Measuring patient preferences through the time trade-off method for orthopedic conditions on large samples
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Gestão e sociedade |
DOI: | 10.21171/ges.v12i31.2318 |
Texto Completo: | https://ges.face.ufmg.br/index.php/gestaoesociedade/article/view/2318 |
Resumo: | Background: In cost-effectiveness analyses, Quality-Adjusted Life Years (QALY) remains one of the most widely used health effect measure. Among the various methods of estimating utility values, time trade-off (TTO) has traditionally been one of the dominant methods for eliciting utilities, however it has been presenting several practical impediments to provide a high and fast collecting process.Objective: To test a method of collecting TTO-derived utilities using a platform called Amazon’s Mechanical Turk (MTurk) that provides reliable, fast and inexpensive data.Methods: A pre-programmed interactive questionnaire was design to simulate a live TTO interview using Qualtrics. To validate the results members of the Research on Research (RoR) Group not aware of the research agreed to answer the same questions on a videoconference live interview. We determined feasibility through assessment quality and cost/benefit relation indicators. In addition, this paper followed the framework for reproducible research reports proposed by our group.Results: Results: Our results showed that the MTurk population is representative of the US population (based on 2012 census) and there were no differences on the willingness to live when comparing the MTurk sample and the live interview sample, and also no differences of the WTL when comparing the different questionnaire designs developed. Preference results showed differences only for race (between others and African-Americans, and other and white), and overall median values of 0.83 (Q1=0.83;Q3=0.90).Conclusions: MTurk is a reliable web place to collect large sample using the TTO method, and should be used to collect utility data for CEA. |
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oai:ojs.pkp.sfu.ca:article/2318 |
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UFMG-19 |
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Gestão e sociedade |
spelling |
Measuring patient preferences through the time trade-off method for orthopedic conditions on large samplesPublic Healthcost-effectiveness analysesQuality-Adjusted Life YearsBackground: In cost-effectiveness analyses, Quality-Adjusted Life Years (QALY) remains one of the most widely used health effect measure. Among the various methods of estimating utility values, time trade-off (TTO) has traditionally been one of the dominant methods for eliciting utilities, however it has been presenting several practical impediments to provide a high and fast collecting process.Objective: To test a method of collecting TTO-derived utilities using a platform called Amazon’s Mechanical Turk (MTurk) that provides reliable, fast and inexpensive data.Methods: A pre-programmed interactive questionnaire was design to simulate a live TTO interview using Qualtrics. To validate the results members of the Research on Research (RoR) Group not aware of the research agreed to answer the same questions on a videoconference live interview. We determined feasibility through assessment quality and cost/benefit relation indicators. In addition, this paper followed the framework for reproducible research reports proposed by our group.Results: Results: Our results showed that the MTurk population is representative of the US population (based on 2012 census) and there were no differences on the willingness to live when comparing the MTurk sample and the live interview sample, and also no differences of the WTL when comparing the different questionnaire designs developed. Preference results showed differences only for race (between others and African-Americans, and other and white), and overall median values of 0.83 (Q1=0.83;Q3=0.90).Conclusions: MTurk is a reliable web place to collect large sample using the TTO method, and should be used to collect utility data for CEA.CEPEAD/FACE - UFMG2017-11-29info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://ges.face.ufmg.br/index.php/gestaoesociedade/article/view/231810.21171/ges.v12i31.2318Management & Society Electronic Journal; Vol. 12 No. 31 (2018): January/April 2018; 2173-2193Gestão e Sociedade; v. 12 n. 31 (2018): Janeiro/Abril de 2018; 2173-21931980-575610.21171/ges.v12i31reponame:Gestão e sociedadeinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGenghttps://ges.face.ufmg.br/index.php/gestaoesociedade/article/view/2318/1269Copyright (c) 2017 Gestão e Sociedadeinfo:eu-repo/semantics/openAccessYen, TalithaRodrigues, Clarissa GarciaOliveira, Aline Chotte deCalvo, Paulo Rafeal SanchesMather, RichardRouth, JonathanVissoci, João Ricardo Nickenig2019-09-07T21:21:52Zoai:ojs.pkp.sfu.ca:article/2318Revistahttps://www.gestaoesociedade.org/gestaoesociedadePUBhttps://www.gestaoesociedade.org/gestaoesociedade/oaiges@face.ufmg.br||ricardo.ges.ufmg@gmail.com||1980-57561980-5756opendoar:2019-09-07T21:21:52Gestão e sociedade - Universidade Federal de Minas Gerais (UFMG)false |
dc.title.none.fl_str_mv |
Measuring patient preferences through the time trade-off method for orthopedic conditions on large samples |
title |
Measuring patient preferences through the time trade-off method for orthopedic conditions on large samples |
