A critical assessment framework to identify, quantify and interpret the sources of uncertainty in cost-effectiveness analyses

Background Using a standardized approach to describe the sources of uncertainty in cost-effectiveness analyses might bring added value to the local critical assessment procedure of reimbursement submissions in Hungary. The aim of this research is to present a procedural framework to identify, quanti...
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Autor*in:	Merész, Gergő [verfasserIn] Dóczy, Veronika Hölgyesi, Áron Németh, Gergely

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Technology Assessment, Biomedical (MeSH unique ID: D013673) Decision Making, Organizational (MeSH unique ID: D003659) Evidence-Based Medicine (MeSH unique ID: D019317) Uncertainty (MeSH unique ID: D035501) Prostatic Neoplasms, Castration-Resistant (MeSH unique ID: D064129)

Anmerkung:	© The Author(s) 2022

Übergeordnetes Werk:	Enthalten in: BMC health services research - London : BioMed Central, 2001, 22(2022), 1 vom: 25. Juni
Übergeordnetes Werk:	volume:22 ; year:2022 ; number:1 ; day:25 ; month:06

Links:	Volltext

DOI / URN:	10.1186/s12913-022-08214-9

Katalog-ID:	SPR05081088X

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520			\|a Background Using a standardized approach to describe the sources of uncertainty in cost-effectiveness analyses might bring added value to the local critical assessment procedure of reimbursement submissions in Hungary. The aim of this research is to present a procedural framework to identify, quantify and interpret sources of uncertainty, using the reimbursement dossier of darolutamide as an illustrative example. Methods In the procedural framework designed for the critical assessment of cost-effectiveness analyses, the quantifiability of an identified source of uncertainty is assessed through the input parameters of the originally submitted model, which is followed by the interpretation of its impact on estimates of costs and outcomes compared to the base case cost-effectiveness conclusion. Results Based on our experiences with the recent reimbursement dossier of darolutamide, the significant and quantifiable sources of uncertainty were the time horizon of the economic analysis; the restriction of the efficacy analysis population; long-term relative effectiveness of darolutamide; price discount on subsequent therapies. We identified resource use patterns for comparator and subsequent therapies as a quantifiable, yet non-significant source of uncertainty. The EQ-5D value set used to estimate utility values was identified as a non-quantifiable and potentially not significant source of uncertainty. Conclusions The procedural framework, demonstrated with an example, was sufficiently flexible and coherent to document and structure the sources of uncertainty in cost-effectiveness analyses. The full-scale use of this framework is desirable during the decision-making process for reimbursement in Hungary. The further formalization of identifying sources of uncertainty is a possible subject of methodological development.
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allfields	10.1186/s12913-022-08214-9 doi (DE-627)SPR05081088X (SPR)s12913-022-08214-9-e DE-627 ger DE-627 rakwb eng Merész, Gergő verfasserin aut A critical assessment framework to identify, quantify and interpret the sources of uncertainty in cost-effectiveness analyses 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Background Using a standardized approach to describe the sources of uncertainty in cost-effectiveness analyses might bring added value to the local critical assessment procedure of reimbursement submissions in Hungary. The aim of this research is to present a procedural framework to identify, quantify and interpret sources of uncertainty, using the reimbursement dossier of darolutamide as an illustrative example. Methods In the procedural framework designed for the critical assessment of cost-effectiveness analyses, the quantifiability of an identified source of uncertainty is assessed through the input parameters of the originally submitted model, which is followed by the interpretation of its impact on estimates of costs and outcomes compared to the base case cost-effectiveness conclusion. Results Based on our experiences with the recent reimbursement dossier of darolutamide, the significant and quantifiable sources of uncertainty were the time horizon of the economic analysis; the restriction of the efficacy analysis population; long-term relative effectiveness of darolutamide; price discount on subsequent therapies. We identified resource use patterns for comparator and subsequent therapies as a quantifiable, yet non-significant source of uncertainty. The EQ-5D value set used to estimate utility values was identified as a