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Impact of a Prescription Co payment Increase on Blood Pressure in Elderly Patients

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									                Impact of a Prescription Co-payment
                   Increase on Blood Pressure in
                          Elderly Patients
                                  Jalpa Doshi, PhD
                   University of Pennsylvania School of Medicine

                                Bruce Lee, MD, MBA
                     University of Pittsburgh School of Medicine

                             Kevin Volpp, MD, PhD
               CHERP, Philadelphia Veterans Affairs Medical Center
                 University of Pennsylvania School of Medicine
                                Wharton School

                         AcademyHealth 2006 Annual Research Meeting
                                        Seattle, WA
Bruce Lee, MD and Kevin Volpp, MD, PhD
                                       June 25, 2006
                                         Acknowledgements



     • Hu Xie, MS, University of Pennsylvania
     • David Horvath, MS, VA CHERP, Philadelphia VAMC




Bruce Lee, MD and Kevin Volpp, MD, PhD
                     Increases in Prescription Cost Sharing for
                              Medicare Beneficiaries


     • Some Medicare beneficiaries previously receiving
       prescription benefits from Medicaid or state
       pharmaceutical assistance programs may face increases
       in cost sharing under the new Medicare Part D

     • Employers continuing to offer retiree drug benefits are
       also increasing prescription cost sharing requirements

     • Ongoing considerations for increasing prescription
       copayments in the Veterans Affairs and TRICARE


Bruce Lee, MD and Kevin Volpp, MD, PhD
                 What Do We Know about the Impact of
            Prescription Cost Sharing Increases in the Elderly?


     • Prior observational studies have shown that increases in
       cost sharing are associated with:
        – Decreased drug utilization and expenditures

           – Decreases in non-essential and essential drug use

           – Mixed results on medical utilization and expenditures
                 • Health consequences of reduced drug utilization manifest
                   over many years




Bruce Lee, MD and Kevin Volpp, MD, PhD
            Few Studies have Examined How Increases in Cost
                    Sharing Impact Clinical Outcomes


     • Little is known about what effects are on physiological
       outcomes (e.g. blood pressure and LDL cholesterol)




                                         STUDY OBJECTIVE
        To examine the impact of a medication copayment
       increase on blood pressure among elderly patients



Bruce Lee, MD and Kevin Volpp, MD, PhD
                 Increase in Medication Co-Payment within the
                   Veterans Affairs (VA) Population Nationally

                                                     $7 per 30-day Supply


         $2 per 30-day Supply


                                         February 2002




Bruce Lee, MD and Kevin Volpp, MD, PhD
                          Difference-in-Difference Framework


                                               Co-Pay
                                              Increase



    Blood
                                                                                EFFECT =
   Pressure                                                             Diff.
                                                                                Difference
                                                                                     in
                                                                                Difference
                                                                        Diff.
                                                                                 (D-in-D)



                                Pre-Period   Feb 2002            Post-Period

                                                Co-Pay Group

                                                 Control Group

Bruce Lee, MD and Kevin Volpp, MD, PhD
                                   Choosing a Control Group



     • Copay exempt veterans
        – Service-connected disabilities rated > 50% and with
          income below the VA pension level
        – Substantial differences in baseline characteristics and
          health trajectories

     • Compare changes in BP across patients of different
       income levels among veterans subject to copayments
        – Patients with “higher” incomes are less likely to be
          affected by the co-payment increase than patients
          with “lower” incomes subject to the co-payment

Bruce Lee, MD and Kevin Volpp, MD, PhD
                                Study Design and Timeframe


                                                         $7 per 30-day Supply


         $2 per 30-day Supply


                                         February 2002
Q1                                         Washout                               Q1
Q2                                          Period                               Q2
Q3
             PRE-PERIOD                                         POST-PERIOD
                                             +/- 3                               Q3
Q4
            11/1/99-11/30/01                                     5/1/02-5/1/04
                                            Months                               Q4




   Patient household income was derived from zip-code matched census data
   and comparison groups created based on income quartiles

Bruce Lee, MD and Kevin Volpp, MD, PhD
                Study Sample: Philadelphia VA Medical Center


 Inclusion Criteria:
 • Patients aged > 65 years
 • > 1 BP medication during pre-period
 • BP recorded at least once in pre-
    and post-period (~99% of pxs)


