Can an administrative drug claims database be used to understand claimant drug utilization?

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Can an administrative drug claims database be used to understand claimant drug utilization? By Elaine McKenzie, BSP, MBA, Consultant, TELUS Health Analytics Elaine McKenzie is a consultant who works with the pharmaceutical industry and insurer customers providing evidence, strategic advice and analysis of health policy and market access issues. Elaine has also done extensive work for provincial and federal government drug plan managers, developing and analyzing policy options. Her experience includes working within the pharmaceutical industry and with private insurers. TELUS Health adjudicates drug claims for some of Canada s largest insurers and plan sponsors. More than 10 million Canadians with private drug plan coverage have drug claims processed by TELUS Health. The dataset available for analysis has close to nine million individuals. For this group of plan members, TELUS Health processed 66.7 million claims and plan sponsors paid almost $3 billion (approximately 74 per cent of the eligible prescription cost of $4 billion) on behalf of employees and their families. Over the last year TELUS Health completed a number of analyses using the drug claims database to answer general questions such as how many individuals are reimbursed for specific drugs? Where do they live? How much does the claimant pay? How much does the plan sponsor pay? What is the influence of coordination of benefits with public plans on claimant and plan sponsor costs? We have also completed detailed analyses in specific therapeutic areas such as multiple sclerosis and depression/anxiety to better understand drug use by individual claimants. How long does the claimant stay or persist with chronic therapy? How compliant is the claimant with the prescribed dose regimen? What influence, if any, does out-of-pocket cost have on claimant behavior? The analyses were funded by and completed for individual pharmaceutical companies and we cannot share the detailed results. We would however like to share some observations, some of which we expected, others which we did not. Who pays for prescriptions for private plan members? For antidepressant drugs, the plan sponsor paid 75 per cent of the prescription cost 1. The remaining 25 per cent was composed of 9 per cent paid out-of-pocket by the claimant and 16 per cent paid through coordination of benefits (COB) with the provincial government drug plan, or another private plan, or both. This was relatively consistent across all antidepressant drugs with the exception of Desvenlafaxine where the private plan paid a larger share because COB with the provincial plan was not available. (Figure 1) Compared to antidepressants, for MS drugs the plan sponsor paid 71 per cent of the prescription cost. 2 The remaining 29 per cent was composed of 8 per cent paid 1 The antidepressant study was based on 421,878 unique individuals who claimed for and were reimbursed for at least one prescription for an antidepressant drug dispensed by an Ontario pharmacy between January 1, 2011 and December 31, 2012. 2 The MS drug study was based on 9,513 individuals who claimed for and were reimbursed for at least 1 prescription for a MS drug (all jurisdictions) between July 1, 2010 and June 30, 2012 14 INSIGHTS

Figure 1: Payers of the prescription cost for antidepressant drugs 10 9 8 Per cent of prescription cost 7 6 5 4 3 2 1 Bupropion Desvenlafaxine Escitalopram Fluvoxamine Sertraline All Citalopram Duloxetine Fluoxetine Paroxetine Venlafaxine Paid by TELUS administered private plan Paid by another plan (COB with public or private or both) Paid by claimant out-of-pocket by the claimant and 21 per cent paid through COB with the provincial government drug plan or another private plan or both. Figure 2: Payers of the prescription cost for MS drugs The private plan paid a larger share for Natalizumab (Tysabri) and Fingolimod (Gilenya) because of restrictive criteria or lack of coverage in some provinces. (Figure 2) 10 9 8 7 6 5 4 3 2 1 Interferon Interferon Glatiramer Interferon Fingolimod Interferon Natalizumab All MS beta-1a beta-1b acetate beta-1b HCI beta-1a (Tysabri) Drugs (Avonex) (Betaseron) (Copaxone) (Extavia) (Gilenya) (Rebif) Paid by TELUS administered private plan Paid by another plan (COB with public or private or both) Paid by claimant Volume 8 / Issue 3 15

