevention Metformin In Obese Other BP Meds Glycemic Agents * Blood pressure medications with extra CVD & renal benefits Only glycemic agent with macrovascular benefits No evidence of macro vascular benefits (unless A1c ~10) For reference only
  • Annual Cost to Continue VBID for Actives, by Number Needed to Treat (NNT) to Prevent One CVD Event *If a budget threshold is reached, covering all drugs above that line will maximize health benefits relative to costs NNT Drug Costs Cumulative Costs* ACE (HOPE) 9 84-118k — Tight BP Control 10-14 96-121k 180-239 Statins (1 ry ⇒ 2 ry prevention) 14 ⇒ 35 73-119 253-358 Other Lipid Lowering Agents — 18-38 271-396 Metformin in Obese 14-16 87-110 358-506 Other Glycemic Agents NS 68-155 427-661 Antidepressants — 56-96 483-757
  • Preliminary Assessment of Secondary Outcomes of Interest
  • The Adverse Impact of Cost Sharing Is More Pronounces in Vulnerable Groups Chernew, Rosen, Fendrick. JGIM. 2008
  • Could VBID Be a Tool to Reduce Disparities?
  • Income Data
    • Patient household income derived from zip-code matched census data
    • Split into two groups: above and below median household income
    • Comparison by income of:
      • Mean number of medications
      • Medication uptake
  • SES Effect on Mean Number Medications -0.16 -0.12 -0.08 -0.04 0.00 0.04 All Glucose Lowering BP Lowering Change in Mean # Meds by Income Status Intervention Controls
  • Impact of FOD Intervention by Income Status Metformin ACE-ARB Statin SSRI Change in Uptake Due to FOD ( ∆ – ∆ ) Income below mean (Q1-Q2) Income above mean (Q3-Q4) ∆–∆–∆ ∆–∆–∆ ∆–∆–∆ 0% 1% 2% 3% 4% 5% 6%
  • Conclusions
    • Among those with incomes below median, a VBID intervention, significantly increased:
      • Mean number of medications
      • Uptake of three of the four medication classes
    • Among those with incomes above median, the VBID intervention did not have a significant impact
    • Big Caveat:
      • Sample size is small
      • Analyses are prelimary
  • Conclusions To Date
    • Targeted co-pay reductions increased uptake of medications
    • Among those on the medications, non-adherence rates declined substantially for ACE/ARBs and statins
    • VBID-type interventions is a useful adjunct to efforts aimed at increasing patient initiation of and adherence to high value medications and possibly an avenue for addressing disparities?
  • Future Directions
    • Evaluate impact on intermediate outcome
    • Assess for differential impact in other vulnerable populations
    • Evaluate productivity outcomes
      • Work-related disability, absenteeism, presenteeism
    • Continue efforts to educate employers that positive ROI is unrealistic expectation
      • When that fails, revisit importance of productivity measurement
    • Initiating a smoke-free work place intervention at UM
      • Looking for control university
  • The Power of Financial Incentives
  •  
  •  
  •  
  • Extra Slides mean number of medication
  • Intermediate Outcomes
    • Have incomplete lab data on cohort
    • Analyses not prespecified
        A1c LDL FOD Diff   -0.30 -5.68 Control Diff   -0.06 -2.17 FOD-Control Diff   -0.23 -3.51
  •  
  •  
  • FOD Study Population M-CARE* (~200,000) U of M* (~70,000) *Estimates from 2006, UM includes actives and dependents only Diabetics Analyses restricted to M-CARE if used: -Medical claims -Lab data -Survey data UM FOD (2,507) a b Controls (8,637) c
  • Extra Slides Follow
  • Value-Based Insurance Design (VBID) in the Medicare Prescription Drug Benefit: An Analysis of Policy Options
  • Policy Options for Implementing VBID in Part D
      • Option 1: Reduce cost sharing for specific drugs or drug classes
      • Option 2: Exempt specific drugs or drug classes from 100% cost sharing in the coverage gap
      • Option 3: Reduce cost sharing for enrollees with chronic conditions
      • Option 4: Reduce cost sharing for enrollees participating in medication therapy management programs (MTMPs)
      • Option 5: Reduce cost sharing for chronic condition special needs plans (CC-SNPs)
  • We Evaluated Each Option’s Impact And Feasibility According To Four Criteria
  • Greatest Potential / Most Feasible Moderate Potential / Feasibility Least Potential / Feasible Option 1: Reduce Cost Sharing for Specific Drugs or Drug Classes
    • Potential to reach a large number of Part D beneficiaries
    • Can be implemented in the current policy environment
    • Plans can create new formulary tier for targeted drugs
    • Incentives needed to encourage plans to take advantage of the option