 Exclusion Criteria:
 • Patients who died
 • History of dementia or cancer
 • Missing zipcode information
 • Copay exempt patients
Bruce Lee, MD and Kevin Volpp, MD, PhD
                                         Study Outcomes


    • Blood pressure
       – Mean systolic blood pressure (SBP)
       – Any SBP > 140 mm Hg (or > 130 for diabetics)
       – Any SBP > 150 mm Hg (or > 140 for diabetics)

    • Antihypertensive medication adherence
       – Gap days ratio
       – Medication Possession Ratio (MPR)
           Complexity of measuring adherence to antihypertensive
           drug regimen
                                                          Rx1   Rx1
           Beta-blockers          Ca-channel blockers
                                                          Rx2
           ACE-inhibitors         ARBS
            Diuretics                Other
Bruce Lee, MD and Kevin Volpp, MD, PhD
                                         Analytic Approach


    • Difference-in-Difference (D-in-D) Framework
       – Use linear regressions to compare before after difference
         in study group (Q1) with before after difference in control
         group (Q4)

             Y= β0+ β1X + β2Q1……. + β3POST + β4Q1*POST…..

    • Control variables (X)
       – Baseline age, gender, employment status, medical
         conditions (CAD, diabetes, ESRD, CVA, hypertensive
         retinopathy, renal failure), BMI class, # of Rx and visits

    • Sensitivity analysis and sub-group analysis

Bruce Lee, MD and Kevin Volpp, MD, PhD
                   Baseline Sample Characteristics (N=4,442)



                           1st Income    2nd Income       3rd Income     4th Income
                           Quartile (Q1) Quartile (Q2)   Quartile (Q3)   Quartile (Q4)
                              <$37,959      $37,960-       $50,207 -        >$60,000
                                            $50,206         $60,000

   Mean Age                   76 (6.1)     77 (5.9)        77 (5.6)         77 (5.5)
   Median                     $30,177      $43,696        $53,479           $68,214
   Income

   % Diabetes                  28.1%        23.1%          22.6%             19.1%

   % CAD                       33.8%        32.9%          26.2%             27.7%

   % CVA                        6.1%         3.1%           4.5%             3.3%

Bruce Lee, MD and Kevin Volpp, MD, PhD
                   Relative Change from Pre- to Post-Period in
                        BP Measures in Q1 vs. Q4 group
                                          Pre-         Post-
                                         period        period        Difference          D-in-D
      1st Income Quartile (Q1)

      SBP                                 141.0         143.7             2.61            +4.12




      4th Income Quartile (Q4)

      SBP                                 143.3         141.8             -1.51




Bruce Lee, MD and Kevin Volpp, MD, PhD
    * or Any SBP> 130 mm Hg for diabetes patients ** or any SBP> 140 mm Hg for diabetes patients
                   Relative Change from Pre- to Post-Period in
                        BP Measures in Q1 vs. Q4 group
                                          Pre-         Post-
                                         period        period        Difference          D-in-D
      1st Income Quartile (Q1)

      SBP                                 141.0         143.7             2.61            +4.12

      Any SBP > 140 mm Hg*               68.1%          82.8%            14.7%            +5.5%




      4th Income Quartile (Q4)

      SBP                                 143.3         141.8             -1.51

      Any SBP > 140 mm Hg*               65.3%          74.5%             9.2%



Bruce Lee, MD and Kevin Volpp, MD, PhD
    * or Any SBP> 130 mm Hg for diabetes patients ** or any SBP> 140 mm Hg for diabetes patients
                   Relative Change from Pre- to Post-Period in
                        BP Measures in Q1 vs. Q4 group
                                          Pre-         Post-
                                         period        period        Difference          D-in-D
      1st Income Quartile (Q1)

      SBP                                 141.0         143.7             2.61            +4.12

      Any SBP > 140 mm Hg*               68.1%          82.8%            14.7%            +5.5%


      Any SBP > 150 mm Hg**              53.7%          69.7%            16.0%            +8.4%

      4th Income Quartile (Q4)

      SBP                                 143.3         141.8             -1.51

      Any SBP > 140 mm Hg*               65.3%          74.5%             9.2%

      Any SBP > 150 mm Hg**              51.4%          59.0%             7.7%
Bruce Lee, MD and Kevin Volpp, MD, PhD
    * or Any SBP> 130 mm Hg for diabetes patients ** or any SBP> 140 mm Hg for diabetes patients
           Patients in Lowest Income Quartile had Increases in
           SBP Compared to those in Higher Income Quartiles




