ORAL CHEMOTHERAPY PARITY LAWS: WHERE DO WE GO FROM HERE? Stacie B. Dusetzina, PhD October 20, 2015 Assistant Professor of Pharmacy and Public Health University of North Carolina at Chapel Hill 1
ORAL CHEMOTHERAPEUTICS 25-35% of cancer medications under development Preferred by patients Extremely expensive with high out-of-pocket costs Increased risk for poor adherence due to cost burden 2
INSURANCE BENEFITS AND CANCER RX Infused Chemo Medical Benefit Copay, no separate chemo charge Subject to medical out-of-pocket max Physician observes use Oral Chemotherapy Pharmacy Benefit Potential high copay Historically no maximum out-of-pocket Physician does not observe use 3
STATE EFFORTS TO REDUCE COST SHARING FOR ORAL CHEMOTHERAPY As of July 2015, 40 States and the District of Columbia have passed chemotherapy parity laws.
GOALS OF PARITY Ensure that patients pay no more for oral cancer therapies than they would pay for intravenous therapies offered by the same health plan.
LIMITATION OF STATE LAWS State Laws Apply Only to: States passing the law A subset of the privately insured population Federal legislation proposed to address gaps in coverage: H.R. 1801: Cancer Drug Coverage Parity Act of 2013 H.R. 2739 and S. 1566: Cancer Drug Coverage Parity Act of 2015 6
IMPACT OF PARITY LAWS ON USE AND COSTS OF ORAL CANCER MEDICATIONS 7
RESEARCH AIMS To Assess the effect of state cancer parity legislation on: Aim 1: Use of cancer medications Aim 2: Patient and health plan spending Aim 3: Adherence to oral cancer medications 8
DATA SOURCE Health Care Cost Institute Claims from 2008 2012 Nationwide inpatient, outpatient and pharmacy administrative claims from: Aetna Humana United Healthcare 9
DATA: HEALTH CARE COST INSTITUTE 10
STUDY DESIGN & ANALYTIC PLAN Leverages a natural experiment Difference-in-difference-in-differences model Compare cancer treatment utilization and costs in: ERISA-exempt and non-exempt plans Before and after legislation Across states with and without parity 11
METHODS SELECTING CONTROLS Comparison groups in interrupted time series. Common scenario: 1 Intervention Group, 1 Control Group 1 Intervention Group, Multiple Control Groups This scenario: Multiple Intervention Groups (at different times) 12
HERE IS THE PROBLEM EXPLAINED GRAPHICALLY * Exaggeration of problem but this is pretty much how it felt to me conceptually. 13
TREATMENT AND CONTROL STATE SELECTION Focus on states that have two years pre-parity and two years post-parity (IN, KS, MN, CT, CO) Select control states based on: HCCI Coverage, Geography, Census Level Demographic Variables 14
LIFE LESSON #1: I AM NOT A DEMOGRAPHER 15
PARITY STATES 16
PARITY STATES AND MATCHED CONTROLS 17
STATE CHARACTERISTICS AFTER MATCHING Characteristic Parity States Non-Parity States Census Level Matching Data Median Household Income $69,017 $69,034 Percent Below Poverty 10.6 10.5 Percent Graduating College 37.0 34.6 Percent Graduating High School 91.8 90.0 Percent Black 5.6 9.0 Percent White 85.7 80.4 18
SEGMENTED REGRESSION ANALYSIS Primary Outcomes: 1) The proportion of chemotherapy that is orally administered 2) Monthly oral chemotherapy costs to patients 3) Monthly oral chemotherapy costs to health plans Primary Exposures: Parity, plan funding status, time 19
BALANCING PATIENT CHARACTERISTICS Fully Insured Plans within Parity States Fully Insured Plans in Non-Parity States Self-Funded Plans within Parity States Self-Funded Plans in Non-Parity States Use a multinomial propensity score to predict group membership. 20
DATA STRUCTURE We included all person months of chemotherapy for patients with a cancer for which an orally administered drug was approved. Control variables measured at the person-month level include: Age, gender, census zip-code level data, type of plan, type of cancer, Charlson comorbidity (measured in the 6 months before the current month), count of other medications used in the pre-period. 21
DEMOGRAPHICS OF SAMPLE POST-PS Parity States Non-Parity States Fully Insured Self-funded Fully Insured Self-funded Age 0-45 21.3 21.5 20.6 21.3 Age 45-64 78.7 78.5 79.4 78.7 Female 57.2 58.8 56.9 56.9 Breast 27.2 28.4 25.8 27.1 Colorectal 11.0 9.8 10.7 10.9 Lung 9.6 9.1 10.6 11.0 Prostate 6.0 6.1 5.8 5.8 NHL 6.7 6.6 7.7 7.3 22
ORAL CHEMO USE AS A % OF TOTAL CHEMO USE BY PARITY AND PLAN STATUS 40.0% 35.0% 30.0% Self Funded, No Parity Fully Insured, No Parity Self Funded, Parity Fully Insured, Parity 25.0% 20.0% 15.0% 10.0% 5.0% 0.0% Year 2 Pre Year 1 Pre Year 1 Post Year 2 Post
CHANGES IN OUT OF POCKET SPENDING BY PARITY STATUS 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Pre-Parity Post-Parity Pre-Parity Post-Parity Fully Insured, Parity $0 Copay Increased from 23% to 56% $0 $1-50 $51-100 $101-500 > $500 Fully Insured, No Parity
LIFE LESSON #2: COST MODELING IS HARD! 25
CHANGES IN PATIENT MONTHLY OUT-OF-POCKET SPENDING DUE TO PARITY Out-of-Pocket Spending DDD 95%CI P-Value 25 th Percentile $-29.07 $-29.24, $-28.80 < 0.001 50 th Percentile $-26.55 $-27.36, $-25.74 < 0.001 75 th Percentile $-3.53 $-11.85, $4.79 0.41 90 th Percentile $-222.20 $-272.67, $-171.73 < 0.001 95 th Percentile $-24.80 $-265.65, $216.06 0.84 Mean $-27.88 $-102.59, $46.83 0.55 DDD = Difference-in-difference-in-differences
CHANGES IN ONE-YEAR HEALTH PLAN SPENDING DUE TO PARITY Health Plan Spending DDD 95%CI P-Value Oral Chemotherapy $1,126 $-3,169, $5,421 0.72 Infused Chemotherapy $-8,678 $-21,143, $3,787 0.12 All Chemotherapy $-8,320 $-20,812, $4,172 0.13 Total Health Care Spending* $-7,299 $-21,610, $7,011 0.26 DDD = Difference-in-difference-in-differences * Inpatient, Outpatient and Pharmacy Spending
LIMITATIONS Out-of-pocket costs are relatively low among privately insured patients, regardless of parity, so differences may be small overall. Use of oral chemo was infrequent in early study years which may impact the stability of time series regression estimates. Lack of clinical data related to cancer diagnoses. 28
CANCER DRUG COVERAGE PARITY ACT OF 2015 (S.1566, H.R.2739) Federal Parity Bipartisan bills introduced 6/2015 Would expand parity to all states and include self-funded plans. We will be there with data!
SPECIAL THANKS Collaborators on Presented Work Ethan Basch Haiden Huskamp Nancy Keating Aaron Winn Research Scholar Grant, RSGI-14-030-01-CPHPS from the American Cancer Society Health Care Cost Institute 30
Email: Dusetzina@unc.edu Twitter: @DusetzinaS 31