spellingShingle |
Measuring patient preferences through the time trade-off method for orthopedic conditions on large samples Measuring patient preferences through the time trade-off method for orthopedic conditions on large samples Yen, Talitha Public Health cost-effectiveness analyses Quality-Adjusted Life Years Yen, Talitha Public Health cost-effectiveness analyses Quality-Adjusted Life Years |
title_short |
Measuring patient preferences through the time trade-off method for orthopedic conditions on large samples |
title_full |
Measuring patient preferences through the time trade-off method for orthopedic conditions on large samples |
title_fullStr |
Measuring patient preferences through the time trade-off method for orthopedic conditions on large samples Measuring patient preferences through the time trade-off method for orthopedic conditions on large samples |
title_full_unstemmed |
Measuring patient preferences through the time trade-off method for orthopedic conditions on large samples Measuring patient preferences through the time trade-off method for orthopedic conditions on large samples |
title_sort |
Measuring patient preferences through the time trade-off method for orthopedic conditions on large samples |
author |
Yen, Talitha |
author_facet |
Yen, Talitha Yen, Talitha Rodrigues, Clarissa Garcia Oliveira, Aline Chotte de Calvo, Paulo Rafeal Sanches Mather, Richard Routh, Jonathan Vissoci, João Ricardo Nickenig Rodrigues, Clarissa Garcia Oliveira, Aline Chotte de Calvo, Paulo Rafeal Sanches Mather, Richard Routh, Jonathan Vissoci, João Ricardo Nickenig |
author_role |
author |
author2 |
Rodrigues, Clarissa Garcia Oliveira, Aline Chotte de Calvo, Paulo Rafeal Sanches Mather, Richard Routh, Jonathan Vissoci, João Ricardo Nickenig |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Yen, Talitha Rodrigues, Clarissa Garcia Oliveira, Aline Chotte de Calvo, Paulo Rafeal Sanches Mather, Richard Routh, Jonathan Vissoci, João Ricardo Nickenig |
dc.subject.por.fl_str_mv |
Public Health cost-effectiveness analyses Quality-Adjusted Life Years |
topic |
Public Health cost-effectiveness analyses Quality-Adjusted Life Years |
description |
Background: In cost-effectiveness analyses, Quality-Adjusted Life Years (QALY) remains one of the most widely used health effect measure. Among the various methods of estimating utility values, time trade-off (TTO) has traditionally been one of the dominant methods for eliciting utilities, however it has been presenting several practical impediments to provide a high and fast collecting process.Objective: To test a method of collecting TTO-derived utilities using a platform called Amazon’s Mechanical Turk (MTurk) that provides reliable, fast and inexpensive data.Methods: A pre-programmed interactive questionnaire was design to simulate a live TTO interview using Qualtrics. To validate the results members of the Research on Research (RoR) Group not aware of the research agreed to answer the same questions on a videoconference live interview. We determined feasibility through assessment quality and cost/benefit relation indicators. In addition, this paper followed the framework for reproducible research reports proposed by our group.Results: Results: Our results showed that the MTurk population is representative of the US population (based on 2012 census) and there were no differences on the willingness to live when comparing the MTurk sample and the live interview sample, and also no differences of the WTL when comparing the different questionnaire designs developed. Preference results showed differences only for race (between others and African-Americans, and other and white), and overall median values of 0.83 (Q1=0.83;Q3=0.90).Conclusions: MTurk is a reliable web place to collect large sample using the TTO method, and should be used to collect utility data for CEA. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-11-29 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://ges.face.ufmg.br/index.php/gestaoesociedade/article/view/2318 10.21171/ges.v12i31.2318 |
url |
https://ges.face.ufmg.br/index.php/gestaoesociedade/article/view/2318 |
identifier_str_mv |
10.21171/ges.v12i31.2318 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://ges.face.ufmg.br/index.php/gestaoesociedade/article/view/2318/1269 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2017 Gestão e Sociedade info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2017 Gestão e Sociedade |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
CEPEAD/FACE - UFMG |
publisher.none.fl_str_mv |
CEPEAD/FACE - UFMG |
dc.source.none.fl_str_mv |
Management & Society Electronic Journal; Vol. 12 No. 31 (2018): January/April 2018; 2173-2193 Gestão e Sociedade; v. 12 n. 31 (2018): Janeiro/Abril de 2018; 2173-2193 1980-5756 10.21171/ges.v12i31 reponame:Gestão e sociedade instname:Universidade Federal de Minas Gerais (UFMG) instacron:UFMG |
instname_str |
Universidade Federal de Minas Gerais (UFMG) |
instacron_str |
UFMG |
institution |
UFMG |
reponame_str |
Gestão e sociedade |
collection |
Gestão e sociedade |
repository.name.fl_str_mv |
Gestão e sociedade - Universidade Federal de Minas Gerais (UFMG) |
repository.mail.fl_str_mv |
ges@face.ufmg.br||ricardo.ges.ufmg@gmail.com|| |
_version_ |
1822179615031951360 |
dc.identifier.doi.none.fl_str_mv |
10.21171/ges.v12i31.2318 |