The private drug plan market is a complex system of first, second and often more payers. Both analyses demonstrate the significant impact that COB, particularly with the provincial government drug plan, but also a second private plan, can have on both plan sponsor cost and claimant out-of-pocket cost. Products that do not have public coverage increase plan sponsor cost. This analysis suggests that private plans try to minimize their risk by relying on COB where possible. We also know that, in some jurisdictions, insurers require plan members using higher cost drugs to request reimbursement from the public plan first. We think this will increase. Products that do not have public coverage also increase claimant out-of-pocket cost. Basic economics would suggest that this decreases demand and may require more intervention in the form of pharmaceutical manufacturer patient assistance programs. How much do private plan members pay? The article on trends in this issue of Insights has information on how much claimants pay out of pocket, based on plan design. Twelve percent of plan members have no out-of-pocket cost, because their plans pay 100 per cent of the cost. However, when the impact of COB is factored in, fully a third of all claimants pay nothing out of pocket. In the case of antidepressant drugs (Figure 3) 33 per cent pay no out of pocket costs. For MS drugs (Figure 4) to the corresponding proportion is 34 per cent. 3 Ninety-five percent of claimants pay less than 30 per cent for an antidepressant drug; 97 per cent of claimants pay less than 30 per cent for a MS drug. Consistently claimants for a MS drug pay a smaller share of the prescription cost than claimants for an antidepressant drug, not a surprising finding given the wide differences in drug costs between the two classes. Figure 3: Claimant share of antidepressant drug prescription cost 35% 3 25% Per cent of claimants 2 15% 1 5% All claimants with 1 or more prescriptions for an antidepressant drug All claimants with 2 or more prescriptions for an antidepressant drug Does claimant out-of-pocket cost influence persistence with treatment? Persistence is a measure of how long patients remain on treatment, i.e. duration of therapy. 4 International studies have demonstrated a negative correlation between claimant out-of-pocket cost and adherence to treatment. 3 Our calculation of OOP does not include any financial assistance provided by the pharmaceutical manufacturer. This, if provided, will further reduce claimant OOP cost. 4 Because we do not know the actual number of days of therapy which were provided to the claimant, assumptions are made to calculate the potential days of therapy available. Every effort was made to minimize the influence of multiple dosage units to achieve the daily dose (antidepressant drugs), to correct the differences in quantity measures entered by pharmacies (MS drugs) and resolve methodological issues. However, there are claimants who appear to receive a quantity of drug larger than anticipated. There are also a limited number of claimants who pay a high share OOP 16 INSIGHTS

Figure 4: Claimant share of multiple sclerosis drug prescription cost 4 35% 3 Per cent of claimants 25% 2 15% 1 5% All claimants with 1 or more prescriptions for a multiple sclerosis drug All claimants with 2 or more prescriptions for a multiple sclerosis drug Our analysis demonstrates that as the claimant share of prescription cost increases the duration of treatment with an antidepressant drug for treatment of depression or anxiety decreases. (Figure 5) However, it appears that plan members who make a small contribution to the prescription cost may be more persistent with treatment than those who pay no out-of-pocket cost. This pattern was consistent across individual drugs in the category and all antidepressant drugs combined. Figure 5: Influence of claimant share of prescription cost on duration of treatment with an antidepressant drug 600 500 400 Average days of therapy 300 200 100 0 All claimants with 1 or more prescriptions for an antidepressant drug All claimants with 2 or more prescriptions for an antidepressant drug Volume 8 / Issue 3 17