  Change in
    Mean
   Systolic
    Blood
  Pressure                  +2.61                                      D-in-D
                                                                       +4.12

                                           -0.75
                                                         -1.63       -1.51


                         1st Income      2nd Income   3rd Income   4th Income
                          Quartile        Quartile     Quartile     Quartile
                             (Q1)           (Q2)          (Q3)         (Q4)

Bruce Lee, MD and Kevin Volpp, MD, PhD
                Relative Change from Pre- to Post-Period in
               Antihypertensive Adherence in Q1 vs. Q4 group


                                          Pre-    Post-
                                         period   period   Difference   D-in-D
     1st Income Quartile (Q1)

     Gap days ratio                       0.12     0.18       0.06      +0.02



     4th Income Quartile (Q4)

     Gap days ratio                       0.10     0.14       0.04




Bruce Lee, MD and Kevin Volpp, MD, PhD
          Results in main sample (All Antihypertensive Users):
          Adjusted Relative Change from Pre- to Post-Period in
                     Outcomes in Q1 vs. Q4 group

     Blood                               SBP           Any SBP>140*        Any SBP>150**
     Pressure                       β      p-value      OR (95% CI)         OR (95% CI)
     Measures
     POST*Q1                      +3.4         0.001   1.28 (0.94-1.73)    1.38 (1.06-1.79)




                             Antihypertensive           Gap Days Ratio
                             Adherence
                             Measure                    β        p-value

                             POST*Q1                   +0.01      0.396


Bruce Lee, MD and Kevin Volpp, MD, PhD
* or Any SBP> 130 mm Hg for DM patients ** or any SBP> 140 mm Hg for DM patients
       Antihypertensive users with uncontrolled blood pressure:
        Adjusted Relative Change from Pre- to Post-Period in
                    Outcomes in Q1 vs. Q4 group

                                             SBP        Gap Days Ratio
     Subgroups                           β    p-value     β       p-value


     SBP>140 mm Hg*                  +5.6     <.0001    +0.035     0.032

     SBP>140 mm Hg
     and HTN Rx < 1*                 +4.3      0.028    +0.084     0.021

    * or Any SBP> 130 mm Hg for DM patients




Bruce Lee, MD and Kevin Volpp, MD, PhD
                                         Discussion


     • Increase in copayment is associated with poorer blood
       pressure outcomes

     • Medication adherence results are mixed with decreased
       adherence observed in antihypertensive users with
       uncontrolled blood pressure
           – Complexity of antihypertensive drug regimens
                 • Further examine fill patterns (e.g. at class/dose level)
                 • Map outcomes at quarterly level rather than averages pre- and post-
                   intervention
                 • Repeat analyses for conditions with less complex drug regimens (e.g.
                   statins and LDL-C)
           – Other explanations


Bruce Lee, MD and Kevin Volpp, MD, PhD
                                         Limitations


     • Use of area-level income as proxy
        – Comparison of Q1 vs. Q4 reduces chances of
          misclassification

     • Data are limited to a single site
           – Feasibility of study at national-level being assessed

     • Data do not capture significant lifestyle changes and
       external stressors that could affect blood pressure

     • Dual-users (VA and Medicare)

Bruce Lee, MD and Kevin Volpp, MD, PhD
                                         Policy Implications


     • Increases in copayments may
        – negatively impact blood pressure control in lower
          income patients
        – worsen cardiovascular outcome disparities in the long
          run

     • Direct implications for VA patients
        – President’s FY2007 budget proposal was considering
          raising VA copays to $15
        – 2 million beneficiaries with creditable drug coverage
          through the VA who have not signed up for Part D


Bruce Lee, MD and Kevin Volpp, MD, PhD
                                Policy Implications for Part D



     • Implications for poor and near poor Medicare
       beneficiaries who may face cost sharing increases under
       Part D
        – Some dual eligibles
        – Beneficiaries previously enrolled in SPAPs that were
          abandoned in light of Part D

     • Policymakers should monitor whether access to effective
       medications and the health of such vulnerable seniors
       will be adversely affected


Bruce Lee, MD and Kevin Volpp, MD, PhD

								
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