Development of computerized alerts with management strategies for 25 serious drug-drug interactions.

PURPOSE: The development of computerized alerts with management strategies for 25 drug-drug interactions (DDIs) is described. SUMMARY: To ensure that clinicians, when confronted with any of 25 serious DDIs in the ambulatory care setting, can avoid these DDIs while treating patients with appropriate medications, management strategies were developed using a consensus approach. Several methods were used to ensure that the recommended alternatives were truly safe. Four well-established drug-interaction compendia were screened, and any potential alternative agent that was listed as having an interaction (moderate or serious in nature) was excluded from the list of alternative agents. Case reports, case series, and clinical studies that focused on the alternative combinations were reviewed to determine if the alternative posed interaction risks. If an interaction for the alternative combination had not been identified in the compendia or in the literature search, other potential mechanisms for drug interactions were explored such as alterations in absorption, distribution, metabolism, or excretion. Pharmacology and therapeutics textbooks and other drug information sources also served as resources. In general, the strategies included alternatives to both medications, changing dosage or increasing monitoring of one of the agents, situations where one of the medications had no alternative but alternatives were available for the other medication, and alternative methods of birth control. In some situations the two drugs were contraindicated, while in others the two drugs should be avoided if at all possible and alternatives used. CONCLUSION: Consensus-based management strategies for 25 serious DDIs were developed for inclusion in computerized alert messages.

Consumer understanding and satisfaction associated with a 3-tier prescription drug benefit.

OBJECTIVE: The purpose of this research was to investigate consumer understanding and satisfaction associated with a 3-tier prescription drug benefit among users of the prescription drug benefit. METHODS: This study involved a self-administered postal questionnaire and the use of prescription drug claims to evaluate utilization of prescription medications. Fifteen hundred subjects were randomly selected based on the following inclusion criteria. Each subject had to (1) be enrolled in a 3-tier copayment ($10 generic, $20 formulary brand, $35 nonformulary brand) prescription drug benefit; (2) be the primary beneficiary (cardholder); (3) be >18 years of age; (4) have received at least 1 prescription medication using his or her prescription drug insurance; and (5) have a mailing address on file. RESULTS: A total of 479 usable responses were returned (35% response rate). The mean (SD) understanding score was 2.22 (1.54) (range: 0 to 6). Fewer than 1% of respondents correctly answered all 6 items used to measure the level of understanding. The mean (SD) satisfaction score was 54.32 (19.69) (range: 0 to 100). Experience with purchasing a medication within a particular copayment tier was predictive of correctly answering the item related to that tier.s copayment amount. Multiple regression analysis revealed a relationship between the amount of use of the drug benefit and the degree of satisfaction with the drug benefit. There was no significant relationship between the level of understanding and the degree of satisfaction with prescription drug insurance. CONCLUSION: The average level of beneficiary understanding of the 3-tier copayment prescription drug benefit was very low, and the average degree of respondent satisfaction appeared to be near neutral. There was no significant relationship between the level of understanding and the degree of satisfaction with prescription drug benefits. The level of understanding was proportional to the amount of drug benefit use, but the degree of satisfaction was not related to the amount of drug benefit use.

Industry's perception of presenting pharmacoeconomic models to managed care organizations.

BACKGROUND: Previous research has shown that pharmacoeconomic (PE) data are considered important but may not be optimally utilized by decision makers. No research has compared the effectiveness of different types of PE models. OBJECTIVES: The purpose of this study was to examine the perceived value and understanding of PE models among decision makers in managed care organizations. The perspective of this study was from research scientists working in the pharmaceutical industry who present PE models to managed care clients. The study objectives were to (1) examine what types of models are best received by decision makers, (2) investigate the barriers to using PE models, and (3) recommend methods for improving PE models. METHODS: A telephone survey of 39 items was conducted with 20 PE research scientists from various U.S. pharmaceutical and biotechnology companies. Topics addressed included factors contributing to how well PE models are received, barriers to using PE models, and recommendations for improving PE models. RESULTS: Models have an impact on health policy decision making. Nineteen of 20 respondents had at least one experience where a PE model played a role in optimizing the formulary positioning of a product. No single model format (e.g., decision analytic tools, spreadsheet analyses, Markov models, multivariate regression models) was regarded as the most effective model type. Although 7 of 20 respondents said simple spreadsheet models were most effective, well-designed, scientifically sound regression models were also reported to be very effective. CONCLUSIONS: The respondents commonly used models to share PE information, which was said to play a role in making health policy decisions by decision makers in managed care. There was no consensus regarding the type of model that was most effective. Study participants indicated that a variety of model designs are effective, ranging from simple spreadsheet models to multivariate regression models. Recommendations for improving PE models include (1) producing scientifically sound models, (2) customizing models where possible, (3) making models transparent, (4) making models user friendly, and (5) involving a nonbiased third party for model development.

Approaches to pharmacy benefit management and the impact of consumer cost sharing.

BACKGROUND: Numerous mechanisms have been introduced to deliver prescription drug benefits while controlling pharmaceutical costs. An understanding of the most prominent mechanisms of benefit management is an important step in determining the most effective approach to take in future years. OBJECTIVES: The aims of this review were to illustrate the mechanisms by which managed care has attempted to efficiently and equitably deliver pharmacy benefits and to discuss the impact of such programs, including consumer cost sharing. METHODS: A review of the literature was conducted using the PreMedline and MEDLINE databases from the years 1966 to 2002, reference lists from relevant articles, and online sources, including news releases, conference materials, and pharmacy benefit management reports. RESULTS: Numerous pharmacy benefit management tools and their impact on utilization, expenditures, and health outcomes are reviewed, including disease state management; utilization management (ie, quantity limitations and prior authorization); drug utilization review; formulary management (ie, open and closed); delivery systems (ie, retail and mail order); and mechanisms for implementing consumer cost sharing (ie, generic incentives, multitiered copayments, and co-insurance). Although there is some evidence to suggest that certain benefit management tools have been successful in reducing health plan expenditures, a more thorough investigation of their potential unintended consequences is needed. CONCLUSIONS: Implementing adequate levels of consumer cost sharing is necessary if employers and health plans are to continue offering prescription drug benefits. It is important to remember, however, that quality health care cannot be forfeited for the sake of short-term cost savings.

Patterns of antidepressant use among children and adolescents.

OBJECTIVE: The purpose of this study was to identify patterns of new antidepressant use among children and adolescents and to determine whether the duration of treatment was sufficient. METHODS: A retrospective 12-month analysis was conducted of claims data for a cohort of nine- to 18-year-old new users of antidepressants in an Ohio Medicaid population. Treatment duration was categorized into five time intervals reflecting initial treatment through various continuation periods. RESULTS: A total of 554 children and adolescents started an antidepressant regimen during a three-month period. These children were mostly Caucasians (78 percent), and their average age was 13 years. Boys and girls were equally represented. The use of antidepressants increased with age among girls but declined among boys. The distribution of antidepressants dispensed was selective serotonin reuptake inhibitors, 47 percent; tricyclic antidepressants, 27 percent; and other antidepressants, 23 percent. The specific agent used varied by primary psychiatric diagnosis. The proportion of children who completed treatment was 94 percent for the four-week treatment period, 23.5 percent for the six-month period, and 12.6 percent for the whole year. CONCLUSIONS: Antidepressants are used in the treatment of children and adolescents who have a wide array of mental health problems. As with adults, continuation of treatment among children and adolescents declines dramatically after an initial period. In addition to studies of the clinical efficacy of antidepressant use among children and adolescents, future research is needed to assess adherence to practice guidelines and health outcomes in childhood and adolescent mental health.