Impact of Prescription Drug Coverage on Medicare Program Expenditures: Will Part D Produce Savings in Part A and Part B? - PowerPoint PPT Presentation

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Impact of Prescription Drug Coverage on Medicare Program Expenditures: Will Part D Produce Savings in Part A and Part B?

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Impact of Prescription Drug Coverage on Medicare Program Expenditures: Will Part D Produce Savings in Part A and Part B? Bruce Stuart, PhD* Becky Briesacher, PhD ... – PowerPoint PPT presentation

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Title: Impact of Prescription Drug Coverage on Medicare Program Expenditures: Will Part D Produce Savings in Part A and Part B?


1
Impact of Prescription Drug Coverage on Medicare
Program Expenditures Will Part D Produce
Savings in Part A and Part B?
  • Bruce Stuart, PhD
  • Becky Briesacher, PhD,, Jalpa Doshi, PhD,
  • Marian Wrobel, PhD, Fatima Baysac, MHS
  • ( University of Maryland Baltimore, UMASS,
  • University of Pennsylvania, Abt
    Associates)
  • AcademyHealth
  • San Diego, June 7, 2004

2
The Belief
  • Drug coverage under Medicare will allow
    seniors to replace more expensive surgeries and
    hospitalizations with less expensive prescription
    medicine.
  • President George W. Bush upon signing the
    Medicare Modernization Act, December 8, 2003

3
Why it Matters
  • Prescription drug expenditure trends
  • Drugs represent the fastest growing service
    segment in the past half decade and for the next
    decade to come
  • Potential for significant cost offsets puts this
    trend in a much more favorable light
  • Cost offsets as a marker for real improvements in
    health
  • If drug coverage improves medical management then
    the impact should be reflected in savings
    elsewhere in the system
  • Stand-along drug plans under Part D
  • Medicare plans have financial incentives to keeps
    drug costs low
  • Tracking cost offsets is a way to monitor
    unintended consequences of plan behavior

4
The Theory
  • Prescription drugs are normal goods
  • As price goes down demand goes up
  • Insurance lowers price so quantity demanded
    should rise
  • As the price of a substitute goes down
  • Quantity demanded goes down
  • If drugs substitute for hospitalization, then
    prescription coverage should reduce Medicare Part
    A spending
  • As the price of a complement goes down
  • Quantity demanded goes up
  • If physician services are a complement for
    prescription drugs, then prescription coverage
    should increase spending for Part B

5
The Evidence
  • Clinical trials
  • Comparing new drugs to placebo on utilization end
    points
  • 1000s of published studies
  • Evidence of savings commonplace
  • Natural experiments
  • Track health care spending following changes in
    drug coverage
  • Studies limited mainly to small changes in
    copays, mostly for poverty populations
  • Non-experimental observational designs
  • Lichtenbergs analyses of new versus old drugs
  • Gillman et al. study of the Vermont pharmacy
    assistance program

6
Lessons from the Evidence
  • Clinical trials
  • Limited to new products tested on nonelderly
    populations with short observation periods
  • High internal validity/low generalizability
  • Natural experiments
  • No experiment comparable to Medicare Part D (or
    any other comprehensive drug plan)/poor
    generalizability
  • Difficulty in finding appropriate control
    populations
  • Non-experimental observational designs
  • Poorly matched controls
  • Selection bias
  • Conclusion from the evidence
  • The only way to adequately test the cost-offset
    hypothesis is through large-scale
    population-based observational studies using
    appropriate matched populations with and without
    drug coverage that demonstrably control for
    selection bias

7
Testing the Cost Offset Hypothesis
  • Data
  • MCBS 1999 and 2000
  • Sample
  • 2-year panel of 3,365 beneficiaries (2,603 with
    and 762 without prescription coverage)
  • Inclusion criteria continuous Part A and B
    coverage, continuous Medicare supplement, and
    continuous (or no) drug benefits
  • Exclusions LTC facility residents, MC
    enrollees, decedents,
  • Dependent variables
  • Annual 2000 expenditures for drugs, Medicare
    inpatient hospital, physician services, all Part
    A and B combined

8
Testing the Cost Offset Hypothesis
  • Explanatory variables
  • Prescription coverage status (continuous from any
    source or none)
  • Age, gender, SSDI disability status
  • Predicted Medicare spending in 2000 based on
    DCG/HCC values generated from 1999 claims data
  • Statistical Procedures
  • Propensity score weighted comparison of mean
    spending levels between those with and without
    prescription coverage
  • GLM regression with gamma distribution and log
    link
  • Sensitivity tests for excluded populations
  • Test for Selection
  • Durbin-Wu-Hausman specification test for omitted
    variables

9
Study Findings
  • Sample composition
  • Substantial differences between population
    samples with and with prescription benefits
    (shows need to control for selection)
  • Differences in annual spending
  • Insured sample had higher spending in all
    categories
  • After propensity weighting, only drug spending
    was found to be significantly higher among
    insured beneficiaries (same for regression
    analysis)
  • Test for selection and sensitivity to sample
    restrictions
  • Negative DWH finding when DCG/HCC variable in the
    models
  • Sensitivity tests confirm general findings for
    excluded populations

10
Study Findings
Annual expenditures (2000) Sample with drug coverage Sample without drug coverage
Prescription drugs 2,074 1,068
Inpatient hospital 2,099 1,835
Physician services 1,537 1,243
All Part A and B 4,952 3,899
11
Study Findings Adjusted versus Unadjusted
Differences (plt.05)
Annual expenditures (2000) difference for sample with coverage (unadjusted) difference for sample with coverage (propensity adjusted)
Prescription drugs 94 66
Inpatient hospital 14 -14
Physician services 24 8
All Part A and B 27 -2
12
Implications for Policy
  • No evidence for cost offsets to prescription
    coverage
  • Failure to find savings associated with
    relatively generous coverage (about 70 of drug
    costs paid by 3rd parties for our sample) means
    that the much less generous Part D benefit is
    unlikely to generate savings in Parts A and B
  • Study limitations
  • Usual caveats on drawing causal inferences from
    observational designs
  • Propensity weighting equates samples on all
    matching variables but restricts generalizability
    to those in the middle of the propensity range
  • Heterogeneity in drug coverage limits
    generalizability to specific types of coverage
  • Future work
  • Focus on medication-sensitive diseases (diabetes,
    hypertension, heart disease, mental illness, and
    chronic lung disease)
  • Focus on drug benefits designs with medication
    management programs
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