non-quantifiable and potentially not significant source of uncertainty. Conclusions The procedural framework, demonstrated with an example, was sufficiently flexible and coherent to document and structure the sources of uncertainty in cost-effectiveness analyses. The full-scale use of this framework is desirable during the decision-making process for reimbursement in Hungary. The further formalization of identifying sources of uncertainty is a possible subject of methodological development. Technology Assessment, Biomedical (MeSH unique ID: D013673) (dpeaa)DE-He213 Decision Making, Organizational (MeSH unique ID: D003659) (dpeaa)DE-He213 Evidence-Based Medicine (MeSH unique ID: D019317) (dpeaa)DE-He213 Uncertainty (MeSH unique ID: D035501) (dpeaa)DE-He213 Prostatic Neoplasms, Castration-Resistant (MeSH unique ID: D064129) (dpeaa)DE-He213 Dóczy, Veronika aut Hölgyesi, Áron aut Németh, Gergely aut Enthalten in BMC health services research London : BioMed Central, 2001 22(2022), 1 vom: 25. Juni (DE-627)331018756 (DE-600)2050434-2 1472-6963 nnns volume:22 year:2022 number:1 day:25 month:06 https://dx.doi.org/10.1186/s12913-022-08214-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2129 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2022 1 25 06
spelling	10.1186/s12913-022-08214-9 doi (DE-627)SPR05081088X (SPR)s12913-022-08214-9-e DE-627 ger DE-627 rakwb eng Merész, Gergő verfasserin aut A critical assessment framework to identify, quantify and interpret the sources of uncertainty in cost-effectiveness analyses 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Background Using a standardized approach to describe the sources of uncertainty in cost-effectiveness analyses might bring added value to the local critical assessment procedure of reimbursement submissions in Hungary. The aim of this research is to present a procedural framework to identify, quantify and interpret sources of uncertainty, using the reimbursement dossier of darolutamide as an illustrative example. Methods In the procedural framework designed for the critical assessment of cost-effectiveness analyses, the quantifiability of an identified source of uncertainty is assessed through the input parameters of the originally submitted model, which is followed by the interpretation of its impact on estimates of costs and outcomes compared to the base case cost-effectiveness conclusion. Results Based on our experiences with the recent reimbursement dossier of darolutamide, the significant and quantifiable sources of uncertainty were the time horizon of the economic analysis; the restriction of the efficacy analysis population; long-term relative effectiveness of darolutamide; price discount on subsequent therapies. We identified resource use patterns for comparator and subsequent therapies as a quantifiable, yet non-significant source of uncertainty. The EQ-5D value set used to estimate utility values was identified as a non-quantifiable and potentially not significant source of uncertainty. Conclusions The procedural framework, demonstrated with an example, was sufficiently flexible and coherent to document and structure the sources of uncertainty in cost-effectiveness analyses. The full-scale use of this framework is desirable during the decision-making process for reimbursement in Hungary. The further formalization of identifying sources of uncertainty is a possible subject of methodological development. Technology Assessment, Biomedical (MeSH unique ID: D013673) (dpeaa)DE-He213 Decision Making, Organizational (MeSH unique ID: D003659) (dpeaa)DE-He213 Evidence-Based Medicine (MeSH unique ID: D019317) (dpeaa)DE-He213 Uncertainty (MeSH unique ID: D035501) (dpeaa)DE-He213 Prostatic Neoplasms, Castration-Resistant (MeSH unique ID: D064129) (dpeaa)DE-He213 Dóczy, Veronika aut Hölgyesi, Áron aut Németh, Gergely aut Enthalten in BMC health services research London : BioMed Central, 2001 22(2022), 1 vom: 25. Juni (DE-627)331018756 (DE-600)2050434-2 1472-6963 nnns volume:22 year:2022 number:1 day:25 month:06 https://dx.doi.org/10.1186/s12913-022-08214-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2129 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2022 1 25 06
