Analysis of ODPRA savings

What are the likely economic benefits to the state of Ohio from the Ohio Drug Price Relief Act? Patrick Murray, MD, MS Senior Scholar Center for Health Care Research and Policy MetroHealth Medical Center (This work does not represent the opinion of the MetroHealth Medical Center, Case Western Reserve University, or the Center for Health Care Research and Policy) This analysis evaluates the likely benefits to the State of Ohio government and the Ohio Pension Plans for the public employees if the Ohio Drug Price Relief Act (ODPRA) was passed and its basic program, reducing the prices paid by the state to the same level as paid by the Veterans Hospital Administration (VHA), was implemented in its most straightforward manner.

To conduct this analysis, it is necessary to determine the population that is affected by the ODPRA, the expected drug purchasing by that population, the likely actual costs being paid by these various groups at present, and to make an estimate of the prices that the VHA is presently paying for drugs relative to the other populations that would be affected by the ODPRA. These can be estimated using available data to arrive at an estimate of the likely economic outcomes of ODPRA. To evaluate the model under different conditions a sensitivity analysis is conducted to see how the estimates change in the areas where there is uncertainty.

Methods and Data The population The population that will be affected has been described in detail by the VORYS report (1) in figure 3 of that report. This analysis utilizes the covered lives described in that figure. The source of the numbers in figure 3 is documented in the footnotes at the end of the VORYS report.

Drug expenses The average person in the United States in 2016 had a drug bill of $1,054 dollars. This estimate is derived from an estimate of the 2016 total retail prescription drug cost ($340.7 billion) (2, 3) divided by the population of the United States (323,148,587 on July 4, 2016). (US census) Drug costs are not uniform across population groups with a prominent variation by age. (4) In conducting this analysis, the population is divided into 4 groups, greater than 64 years old, 19 -44 years old, 45 – 64 years old, and less than 19 years old. Table 1 indicates the ratio of subgroup drug spending relative to average spending in 2012. (4). Each of the groups identified in the VORYS report is assigned to one of these four levels of spending in table 1.

Table 1 Age group (years)

> 65

Percent average spending for the age group relative to the national average 237*

45 - 64

154

19 - 44

54

< 19 31 * and average of the costs for those > 84 years old and those 65 -84 years old Actual prices paid for drugs The actual price paid for drugs is highly variable across groups of drugs and across plans. Most people are enrolled in private insurance plans that utilize Pharmacy Benefit Managers which negotiate with pharmaceutical companies what is actually charged for a given drug. The benefit in terms of lower cost is only partially passed on to the insurance company or other purchaser of drugs. The results of these private insurance and PBM negotiations are not public. At a global level, it is possible to make an estimate of how much drugs are discounted using information in the public domain.

We draw on two reports to assess the relative costs for drugs in different insurance situations.

The first is a report by the QuintilesIMS Institute (5) that provides an estimate of how much on average drugs purchased under Medicare Part D and commercial insurance are discounted from their list price.

Their estimate is that Medicare Part D plans purchase drugs at a 35% discount. They also state that most commercial plans receive a smaller discount than Medicare for a variety of reasons they discuss.

They note that this can be as much as a 10% smaller discount. In this analysis we have used a figure of 30% cost reduction from list price as the typical “commercial” discount and the 35% rate when evaluating savings for groups on Medicare.

In situations where the consumer is purchasing the drug in a retail environment there is an additional payment for the drug beyond that paid by the insurer. This is most relevant in all the pensions plans, and the state employees benefit plans. We have accounted for the copay costs using estimates of typical copays provided in the previously cited Quintiles report (5) in these groups.

The second report by Gagnon and Wolfe (6) provides estimates of present Medicaid discounts, Medicare Part D discounts, and an estimate of VHA discounts for brand name drugs. In this study with a different methodology, the relative payments for drugs compared to “list price” for Medicare Part D, Medicaid, and VHA are 83%, 48%, and 46% respectively. To make similar comparisons with the QuintilesIMS report it is necessary to subtract the copay percentage from the Medicare Part D leaving us with an estimated Medicare Part D payment of 61%. The discount/rebate rates comparable to the Quintiles report thus are, Medicare Part D 39%, Medicaid 52%, and VHA 54%.

The difference between Ohio Medicaid and VHA is probably understated because Ohio at present, has no formulary for Medicaid drugs, thus weakening its bargaining position for additional discounts beyond that mandated Federal law.

For the current drug costs in the Ryan White program, this analysis uses the actual amount of the Federal dollars to this program divided by the covered lives. Because this program is one of the 340B reimbursement programs, we used the Medicaid/VHA ratio to determine savings. Again, this is taking a conservative approach.

For drugs purchased at the OSU Medical Center we took the actual drug expenditure and divided it into 21% Medicaid and the balance as commercial. For Medicaid, we applied the Medicaid methodology to assess costs relative to VHA and for the remainder we calculated the savings based on the 30% discount for commercial drug costs.

