Forecasting Medicaid Expenditures for Antipsychotic Medications

Slade, Eric P.; Simoni, Jane M.

doi:10.1176/appi.ps.201400042

Cited by 9 publications

(6 citation statements)

References 11 publications

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“…The greatest cost-effectiveness was observed among low-DUP clients and when generic drug prices were used (as is likely to be the case in the future) 32 The third analytic approach, using NHB, found a .95 probability that NAV was more cost-effective than CC if the QLS-SD is valued at $40 000. Among the low-DUP samples there was a .94 probability that NAV was more cost-effective at only $20 000/QLS-SD, while among the high-DUP patients there was a .31 probability at $20 000 and only a .64 probability that NAV was cost-effective compared to CC at $50 000.…”

Section: Discussionmentioning

confidence: 99%

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Cost-Effectiveness of Comprehensive, Integrated Care for First Episode Psychosis in the NIMH RAISE Early Treatment Program

Rosenheck

Leslie

Sint

et al. 2016

SCHBUL

122

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This study compares the cost-effectiveness of Navigate (NAV), a comprehensive, multidisciplinary, team-based treatment approach for first episode psychosis (FEP) and usual Community Care (CC) in a cluster randomization trial. Patients at 34 community treatment clinics were randomly assigned to either NAV (N = 223) or CC (N = 181) for 2 years. Effectiveness was measured as a one standard deviation change on the Quality of Life Scale (QLS-SD). Incremental cost effectiveness ratios were evaluated with bootstrap distributions. The Net Health Benefits Approach was used to evaluate the probability that the value of NAV benefits exceeded its costs relative to CC from the perspective of the health care system. The NAV group improved significantly more on the QLS and had higher outpatient mental health and antipsychotic medication costs. The incremental cost-effectiveness ratio was $12 081/QLS-SD, with a .94 probability that NAV was more cost-effective than CC at $40 000/QLS-SD. When converted to monetized Quality Adjusted Life Years, NAV benefits exceeded costs, especially at future generic drug prices.

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Section: Discussionmentioning

confidence: 99%

“…Antipsychotic and other medication costs were estimated from discounted prices from the Federal Supply Schedule Prices for 2014. Since on-patent drugs will soon be generic, 32 sensitivity analyses were also conducted in which drug-costs were considered at generic prices.…”

Section: Assessmentsmentioning

confidence: 99%

Cost-Effectiveness of Comprehensive, Integrated Care for First Episode Psychosis in the NIMH RAISE Early Treatment Program

Rosenheck

Leslie

Sint

et al. 2016

SCHBUL

122

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“…Similarly, even though forecasting has been used by many other payers internationally, there are few studies on forecasting of pharmaceutical expenditure published to date. Some of these studies are focused on the forecasting methods [11][12][13][14] and some presented projections of pharmaceutical expenditure [15][16][17][18][19] including comprehensive approaches to cover all therapeutic areas [20,21]. The accuracy of forecasting has also been evaluated [22,23].…”

Section: Introductionmentioning

confidence: 99%

Forecasting drug utilization and expenditure: ten years of experience in Stockholm

Linnér

Eriksson

Persson

et al. 2020

BMC Health Serv Res

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Background: Operating under constrained budgets, payers and providers globally face challenges in enabling appropriate and sustainable access to new medicines. Among payer initiatives aiming to improve preparedness of healthcare systems for the introduction of new medicines, drug utilization and expenditure forecasting has played an increasingly important role. This study aims to describe the forecasting model used in Region Stockholm and to evaluate the accuracy of the forecasts produced over the past decade. Methods: In this repeated cross-sectional study, we compared the predicted pharmaceutical expenditure with actual expenditure during the entire available follow-up period (2007-2018) both for overall drug utilization and for individual therapeutic groups. All analyses were based on pharmaceutical expenditure data that include medicines used in hospitals and dispensed prescription medicines for all residents of the region. Results: According to the forecasts, the total pharmaceutical expenditure was estimated to increase between 2 and 8% annually. Our analyses showed that the accuracy of these forecasts varied over the years with a mean absolute error of 1.9 percentage points. Forecasts for the same year were more accurate than forecasts for the next year. The accuracy of forecasts also differed across the therapeutic areas. Factors influencing the accuracy of forecasting included the timing of the introduction of both new medicines and generics, the rate of uptake of new medicines, and sudden changes in reimbursement policies. Conclusions: Based on the analyses of all forecasting reports produced since the model was established in Stockholm in the late 2000s, we demonstrated that it is feasible to forecast pharmaceutical expenditure with a reasonable accuracy. A number of factors influencing the accuracy of forecasting were also identified. If forecasting is used to provide data for decisions on budget allocation and agreements between payers and providers, we advise to update the forecast as close as possible prior to the decision date.

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“…In the last two decades dramatic changes in the use of SGAs, most of which are financed by public programs in the United States, such as Medicaid and Medicare, have been observed. Between 1999 and 2005, antipsychotic prescriptions per Medicaid beneficiary increased 30% (Slade and Simoni‐Wastila, 2015). Few studies have examined how physician characteristics impact the adoption speed across several new, therapeutically similar drugs over time.…”

Section: Introductionmentioning

confidence: 99%

A Bayesian hierarchical model for characterizing the diffusion of new antipsychotic drugs

Huskamp

Donohue

et al. 2020

Biometrics

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New prescription medications are a primary driver of spending growth in the United States. For patients with severe mental illnesses, second‐generation antipsychotic (SGA) medications feature prominently. However, many SGAs are costly, particularly before generic entry, and some may increase the risk of diabetes. Because physicians play a prominent role in new prescription adoption, understanding their prescribing behaviors is policy‐relevant. Several features of prescription data, such as different antipsychotic choice sets over time, variable physician prescription volumes, and correlation among drug choices within physicians, complicate inferences. We propose a multivariate Bayesian hierarchical model with piecewise random effects to characterize the diffusion of new antipsychotic drugs. This model captures the complex prescriber‐specific relationships among the different diffusion processes and takes advantage of the Bayesian paradigm to quantify uncertainty for all parameters straightforwardly. To evaluate the prescribing patterns for each physician, we propose various indices to identify early new SGA adopters. A sample of nearly 17,000 US physicians whose antipsychotic drug prescribing information was collected between January 1, 1997 and December 31, 2007 illustrates the methods. Determinants of high prescription rates and adoption speeds of new SGAs included physician sex, age, hospital affiliation, physician specialty, and office location. Large within‐ and between‐provider variations in prescribing patterns of new SGAs were identified. Early adopters for one drug were not early adopters for another drug.

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Forecasting Medicaid Expenditures for Antipsychotic Medications

Cited by 9 publications

References 11 publications

Cost-Effectiveness of Comprehensive, Integrated Care for First Episode Psychosis in the NIMH RAISE Early Treatment Program

Cost-Effectiveness of Comprehensive, Integrated Care for First Episode Psychosis in the NIMH RAISE Early Treatment Program

Forecasting drug utilization and expenditure: ten years of experience in Stockholm

A Bayesian hierarchical model for characterizing the diffusion of new antipsychotic drugs

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