allfields_unstemmed	10.1186/s12913-022-08214-9 doi (DE-627)SPR05081088X (SPR)s12913-022-08214-9-e DE-627 ger DE-627 rakwb eng Merész, Gergő verfasserin aut A critical assessment framework to identify, quantify and interpret the sources of uncertainty in cost-effectiveness analyses 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Background Using a standardized approach to describe the sources of uncertainty in cost-effectiveness analyses might bring added value to the local critical assessment procedure of reimbursement submissions in Hungary. The aim of this research is to present a procedural framework to identify, quantify and interpret sources of uncertainty, using the reimbursement dossier of darolutamide as an illustrative example. Methods In the procedural framework designed for the critical assessment of cost-effectiveness analyses, the quantifiability of an identified source of uncertainty is assessed through the input parameters of the originally submitted model, which is followed by the interpretation of its impact on estimates of costs and outcomes compared to the base case cost-effectiveness conclusion. Results Based on our experiences with the recent reimbursement dossier of darolutamide, the significant and quantifiable sources of uncertainty were the time horizon of the economic analysis; the restriction of the efficacy analysis population; long-term relative effectiveness of darolutamide; price discount on subsequent therapies. We identified resource use patterns for comparator and subsequent therapies as a quantifiable, yet non-significant source of uncertainty. The EQ-5D value set used to estimate utility values was identified as a non-quantifiable and potentially not significant source of uncertainty. Conclusions The procedural framework, demonstrated with an example, was sufficiently flexible and coherent to document and structure the sources of uncertainty in cost-effectiveness analyses. The full-scale use of this framework is desirable during the decision-making process for reimbursement in Hungary. The further formalization of identifying sources of uncertainty is a possible subject of methodological development. Technology Assessment, Biomedical (MeSH unique ID: D013673) (dpeaa)DE-He213 Decision Making, Organizational (MeSH unique ID: D003659) (dpeaa)DE-He213 Evidence-Based Medicine (MeSH unique ID: D019317) (dpeaa)DE-He213 Uncertainty (MeSH unique ID: D035501) (dpeaa)DE-He213 Prostatic Neoplasms, Castration-Resistant (MeSH unique ID: D064129) (dpeaa)DE-He213 Dóczy, Veronika aut Hölgyesi, Áron aut Németh, Gergely aut Enthalten in BMC health services research London : BioMed Central, 2001 22(2022), 1 vom: 25. Juni (DE-627)331018756 (DE-600)2050434-2 1472-6963 nnns volume:22 year:2022 number:1 day:25 month:06 https://dx.doi.org/10.1186/s12913-022-08214-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2129 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2022 1 25 06
allfieldsGer	10.1186/s12913-022-08214-9 doi (DE-627)SPR05081088X (SPR)s12913-022-08214-9-e DE-627 ger DE-627 rakwb eng Merész, Gergő verfasserin aut A critical assessment framework to identify, quantify and interpret the sources of uncertainty in cost-effectiveness analyses 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Background Using a standardized approach to describe the sources of uncertainty in cost-effectiveness analyses might bring added value to the local critical assessment procedure of reimbursement submissions in Hungary. The aim of this research is to present a procedural framework to identify, quantify and interpret sources of uncertainty, using the reimbursement dossier of darolutamide as an illustrative example. Methods In the procedural framework designed for the critical assessment of cost-effectiveness analyses, the quantifiability of an identified source of uncertainty is assessed through the input parameters of the originally submitted model, which is followed by the interpretation of its impact on estimates of costs and outcomes compared to the base case cost-effectiveness conclusion. Results Based on our experiences with the recent reimbursement dossier of darolutamide, the significant and quantifiable sources of uncertainty were the time horizon of the economic analysis; the restriction of the efficacy analysis population; long-term relative effectiveness of darolutamide; price discount on subsequent therapies. We identified resource use patterns for comparator and subsequent therapies as a quantifiable, yet non-significant source of uncertainty. The EQ-5D value set used to estimate utility values was identified as a non-quantifiable and potentially not significant source of uncertainty. Conclusions The procedural framework, demonstrated with an example, was sufficiently flexible and coherent to document and structure the sources of uncertainty in cost-effectiveness analyses. The full-scale use of this framework is desirable during the decision-making process for reimbursement in Hungary. The further formalization of identifying sources of uncertainty is a possible subject of methodological development. Technology Assessment, Biomedical (MeSH unique ID: D013673) (dpeaa)DE-He213 Decision Making, Organizational (MeSH unique ID: D003659) (dpeaa)DE-He213 Evidence-Based Medicine (MeSH unique ID: D019317) (dpeaa)DE-He213 Uncertainty (MeSH unique ID: D035501) (dpeaa)DE-He213 Prostatic Neoplasms, Castration-Resistant (MeSH unique ID: D064129) (dpeaa)DE-He213 Dóczy, Veronika aut Hölgyesi, Áron aut Németh, Gergely aut Enthalten in BMC health services research London : BioMed Central, 2001 22(2022), 1 vom: 25. Juni (DE-627)331018756 (DE-600)2050434-2 1472-6963 nnns volume:22 year:2022 number:1 day:25 month:06 https://dx.doi.org/10.1186/s12913-022-08214-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2129 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2022 1 25 06
