Predictors of negotiated prices for new drugs in Germany.

Afschin Gandjour, Sofia Schüßler, Thomas Hammerschmidt, Charalabos-Markos Dintsios
Author Information
  1. Afschin Gandjour: Frankfurt School of Finance and Management, Frankfurt am Main, Germany.
  2. Sofia Schüßler: Frankfurt School of Finance and Management, Frankfurt am Main, Germany.
  3. Thomas Hammerschmidt: Faculty of Applied Health and Social Sciences, Technical University of Applied Sciences Rosenheim, Rosenheim, Germany.
  4. Charalabos-Markos Dintsios: Institute for Health Services Research and Health Economics, Centre for Health and Society, Faculty of Medicine, Heinrich-Heine University Düsseldorf, Gebäude 12.49, Moorenstraße 5, 40225, Düsseldorf, Germany. dintsios@hhu.de. ORCID

Abstract

INTRODUCTION: In Germany, all new, innovative medicines are subject to an early benefit assessment by the German Federal Joint Committee with subsequent price negotiation and optional arbitration. The purpose of this study was to identify drivers of negotiated (including arbitrated) prices of new, non-orphan innovative medicines in Germany.
METHODS: The analysis considered all non-orphan drugs that underwent a benefit appraisal between January 2011 and June 2016, and displayed a reimbursement price in the German Drug Directory (Lauer-Taxe) in November 2017. Negotiated annual treatment costs were analyzed with respect to 11 explanatory variables in regression models.
RESULTS: The total sample included 106 non-orphan drugs. The analysis showed a significant and positive association of log-transformed negotiated annual treatment cost of new medicines with log-transformed annual treatment cost of its comparator(s), extent of added benefit, and log-transformed size of the target population. Analyzing the effects of specific endpoints instead of the overall added benefit revealed that the single endpoint with the largest impact on price is adverse events (AEs). Surprisingly, an increase in AEs significantly increased the price. Various subgroup and sensitivity analyses demonstrated the robustness of the results. The adjusted R squared for all models was above 80%.
CONCLUSIONS: The analysis was able to confirm that variables whose consideration is mandated by law are, in fact, the key drivers of negotiated prices. Somewhat puzzling, the analysis also found an increase in AEs to move prices significantly upward.

Keywords

References

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MeSH Term

Costs and Cost Analysis
Drug Costs
Germany
Humans
Negotiating
Quality of Life

Word Cloud

Created with Highcharts 10.0.0Germanynewmedicinesbenefitpricenegotiatedpricesanalysisnon-orphandrugsannualtreatmentlog-transformedAEsinnovativeGermandriversvariablesmodelscostaddedincreasesignificantlyINTRODUCTION:subjectearlyassessmentFederalJointCommitteesubsequentnegotiationoptionalarbitrationpurposestudyidentifyincludingarbitratedMETHODS:consideredunderwentappraisalJanuary2011June2016displayedreimbursementDrugDirectoryLauer-TaxeNovember2017Negotiatedcostsanalyzedrespect11explanatoryregressionRESULTS:totalsampleincluded106showedsignificantpositiveassociationcomparatorsextentsizetargetpopulationAnalyzingeffectsspecificendpointsinsteadoverallrevealedsingleendpointlargestimpactadverseeventsSurprisinglyincreasedVarioussubgroupsensitivityanalysesdemonstratedrobustnessresultsadjustedRsquared80%CONCLUSIONS:ableconfirmwhoseconsiderationmandatedlawfactkeySomewhatpuzzlingalsofoundmoveupwardPredictorsAMNOGInnovativeNegotiationPredictionPricing

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