Figure 6: Influence of claimant share of prescription cost on duration of treatment with an MS drug 450 400 Average days of therapy 350 300 250 200 150 100 50 0 All claimants with 1 or more prescriptions for an MS drug All claimants with 2 or more prescriptions for an MS drug The relationship between an increase in claimant share of prescription cost and decrease in duration of treatment with an MS drug also exists but the relationship is not as strong and is notably absent at the higher end of claimant share, possibly due to the very limited number of claimants available. Pharmaceutical industry patient assistance programs that offset the out-of-pocket cost for the claimant may be a factor in maintaining persistence as the claimant share of cost increases. However, again it appears that plan members who make a small contribution to the prescription cost may be more persistent with treatment than those who pay no out-ofpocket cost. This pattern was again consistent across individual drugs in the category and all MS drugs combined. For plan sponsors looking to reduce costs through cost shifting to plan members this could be an important consideration. If the change has the effect of decreasing persistence it could have the unintended effect of increasing other benefit costs such as short-term disability and longterm disability. It is also an important consideration for pharmaceutical companies bringing new therapies to market. If a higher price increases the amount the claimant pays out-of-pocket this too could influence persistence and patient outcomes. We found it interesting that duration of therapy was less when the claimant paid none of the prescription cost than when the claimant paid a small portion. We are not yet sure if this finding will be found across a broader range of therapeutic categories. But if it is will plan sponsors move towards introducing cost sharing in plans where it does not now exist? The evidence from this year s Trends report indicates a large shift in this direction. What might be the implications for the design of pharmaceutical manufacturer patient assistance programs? Are claimants more persistent when the prescription cost is lower? The average cost / prescription for a multisource antidepressant drug was $50.00, approximately 40 per cent of the average prescription cost of $129.00 for single source antidepressant drugs. The analysis suggests that when the prescription cost is lower which results in a lower out-of-pocket cost for the claimant, the duration of therapy is longer. In a therapeutic class with a significant number of choices, a high cost product imposes a greater burden on claimants out-of-pocket cost. We think this will be an important consideration when pricing a new product for market entry. What might be needed for a new, higher cost product to compete effectively? Summary and conclusions There are limitations in using administrative drug claim databases to identify the patterns of use in clinical practice. It is however real world evidence and the claimants come from a range of plan sponsors across multiple industrial 18 INSIGHTS

Figure 7: Influence of prescription cost on duration of treatment with an antidepressant 600 500 400 Average days of therapy 300 200 100 0 Weighted average, all multisource drugs Weighted average, all single source drugs Weighted average, all drugs sectors with many variations in plan design and cover the spectrum from under-utilization to expected utilization to over-utilization. We studied each individual antidepressant and MS drug and all antidepressant drugs together and all MS drugs together and our findings were consistent. We believe it is a realistic picture for drug use in these therapeutic areas. There are a number of implications for plan sponsors and pharmaceutical manufacturers. Specifically for pharmaceutical manufacturers we think the following are important: 1. The private drug plan market is complex with 1st, 2nd and often more payers. Coordination of benefits across multiple payers significantly impacts both plan sponsor cost and claimant out-of-pocket cost. The importance of a public listing, particularly for higher cost products, cannot be underestimated. 2. There is evidence that persistence with treatment is influenced by claimant out-of-pocket cost. As claimant cost increases, duration of therapy decreases. But it appears that claimants who make a small contribution to the prescription cost may be more persistent than those who pay no out-of-pocket cost. While at first this appears surprising, it may be true we value more what we pay for! 3. As plan sponsors become more familiar with the dynamics of persistence and cost sharing there will be an increased focus to design drug plans that can optimize persistence and compliance and improve outcomes without increasing cost. Potentially, plan sponsors may favor lower cost drug therapies with lower cost sharing to attempt to influence claimant outcomes. 4. Plan sponsors can be expected to increase the use of step therapy and tiered copayments with all new, higher cost therapies to maximize the opportunity for plan members to find the lowest cost effective therapy. 5. In the final analysis, plan sponsors and pharmaceutical manufacturers share a common goal: to optimize outcomes and improve employee productivity. The real opportunity is to bring solutions and programs to market that achieve these results for the plan sponsors and plan members. We welcome your comments, thoughts and input and your suggestions for additional analyses and future studies as we together advance our collective understanding of private drug plan members and the influencers of drug utilization. Volume 8 / Issue 3 19