Kirsten Axelsen

Impact of Medicaid Preferred Drug Lists on Therapeutic Adherence

AbstractObjective: To estimate rates of non-adherence for statins following implementation of a preferred drug list (PDL). Study design: A retrospective cohort study. Methods: A difference-in-difference-in-difference approach was used to estimate the impact of a PDL on the use of statins in an Alabama Medicaid population. The PDL restricted access to certain branded medications and imposed a monthly prescription limit. The use of restricted drugs was compared with the use of unrestricted drugs in the months before and after the PDL in North Carolina (where there were no such restrictions) and Alabama. Pharmacy data from 2001 to 2005 were used to examine the effect of the Alabama PDL implemented in 2004. Results: Following the PDL in Alabama, Medicaid beneficiaries treated with statins had an 82% higher relative odds of becoming non-adherent with statin therapy compared with North Carolina and with pre-PDL Alabama [odds ratio (OR) 1.82, 95% CI 1.57, 2.11]. Furthermore, patients taking a restricted statin were more likely to be non-adherent than unrestricted patients (OR 1.42, 95% CI 1.12, 1.80). In addition, among Medicaid beneficiaries taking a restricted statin, people aged 65 years or older were more likely to be non-adherent than their younger counterparts after the PDL (OR 1.33, 95% CI 1.02, 1.73). Fifty-one per cent of patients in the Alabama sample were non-adherent with statin therapy after the PDL, compared with 39% before. Non-adherence was 36% in North Carolina in both periods. Conclusion: The management of heart disease and high cholesterol are important challenges, especially for low-income patients. Policy makers should be aware that access restrictions can have adverse consequences for patient adherence.

Generic and therapeutic statin switches and disruptions in therapy

ABSTRACT Background: The study objective was to compare dose-equivalence, adherence and subsequent switch rates among patients recently switched from a branded to generic version of the same statin (generic substitution, GS) vs. those switched from branded statin to generic version of a different statin (therapeutic substitution, TS). Methods: In a retrospective cohort analysis among adult enrollees in over 90 US health plans, the authors identified adult patients who switched from a branded to generic statin from July–December 2006 (simvastatin became generic in June 2006). Patients were classified by type of statin switch: GS (e.g., branded simvastatin → generic simvastatin), and TS (e.g., branded atorvastatin → generic simvastatin). Demographic and clinical data were collected from claims before switch through 6 months follow-up. Separate outcomes of interest included proportion of patients that switched to a less potent daily dose, that switched back to previous branded statin after switch, and that were at least 80% adherent during the 6 months after initial switch. Significant predictors of each clinical outcome were identified using multivariable logistic regression models, adjusting for differences between groups in covariates and potential confounders. Results: The 6-month TS (n = 3807) and GS (n = 40,165) groups were generally similar demographically. Compared to GS, TS patients were significantly more likely to be switched to a less potent dose (26.2% vs. 0.5%, adjusted odds ratio [AOR] in patients with high-potency index medication = 83.4, p < 0.0001); 33% less likely to be adherent in the 6 months after switch (67.7% vs. 75.9%, AOR in patients with no switch in first 6 months follow-up = 0.67, p < 0.0001); and four times more likely to switch back to previous branded statin (11.3% vs. 2.9%, AOR = 4.1, p < 0.0001). Limitations: This study did not account for co-payment changes, lipid measurements, or changes in pill burden. Conclusions: While this study did not have data on why patients had TS (e.g., for cost or clinical reasons), TS was more likely to involve a subsequent disruption to statin therapy than GS. TS could potentially lead to adverse impacts on patients’ outcomes, and should be studied further.

Optimizing the Leveraging of Real-World Data to Improve the Development and Use of Medicines

Health research, including health outcomes and comparative effectiveness research, is on the cusp of a golden era of access to digitized real-world data, catalyzed by the adoption of electronic health records and the integration of clinical and biological information with other data. This era promises more robust insights into what works in health care. Several barriers, however, will need to be addressed if the full potential of these new data are fully realized; these will involve both policy solutions and stakeholder cooperation. Although a number of these issues have been widely discussed, we focus on the one we believe is the most important-the facilitation of greater openness among public and private stakeholders to collaboration, connecting information and data sharing, with the goal of making robust and complete data accessible to all researchers. In this way, we can better understand the consequences of health care delivery, improve the effectiveness and efficiency of health care systems, and develop advancements in health technologies. Early real-world data initiatives illustrate both potential and the need for future progress, as well as the essential role of collaboration and data sharing. Health policies critical to progress will include those that promote open source data standards, expand access to the data, increase data capture and connectivity, and facilitate communication of findings.

Per-patient-per-month Drug Costs in Medicare Part D Protected Classes

AbstractObjective: The objective of this study was to estimate the per-patient-per-month (PPPM) costs of medications in the six Medicare Part D protected classes based on findings among Medicare and dual eligible beneficiaries with drug coverage before the enactment of the benefit. Design: Data were from the Thomson Medstat MarketScan® Medicare and Medicaid claims databases. The study sample was constructed by identifying patients who were enrolled either in Medicare or dually in Medicare and Medicaid. PPPM costs were calculated for each protected class. Drugs covered under Part B were excluded. Outcomes measure: PPPM aggregated costs within each class. Results: The classes in which generic formulations are available (antidepressants and anticonvulsants) show low PPPM costs (

Effects of Medicaid Access Restrictions on Statin Utilisation for Patients Treated by Physicians Practising in Poor and Minority Neighbourhoods

US45.31 and

Real World Data: Policy Issues Regarding their Access and Use.

