Multi-Criteria Decision Analytic Model for the Comparative Formulary Inclusion of Direct Oral Anticoagulant in Qatar
Abstract
Aim: The formulary inclusion of direct oral anticoagulant (DOACs) in the government
hospital health services in Qatar is not comparative or restricted. Requests to include a
DOAC in the formulary are typically accepted if evidence of efficacy and tolerability
is presented. There are no literature reports of a DOAC scoring model that is based on
comparatively weighted multiple indications and no reports of DOAC selection in
Qatar or the Middle East. This study aims to compare first-line use of the DOACs that
are available in Qatar.
Methods: A comparative, evidence-based multicriteria decision analysis (MCDA)
model was constructed to follow the multiple indications and criteria of DOACs.
Literature and best evidence informed and guided the selection criteria of DOACs,
oversees and confirmed by a specialized expert panel. Input from the relevant local
practitioner population steered the relative weighting of selection criteria. The base case
MCDA model was based on multivariate uncertainty analysis to account for inherent
input uncertainty. Comparatively scored DOACs, exceeding a defined score threshold,
were recommended for formulary selection. The model comprised main criteria and
sub-criteria. The criteria of most weight in differential selection were determined. Out
of all available DOACs, inside and outside Qatar, the top-scoring DOACs were
suggested as formulary options, followed by others for nonformulary use. About the
DOACs available in Qatar, and based on the outcomes of the MCDA model, the DOAC
that is best suited for first-line use at current HMC practices will be determined. Results: The selection criteria included 10 main criteria and 28 sub-criteria. Main
criteria according to their weight from highest to lowest are; clinical efficacy, safety,
dosage frequency, drug interaction, availability of a specific and approved reversal
agent, ease of switching during treatment, regimen flexibility, special population
requirements, pharmacokinetics properties, and administration as a crushed tablet.
DOACs total achieved performance mean scores were as follow: apixaban 711.8 (95%
CI 711.5 – 712.1), rivaroxaban 699.6 (95% CI, 699.4 – 699.9), edoxaban 658.7 (95%
CI, 658.4 – 658.9), and dabigatran 569.6, (95% CI 569.4 – 569.8). Based on one-way
sensitivity analysis, excluding dosage frequency did not change DOACs ranking.
However, DOACs recommendations changed to only apixaban being recommended as
a formulary option, while dabigatran, rivaroxaban, and edoxaban are recommended to
be excluded from the formulary. Excluding availability of a specific and approved
reversal agent, however, resulted in edoxaban being ranked first with mean score of
737.2 (95% CI, 736.9 - 737.5), followed by apixaban 677.2 (95% CI,676.9 - 677.5),
rivaroxaban 663.5 (95% CI, 663.2 - 663.8), and dabigatran 518.1 (95% CI, 517.9 -
518.3). As a result, both edoxaban and apixaban were recommended as formulary
option, and rivaroxaban as non-formulary option, and dabigatran is recommended to be
excluded from the formulary. Both multivariate and scenario sensitivity analysis did
not change the results of the base-case analysis.
Conclusion: When incorporating and investigating the input of all key relative criteria
of DOACs from relevant local practitioners in the MCDA model, apixaban was ranked
the highest followed by rivaroxaban, edoxaban, and lastly dabigatran. Thus, apixaban
and rivaroxaban were recommended as formulary options, edoxaban for non-formulary
use, and dabigatran was rejected.
Implication: The implementation of a locally developed DOACs-specific comparative MCDA scoring model, will help assess any future DOAC, against locally available
DOACs, for the purpose of making decisions about formulary inclusion. Results of the
study will help in determining the best of the Qatari available DOACs for first-line use,
based on evidence-based clinical, safety and economic data
DOI/handle
http://hdl.handle.net/10576/15323Collections
- Master in Pharmacy [58 items ]