Good Research Practices for Measuring Drug Costs in Cost-Effectiveness Analyses: A Managed Care Perspective: The ISPOR Drug Cost Task Force Report—Part III

AbstractObjectivesThe objective of this report is to provide guidance and recommendations on how drug costs should be measured for cost-effectiveness analyses conducted from the perspective of a managed care organization (MCO).MethodsThe International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Task Force on Good Research Practices—Use of Drug Costs for Cost Effectiveness Analysis (DCTF) was appointed by the ISPOR Board of Directors. Members were experienced developers or users of CEA models. The DCTF met to develop core assumptions and an outline before preparing a draft report. They solicited comments on drafts from external reviewers and from the ISPOR membership at ISPOR meetings and via the ISPOR Web site.ResultsThe cost of a drug to an MCO equals the amount it pays to the dispenser for the drug's ingredient cost and dispensing fee minus the patient copay and any rebates paid by the drug's manufacturer. The amount that an MCO reimburses for each of these components can differ substantially across a number of factors that include type of drug (single vs. multisource), dispensing site (retail vs. mail order), and site of administration (self-administered vs. physician's office). Accurately estimating the value of cost components is difficult because they are determined by proprietary and confidential contracts.ConclusionEstimates of drug cost from the MCO perspective should include amounts paid for medication ingredients and dispensing fees, and net out copays, rebates, and other drug price reductions. Because of the evolving nature of drug pricing, ISPOR should publish a Web site where current DCTF costing recommendations are updated as new information becomes available

Comparative Effectiveness, Personalized Medicine and Innovation: The Path Forward

Genetic-screening, Health-policy, Treatment-outcome

Impact of non-medical switching on clinical and economic outcomes, resource utilization and medication-taking behavior: a systematic literature review

<p><b>Objective</b>: To evaluate current knowledge of the impact of non-medical switching on clinical and economic outcomes, resource utilization and medication-taking behavior. <b>Methods</b>: The literature was searched (Medline and Web of Science, January 2000–November 2015) to identify United States’ studies evaluating ≥25 patients and measuring the impact of non-medical switching of drugs (switching to a chemically distinct but similar medication for reasons other than lack of clinical efficacy/response, side effects or poor adherence) on ≥1 clinical, economic, resource utilization or medication-taking behavior outcome. The direction of association between non-medical switching and outcomes was classified as negative or positive if a statistically significant worsening or improvement was reported, or neutral if no significant difference was observed. <b>Results</b>: Twenty-nine studies contributed 96 outcomes (60.4% clinical; 21.9% resource utilization; 13.5% economic; 4.2% medication-taking behavior) within six disease categories (cardio-metabolic, immune-mediated, acid suppression, psychiatric, hormone replacement therapy and pain). The direction of association was more frequently negative (33.3%) or neutral (55.2%) than it was positive (11.5%). Stratified by outcome type, non-medical switching was negatively associated with clinical, economic, healthcare utilization and medication-taking behavior outcomes in 20.7%, 69.2%, 38.1% and 75.0% of cases, respectively; and positively in only 4.8%–17.2% of outcomes subgroups. Of 32 outcomes in patients demonstrating stable/well controlled disease, 68.8% and 31.3% had a negative and neutral direction of association. In patients without demonstrated disease stability, outcomes were negatively, neutrally and positively impacted by non-medical switching in 15.6%, 67.2% and 17.2% of 64 outcomes. <b>Limitations</b>: Our inability to evaluate specific disease state categories and studies/outcomes received equal weight regardless of sample size or magnitude of effect. <b>Conclusions</b>: Non-medical switching was more often associated with negative or neutral effects than positive effects on an array of important outcomes. Among patients with stable/well controlled disease, non-medical switching was associated with mostly negative effects.</p