allfieldsSound	10.1186/s12913-022-08214-9 doi (DE-627)SPR05081088X (SPR)s12913-022-08214-9-e DE-627 ger DE-627 rakwb eng Merész, Gergő verfasserin aut A critical assessment framework to identify, quantify and interpret the sources of uncertainty in cost-effectiveness analyses 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Background Using a standardized approach to describe the sources of uncertainty in cost-effectiveness analyses might bring added value to the local critical assessment procedure of reimbursement submissions in Hungary. The aim of this research is to present a procedural framework to identify, quantify and interpret sources of uncertainty, using the reimbursement dossier of darolutamide as an illustrative example. Methods In the procedural framework designed for the critical assessment of cost-effectiveness analyses, the quantifiability of an identified source of uncertainty is assessed through the input parameters of the originally submitted model, which is followed by the interpretation of its impact on estimates of costs and outcomes compared to the base case cost-effectiveness conclusion. Results Based on our experiences with the recent reimbursement dossier of darolutamide, the significant and quantifiable sources of uncertainty were the time horizon of the economic analysis; the restriction of the efficacy analysis population; long-term relative effectiveness of darolutamide; price discount on subsequent therapies. We identified resource use patterns for comparator and subsequent therapies as a quantifiable, yet non-significant source of uncertainty. The EQ-5D value set used to estimate utility values was identified as a non-quantifiable and potentially not significant source of uncertainty. Conclusions The procedural framework, demonstrated with an example, was sufficiently flexible and coherent to document and structure the sources of uncertainty in cost-effectiveness analyses. The full-scale use of this framework is desirable during the decision-making process for reimbursement in Hungary. The further formalization of identifying sources of uncertainty is a possible subject of methodological development. Technology Assessment, Biomedical (MeSH unique ID: D013673) (dpeaa)DE-He213 Decision Making, Organizational (MeSH unique ID: D003659) (dpeaa)DE-He213 Evidence-Based Medicine (MeSH unique ID: D019317) (dpeaa)DE-He213 Uncertainty (MeSH unique ID: D035501) (dpeaa)DE-He213 Prostatic Neoplasms, Castration-Resistant (MeSH unique ID: D064129) (dpeaa)DE-He213 Dóczy, Veronika aut Hölgyesi, Áron aut Németh, Gergely aut Enthalten in BMC health services research London : BioMed Central, 2001 22(2022), 1 vom: 25. Juni (DE-627)331018756 (DE-600)2050434-2 1472-6963 nnns volume:22 year:2022 number:1 day:25 month:06 https://dx.doi.org/10.1186/s12913-022-08214-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2129 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2022 1 25 06
language	English
source	Enthalten in BMC health services research 22(2022), 1 vom: 25. Juni volume:22 year:2022 number:1 day:25 month:06
sourceStr	Enthalten in BMC health services research 22(2022), 1 vom: 25. Juni volume:22 year:2022 number:1 day:25 month:06
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Technology Assessment, Biomedical (MeSH unique ID: D013673) Decision Making, Organizational (MeSH unique ID: D003659) Evidence-Based Medicine (MeSH unique ID: D019317) Uncertainty (MeSH unique ID: D035501) Prostatic Neoplasms, Castration-Resistant (MeSH unique ID: D064129)
isfreeaccess_bool	true
container_title	BMC health services research
authorswithroles_txt_mv	Merész, Gergő @@aut@@ Dóczy, Veronika @@aut@@ Hölgyesi, Áron @@aut@@ Németh, Gergely @@aut@@
publishDateDaySort_date	2022-06-25T00:00:00Z
hierarchy_top_id	331018756
id	SPR05081088X
language_de	englisch