We did not attempt to assess the potential savings for the vaccination programs noted by VORYS. Operationalizing the costs in the different groups The subgroups cited in the VORYS report are listed in Table 2 with the age group used for determining the annual drug costs for each. In four groups (children with handicaps, state mental health hospitals, youth corrections, and developmental disabilities) we doubled the costs because of the nature of the individuals in those categories usually have drug costs much higher than the average. In one category, workersâ&#x20AC;&#x2122;compensation, we used half the cost because the drug costs would only be for the identified injury or disability.

Table 2: Age group categorization of population State program

Percent cost category

Children with Medical Handicaps

Less than 19

Family Planning Program

19 - 44

Ohio Public Employees Retirement System

Greater than 64

School Teachers Retirement System

Greater than 64

School Employees Retirement System

Greater than 64

Highway Patrol Retirement System

Greater than 64

Ohio Police and Pension Fund

Greater than 64

State ODMHAS hospitals

19 - 44

Non-state governmental entities, including community mental health agencies

19 - 44

Ohio Department of Rehabilitation & Correction

19 - 44

Ohio Department of Youth Services

Less than 19

Ohio Department of Developmental Disabilities

Less than 19

Ohio Department of Administrative Services State Employee Health Insurance

19 - 44

Ohio Bureau Workers Comp

19 - 44

Employees of State University and Community Colleges

19 - 44

Estimate of Cost savings to the state of Ohio This analysis uses the discount/rebate rates established in two reports (QuintilesIMS and GagnonWolfe) and makes conservative estimates to determine a probable range of cost savings from the passing and implementation of the Ohio Drug Price Relieve Act. It varies the Medicare discount/rebate rate from 17% (Gagnon study) to 35% (Quintiles study). It varies the Medicaid discount/rebate rate from 50% to 53.1%. The lower Medicaid discount/rebate estimate used is 2% less than the estimate in

Gagnon. This is considering a situation in which the state of Ohio has a weaker bargaining position than the average state Medicaid program given its lack of a tightly controlled formulary. The higher Medicaid discount/rebate estimate is 1.1% more than the estimate in Gagnon. This is a situation where the difference in VHA and Medicaid costs are only those federally mandated ones and the state and VHA negotiated discounts/rebates are the same. The commercial discount rate is varied in this analysis.

Table 3: Results of Sensitivity Analysis Condition

State savings

State Pension plan savings

Total Ohio taxpayer and state pension plan savings

30% commercial $314 million discount 17% Medicare discount 50% Medicaid discount

$222 million

$536 million

30% commercial $164 million discount 35% Medicare discount 53.1 % Medicaid discount

0

$164 million

The analysis takes a conservative approach with regards expected costs for the subgroups and makes a number of other conservative choices when trying to assess savings. The actual savings using this methodology are most likely to be in the midrange of the sensitivity analysis or 350 million dollars.

They could be as much as $536 million.

The savings to the state come primarily from the OSU medical center, Medicaid, and the care provided at ODMHAS hospitals. The analysis uses data about costs for name brand drugs and applies it to all drug costs. Information about generic drugs pricing and discounts is much less available, but it seems likely that a similar pattern of relative discounts occurs in generic drug acquisition.

Notes and References 1. Maureen M. Corcoran, Barbara Coulter Edwards, Robyn Colby, James Downie, Marisa Weisel, Analysis of Proposed Ohio Initiated Statute to Regulate State Prescription Drug Purchasing. VORYS Health Care Advisors ad Health Management Associates under contract to the Pharmaceutical Research and Manufacturers of America (PhRMA). Accessed at http://www.voryshcadvisors.com/2016/09/30/new-report-regarding-drug-purchasing-in-ohio/ (7/25/17) 2. Table 94. National health expenditures, average annual percent change, and percent distribution, by type of expenditure: United States, selected years 1960â&#x20AC;&#x201C;2015 https://www.cdc.gov/nchs/data/hus/2016/094.pdf 3. This ASPE projection shows expenditures for Retail Prescription Drugs of $343 billion in 2016 and Total Prescription Drugs equal to $477 billion. https://aspe.hhs.gov/system/files/pdf/187586/Drugspending.pdf

â&#x20AC;&#x153;Observations on Trends in Prescription Drug Spending,â&#x20AC;? ASPE Issue Brief, Department of Health and Human Services, March 8, 2016 .

4. https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-andReports/NationalHealthExpendData/Downloads/2012AgeandGenderCSVfiles.zip 5. Murray Aitken, Estimate of Medicare Part D Costs After Accounting for Manufacturer Rebates. (A report by the QuintilesIMS Institute) https://www.imshealth.com/files/web/.../IIHI_Estimate_of_Medicare_Part_D_Costs.pdf 6. Gagnon M., Wolfe S. Mirror, Mirror on the Wall: Medicare Part D pays needlessly high brand name prices compared with other OECD countries and with US government programs. Carleton.ca,July 23, 2015. Accessed at https://www.citizen.org/sites/default/files/2269a.pdf