Pharmacoeconomic Guidelines: United States of America

Country/Region: United States of America
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Published PE Recommendations
Published PE Recommendations Source:
Academy of Managed Care Pharmacy
Additional Information:

1. The PDF version  and the link to AMCP Formulary Submission Version 4.1

 2. A Webinar on Version 4.1 is available here

Information current as of Friday, October 7, 2022

Key Features

Type of Guidelines Published PE Recommendations
Title and year of the document The AMCP Format for Formulary Submissions: Guidance on Submission of Pre-approval and Post-approval Clinical and Economic Information and Evidence (Version 4.1, January 2020)
Affiliation of authors AMCP Format Executive Committee members (see Acknowledgements page for affiliations)
Purpose of the document To identify comprehensive evidence and information elements for the creation of dossiers that meet the evidentiary needs of health care decision-makers (HCDMs). The AMCP Format is designed to encourage sharing of objective, credible, and relevant information on medical products to: 1. Improve the timeliness, scope, quality, and relevance of clinical and economic evidence and information provided by manufacturers to HCDMs; and 2. Streamline the evidence and information acquisition and review process for HCDMs.
Standard reporting format included Yes
Disclosure No
Target audience of funding/ author's interests Health care decision makers with relevant expertise who are involved in managing formularies and analyzing data submitted by manufacturers in advance of coverage and reimbursement considerations.
Perspective The health care decision maker perspective is recommended for the primary analysis, with optional perspectives (i.e., societal, employer) conducted as secondary evaluations. 
Indication The Format provides guidance for pre-approval and post-approval clinical and economic evidence. Inclusion of data to support product use in labeled and off-label indications is encouraged post-approval.
Target population Yes, target population should be clearly defined in submission. The target population for a budget impact model should include all patients eligible to receive the new intervention during the modeled time horizon.
Subgroup analysis Yes, include clinical markers, diagnostic or genetic criteria, or other markers, if known, that can be used to identify appropriate subpopulations. Subgroup analyses are encouraged to help clarify incremental cost-effectiveness or value for select subpopulations. This should include patient demographics or clinical characteristics that may modify treatment effect.
Choice of comparator Existing standard of care, best available, usual care or best supportive care. Manufacturers should consult with health care decision-makers, ideally in the early phases of model development, to identify optimal modeling approaches and ensure the incorporation of appropriate comparator products.
Time horizon Analyses should incorporate a time horizon that is appropriate for the disease, treatment, and perspective being evaluated. The time horizon should be long enough to reflect all important differences in costs and outcomes between the technologies being compared.
Assumptions required Yes, documented with source citations
Preferred analytical technique Both cost-effectiveness analyses (CEA) and budget impact models (BIM) are specified in the Format. Analytical technique for CEAs should be selected based on appropriateness of use in the condition or treatment being evaluated. BIM's provide useful information to decision makers related to the expected financial effects of product adoption from a payer perspective.
Costs to be included All resources used that are relevant to the analysis, including costs of the product and other medical resources consumed within each clinical pathway, including the economic impact of adverse events.
Source of costs Unit cost data most relevant to the decision-maker, based on health care system data. If specific health care system data are not available, costs from representative U.S. private payers, Medicare, and others may be used.
Modeling Yes, where direct primary or secondary empirical evaluation of effectiveness is not available or is limited to relatively short duration studies compared with the typical duration of the disease.
Systematic review of evidences Yes, from best designed and least biased sources relevant to the question and population under study. Results of systematic reviews may be provided as additional supporting evidence.
Preference for effectiveness over efficacy Yes, when available, RCT data should be assessed and considered as the basis of all efficacy or effectiveness estimates. When available, real-world evidence, including prospective and retrospective observational trials, and direct and indirect comparisons should be assessed for relevance and validity. If appropriate, these data should also be incorporated into the model. When feasible and scientifically plausible, efficacy results from RCTs should be transformed into effectiveness parameters. For example, this may involve inclusion of an adherence parameter into the model based on observational data. Documentation and clear description of the methodology will be necessary for health care system staff to evaluate the validity of this approach.
Preferred outcome measure Assess clinical events, life expectancy, and QALYs – with the latter two outcomes primarily relevant for lifetime timeframe analyses. 
Preferred method to derive utility Utility values from general health assessment instruments should ideally be derived from the general population, but this may be impractical and in some situations trial-derived utilities may be used.
Equity issues stated Yes, services intended to accompany a specialty pharmaceutical at launch should include financial assistance to patients.
Discounting costs When appropriate, adjustment for the time preference should be incorporated and should follow ISPOR Task Force on good research practices recommendations.
Discounting outcomes When appropriate, adjustment for the time preference should be incorporated and should follow ISPOR Task Force on good research practices recommendations.
Sensitivity analysis-parameters and range Analysts should justify the distribution used for each parameter that is included in sensitivity analyses. The use of arbitrary lower and upper values is strongly discouraged. Use of generally accepted confidence intervals (95%) should be employed if parameter uncertainty is, at least largely, characterized by random error. The 3-5 parameters and 2-3 assumptions that have the greatest impact on the results should be identified.
Sensitivity analysis-methods Both univariate and probabilistic sensitivity analyses should be conducted. A comprehensive one-way sensitivity analysis of all parameters in the model is strongly recommended, including assessment of impacts on both incremental effectiveness (e.g., QALYs) and cost-effectiveness. 
Presenting results Comprehensive one-way sensitivity analysis of all parameters in the model is strongly recommended, including assessment of impacts on both incremental effectiveness (e.g., QALYs) and cost-effectiveness. It is recommended that results of probabilistic sensitivity analyses include cost-effectiveness scatter plots and acceptability curves.
Incremental analysis Yes
Total costs vs effectiveness (cost/effectiveness ratio) Yes
Portability of results (Generalizability) Yes
Financial impact analysis Budget impact models are important to assess affordability, but financial analyses (e.g., drug cost only) are not directly relevant to value-based decision-making. Recommended to present the findings as both the PMPM and the total budget impact on the health system.
Mandatory or recommended or voluntary The AMCP Format is a guidance, not a mandate; however, many US payer organizations now require the Format as a core evidence communication resource to support payer decision-making. Manufacturers have final discretion on how to communicate information for health care decision-makers' consideration.


The key features form was contributed by: 

Sherry Andes, PharmD, Manager, Medical Outcomes Value Liaison, Ferring Pharmaceuticals, Louisville, KY, USA

Aimee Loucks, PharmD, Director, Clinical Pharmacy Services, Kaiser Permanente, Seattle, WA, USA

Stephen Kogut, PhD, MBA, Professor, University of Rhode Island, Kingston, Rhode Island, USA

Jeff Lee, PharmD, FCCP, Vice President, US Value Strategy and Services, Lumanity, Nashville, TN, USA

Elizabeth Hill, PharmD, MBA, Director, Professional Affairs, Academy of Managed Care Pharmacy, Alexandria, VA, USA

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