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The aim of this research is to present a procedural framework to identify, quantify and interpret sources of uncertainty, using the reimbursement dossier of darolutamide as an illustrative example. Methods In the procedural framework designed for the critical assessment of cost-effectiveness analyses, the quantifiability of an identified source of uncertainty is assessed through the input parameters of the originally submitted model, which is followed by the interpretation of its impact on estimates of costs and outcomes compared to the base case cost-effectiveness conclusion. Results Based on our experiences with the recent reimbursement dossier of darolutamide, the significant and quantifiable sources of uncertainty were the time horizon of the economic analysis; the restriction of the efficacy analysis population; long-term relative effectiveness of darolutamide; price discount on subsequent therapies. We identified resource use patterns for comparator and subsequent therapies as a quantifiable, yet non-significant source of uncertainty. The EQ-5D value set used to estimate utility values was identified as a non-quantifiable and potentially not significant source of uncertainty. Conclusions The procedural framework, demonstrated with an example, was sufficiently flexible and coherent to document and structure the sources of uncertainty in cost-effectiveness analyses. The full-scale use of this framework is desirable during the decision-making process for reimbursement in Hungary. 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author	Merész, Gergő
spellingShingle	Merész, Gergő misc Technology Assessment, Biomedical (MeSH unique ID: D013673) misc Decision Making, Organizational (MeSH unique ID: D003659) misc Evidence-Based Medicine (MeSH unique ID: D019317) misc Uncertainty (MeSH unique ID: D035501) misc Prostatic Neoplasms, Castration-Resistant (MeSH unique ID: D064129) A critical assessment framework to identify, quantify and interpret the sources of uncertainty in cost-effectiveness analyses
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topic_title	A critical assessment framework to identify, quantify and interpret the sources of uncertainty in cost-effectiveness analyses Technology Assessment, Biomedical (MeSH unique ID: D013673) (dpeaa)DE-He213 Decision Making, Organizational (MeSH unique ID: D003659) (dpeaa)DE-He213 Evidence-Based Medicine (MeSH unique ID: D019317) (dpeaa)DE-He213 Uncertainty (MeSH unique ID: D035501) (dpeaa)DE-He213 Prostatic Neoplasms, Castration-Resistant (MeSH unique ID: D064129) (dpeaa)DE-He213
topic	misc Technology Assessment, Biomedical (MeSH unique ID: D013673) misc Decision Making, Organizational (MeSH unique ID: D003659) misc Evidence-Based Medicine (MeSH unique ID: D019317) misc Uncertainty (MeSH unique ID: D035501) misc Prostatic Neoplasms, Castration-Resistant (MeSH unique ID: D064129)
topic_unstemmed	misc Technology Assessment, Biomedical (MeSH unique ID: D013673) misc Decision Making, Organizational (MeSH unique ID: D003659) misc Evidence-Based Medicine (MeSH unique ID: D019317) misc Uncertainty (MeSH unique ID: D035501) misc Prostatic Neoplasms, Castration-Resistant (MeSH unique ID: D064129)
topic_browse	misc Technology Assessment, Biomedical (MeSH unique ID: D013673) misc Decision Making, Organizational (MeSH unique ID: D003659) misc Evidence-Based Medicine (MeSH unique ID: D019317) misc Uncertainty (MeSH unique ID: D035501) misc Prostatic Neoplasms, Castration-Resistant (MeSH unique ID: D064129)
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title	A critical assessment framework to identify, quantify and interpret the sources of uncertainty in cost-effectiveness analyses
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title_full	A critical assessment framework to identify, quantify and interpret the sources of uncertainty in cost-effectiveness analyses
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title_sort	critical assessment framework to identify, quantify and interpret the sources of uncertainty in cost-effectiveness analyses
title_auth	A critical assessment framework to identify, quantify and interpret the sources of uncertainty in cost-effectiveness analyses
abstract	Background Using a standardized approach to describe the sources of uncertainty in cost-effectiveness analyses might bring added value to the local critical assessment procedure of reimbursement submissions in Hungary. The aim of this research is to present a procedural framework to identify, quantify and interpret sources of uncertainty, using the reimbursement dossier of darolutamide as an illustrative example. Methods In the procedural framework designed for the critical assessment of cost-effectiveness analyses, the quantifiability of an identified source of uncertainty is assessed through the input parameters of the originally submitted model, which is followed by the interpretation of its impact on estimates of costs and outcomes compared to the base case cost-effectiveness conclusion. Results Based on our experiences with the recent reimbursement dossier of darolutamide, the significant and quantifiable sources of uncertainty were the time horizon of the economic analysis; the restriction of the efficacy analysis population; long-term relative effectiveness of darolutamide; price discount on subsequent therapies. We identified resource use patterns for comparator and subsequent therapies as a quantifiable, yet non-significant source of uncertainty. The EQ-5D value set used to estimate utility values was identified as a non-quantifiable and potentially not significant source of uncertainty. Conclusions The procedural framework, demonstrated with an example, was sufficiently flexible and coherent to document and structure the sources of uncertainty in cost-effectiveness analyses. The full-scale use of this framework is desirable during the decision-making process for reimbursement in Hungary. The further formalization of identifying sources of uncertainty is a possible subject of methodological development. © The Author(s) 2022