US50.97, respectively). The most expensive class is the antiretrovirals (

Payer and Pharmaceutical Manufacturer Considerations for Outcomes-Based Agreements in the United States☆

US829.73). This class is the costliest for all dual eligible patients including those aged 64 years and under. Among the dual eligibles aged 65 years and older, the immunosuppressants are the most expensive class. The same result is seen qualitatively in the Medicare group. Conclusions: PPPM costs are not uniformly high among the protected classes. The claims data in this study allowed a ‘real world’ check of how much the protected classes may impact the finances of Part D. There are differences within the classes between the dual eligible and Medicare patients, and also within the dual eligibles by age. This is an important message to policy makers that a change to the structure of the protected classes in Part D may have differential effects across classes and also within classes.

Real-World Data: Responses to Zito and Doshi.

AbstractObjectives: To explore whether Medicaid preferred drug lists (PDL) impact the utilisation of restricted statin (cholesterol-reducing) medication for all Medicaid patients equally or disproportionately impact patients who are treated by doctors prescribing in poor or minority neighbourhoods. Study design: A retrospective, regression-based analysis, using a pharmacy claims database combined with demographic variables derived from census for the zip code of the practising physician. Methods: Changes in the proportion of statin prescriptions filled for off-PDL (restricted) medicines before and after the adoption of a Medicaid PDL were examined in six states (Alabama, Florida, Georgia, Texas, Virginia, West Virginia). Two non-PDL states were used as controls for underlying market dynamics (New York, North Carolina). Demographics of physicians’ neighbourhoods (poverty and ethnicity) were used to examine the variation in prescribing based on the characteristics of physicians’ areas of practice. Results: The decline in the use of restricted prescriptions (off-PDL drugs) after a PDL varied considerably from state to state, with the greatest decline in Florida (97%) and the smallest decline in Texas (65%). There was a statistically significant and positive association between the degree of decline in the use of restricted medications and the share of impoverished households and the share of the minority population in Alabama, Florida and Texas. Conclusion: The analysis indicates that there is considerable variation in the impact of a preferred drug list by state, and that in certain states the prescriptions filled after a PDL adhere more closely to Medicaid-imposed restrictions in poorer or more ethnically diverse neighbourhoods. This could imply that because of the PDL, in these poorer and more ethnically diverse neighbourhoods, there is a greater change in physicians’ prescribing practice, fewer patients receive the restricted medication by prior authorisation, and more patients experience a disruption in their medication regimen and any resultant unintended consequences. This is an area worthy of future exploration, particularly as the oldest and most vulnerable of these patients transition into Medicare part D for their prescription coverage and may experience changes in formulary.

Racial differences in switching, augmentation, and titration of lipid-lowering agents by Medicare/Medicaid dual-eligible patients.

As real-world data (RWD) in health care begin to cross over to the Big Data realms, a panel of health economists was gathered to establish how well the current US policy environment further the goals of RWD and, if not, what can be done to improve matters. This report summarizes these discussions spanning the current US landscape of RWD availability and usefulness, private versus public development of RWD assets, the current inherent bias in terms of access to RWD, and guiding principles in providing quality assessments of new RWD studies. Three main conclusions emerge: (1) a business case is often required to incentivize investments in RWD assets. However, access restrictions for public data assets have failed to generate a proper market for these data and hence may have led to an underinvestment of public RWDs; (2) Very weak empirical evidence exist on for-profit entities misusing public RWD data entities to further their own agendas, which is the basis for supporting access restrictions of public RWD data; and (3) perhaps developing standardized metrics that could flag misuse of RWDs in an efficient way could help quell some of the fear of sharing public RWD assets with for-profit entities. It is hoped that these discussions and conclusions would pave the way for more rigorous and timely debates on the greater availability and accessibility of RWD assets.

PCV44 EFFECTS OF MEDICAID ACCESS RESTRICTIONS ON STATIN UTILISATION FOR PATIENTS TREATED BY PHYSICIANS PRACTISING IN POOR AND MINORITY NEIGHBORHOODS

BACKGROUND Considerable interest exists among health care payers and pharmaceutical manufacturers in designing outcomes-based agreements (OBAs) for medications for which evidence on real-world effectiveness is limited at product launch. OBJECTIVES To build hypothetical OBA models in which both payer and manufacturer can benefit. METHODS Models were developed for a hypothetical hypercholesterolemia OBA, in which the OBA was assumed to increase market access for a newly marketed medication. Fixed inputs were drug and outcome event costs from the literature over a 1-year OBA period. Model estimates were developed using a range of inputs for medication effectiveness, medical cost offsets, and the treated population size. Positive or negative feedback to the manufacturer was incorporated on the basis of expectations of drug performance through changes in the reimbursement level. Model simulations demonstrated that parameters had the greatest impact on payer cost and manufacturer reimbursement. RESULTS Models suggested that changes in the size of the population treated and drug effectiveness had the largest influence on reimbursement and costs. Despite sharing risk for potential product underperformance, manufacturer reimbursement increased relative to having no OBA, if the OBA improved market access for the new product. Although reduction in medical costs did not fully offset the cost of the medication, the payer could still save on net costs per patient relative to having no OBA by tying reimbursement to drug effectiveness. CONCLUSIONS Pharmaceutical manufacturers and health care payers have demonstrated interest in OBAs, and under a certain set of assumptions both may benefit.