    Low or no cost sharing for high-value drugs would encourage adherence among all enrollees who may benefit from a drug in these classes, regardless of their chronic condition diagnosis Most Promising Size of Medicare Population Affected Policy Change Required Operational Change Required Political Support
  • Greatest Potential / Most Feasible Moderate Potential / Feasibility Least Potential / Feasible Option 2: Exempt Specific Drugs or Drug Classes from 100% Cost Sharing in the Coverage Gap
    • Affects fewer beneficiaries, but targets patients with high drug spending
    • Can be implemented in the current policy environment
    • Incentives needed to encourage plans to add gap coverage for targeted drugs or drug classes
    Because adherence may decline as enrollees are exposed to high cost sharing, this option would offer protection when costs are generally the greatest—during the coverage gap Promising, But Smaller Impact Size of Medicare Population Affected Policy Change Required Operational Change Required Political Support
  • Greatest Potential / Most Feasible Moderate Potential / Feasibility Least Potential / Feasible Option 3: Reduce Cost Sharing for Enrollees with Chronic Conditions
    • Potential to reach a large number of Part D beneficiaries
    • May require exemption from non-discrimination clause and uniform benefit requirement
    • Requires process to identify enrollees with specific chronic condition diagnoses and to select drugs eligible for reduced cost sharing
    Targeting enrollees with a specific chronic condition for lower cost sharing—for all drugs or just those that treat the particular condition—would lessen the out-of-pocket burden associated with the chronic condition Effective Targeting, But Legislative Barriers Size of Medicare Population Affected Policy Change Required Operational Change Required Political Support
  • Option 4: Reduce Cost Sharing for Enrollees Participating in MTMPs
    • Targets small percentage of Medicare population
    • Positively reinforces MTMP efforts to improve beneficiaries’ medication adherence
    • May require exemption from non-discrimination clause and uniform benefit requirement
    • Plans may wish to monitor MTMP participation to identify beneficiaries who qualify for low cost sharing
    Enrollees participating in Part D’s MTMP would benefit from reduced cost sharing for specific drugs, in addition to other patient outreach and counseling on medication use MTMP: Medication Therapy Management Program Potential to Improve Adherence, But Legislative Barriers Size of Medicare Population Affected Policy Change Required Operational Change Required Political Support Greatest Potential / Most Feasible Moderate Potential / Feasibility Least Potential / Feasible
  • Greatest Potential / Most Feasible Moderate Potential / Feasibility Least Potential / Feasible Option 5: Reduce Cost Sharing for CC-SNP Enrollees Based on the Plan’s Target Condition
    • Affects fewest beneficiaries
    • Can be implemented in the current policy environment
    • No operational changes required
    • May be an ideal first step in implementing VBID in the Medicare Part D program
    SNPs designed for a specific chronic condition could reduce cost sharing for drugs treating the target condition as part of an overall model of care aimed at better disease management Path of Least Resistance Size of Medicare Population Affected Policy Change Required Operational Change Required Political Support
  • While VBID Can Be Implemented in Part D, Policymakers Should Consider How to Encourage Plan Adoption
    • Several options are now available to Part D plans
      • No legislative or regulatory changes needed for Options 1, 2, or 5
      • Plans may require incentives to adopt VBID
    • Additional analysis is needed to further explore VBID in Medicare
      • Identify incentives that would be most attractive to Part D plans
      • Define high-value drugs or chronic conditions
      • Project costs or savings from VBID implementation
      • Examine VBID opportunities for other Medicare services (Parts A&B)
  • Could VBID Take Off As Other Part D Benefit Designs Have? N = 1,429 Source: Avalere Health analysis using DataFrame®, a proprietary database of Medicare Part D plan features. 2009 data from November 2008. 2006 data from July 2006. *N = Total number of PDPs offered each year. N = 1,648 Percent of Medicare Prescription Drug Plans (PDPs) with Four or More Tiers
  • The Benefit Derived from a Specific Service Depends on the Patient Using It Beta-Blockers Clinical benefit Low-risk group High-risk group Low High Patient Contribution Falls as Benefit Increases