abstractGer	Background Using a standardized approach to describe the sources of uncertainty in cost-effectiveness analyses might bring added value to the local critical assessment procedure of reimbursement submissions in Hungary. The aim of this research is to present a procedural framework to identify, quantify and interpret sources of uncertainty, using the reimbursement dossier of darolutamide as an illustrative example. Methods In the procedural framework designed for the critical assessment of cost-effectiveness analyses, the quantifiability of an identified source of uncertainty is assessed through the input parameters of the originally submitted model, which is followed by the interpretation of its impact on estimates of costs and outcomes compared to the base case cost-effectiveness conclusion. Results Based on our experiences with the recent reimbursement dossier of darolutamide, the significant and quantifiable sources of uncertainty were the time horizon of the economic analysis; the restriction of the efficacy analysis population; long-term relative effectiveness of darolutamide; price discount on subsequent therapies. We identified resource use patterns for comparator and subsequent therapies as a quantifiable, yet non-significant source of uncertainty. The EQ-5D value set used to estimate utility values was identified as a non-quantifiable and potentially not significant source of uncertainty. Conclusions The procedural framework, demonstrated with an example, was sufficiently flexible and coherent to document and structure the sources of uncertainty in cost-effectiveness analyses. The full-scale use of this framework is desirable during the decision-making process for reimbursement in Hungary. The further formalization of identifying sources of uncertainty is a possible subject of methodological development. © The Author(s) 2022
abstract_unstemmed	Background Using a standardized approach to describe the sources of uncertainty in cost-effectiveness analyses might bring added value to the local critical assessment procedure of reimbursement submissions in Hungary. The aim of this research is to present a procedural framework to identify, quantify and interpret sources of uncertainty, using the reimbursement dossier of darolutamide as an illustrative example. Methods In the procedural framework designed for the critical assessment of cost-effectiveness analyses, the quantifiability of an identified source of uncertainty is assessed through the input parameters of the originally submitted model, which is followed by the interpretation of its impact on estimates of costs and outcomes compared to the base case cost-effectiveness conclusion. Results Based on our experiences with the recent reimbursement dossier of darolutamide, the significant and quantifiable sources of uncertainty were the time horizon of the economic analysis; the restriction of the efficacy analysis population; long-term relative effectiveness of darolutamide; price discount on subsequent therapies. We identified resource use patterns for comparator and subsequent therapies as a quantifiable, yet non-significant source of uncertainty. The EQ-5D value set used to estimate utility values was identified as a non-quantifiable and potentially not significant source of uncertainty. Conclusions The procedural framework, demonstrated with an example, was sufficiently flexible and coherent to document and structure the sources of uncertainty in cost-effectiveness analyses. The full-scale use of this framework is desirable during the decision-making process for reimbursement in Hungary. The further formalization of identifying sources of uncertainty is a possible subject of methodological development. © The Author(s) 2022
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title_short	A critical assessment framework to identify, quantify and interpret the sources of uncertainty in cost-effectiveness analyses
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A critical assessment framework to identify, quantify and interpret the sources of uncertainty in cost-effectiveness analyses

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