Using Best–Worst Scaling to Investigate Preferences in Health Care
Introduction Best–worst scaling (BWS) is becoming increasingly popular to elicit preferences in health care. However, little is known about current practice and trends in the use of BWS in health care. This study aimed to identify, review and critically appraise BWS in health care, and to identify t...
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Veröffentlicht in: | PharmacoEconomics 2016-12, Vol.34 (12), p.1195-1209 |
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description | Introduction
Best–worst scaling (BWS) is becoming increasingly popular to elicit preferences in health care. However, little is known about current practice and trends in the use of BWS in health care. This study aimed to identify, review and critically appraise BWS in health care, and to identify trends over time in key aspects of BWS.
Methods
A systematic review was conducted, using Medline (via Pubmed) and EMBASE to identify all English-language BWS studies published up until April 2016. Using a predefined extraction form, two reviewers independently selected articles and critically appraised the study quality, using the Purpose, Respondents, Explanation, Findings, Significance (PREFS) checklist. Trends over time periods (≤2010, 2011, 2012, 2013, 2014 and 2015) were assessed further.
Results
A total of 62 BWS studies were identified, of which 26 were BWS object case studies, 29 were BWS profile case studies and seven were BWS multi-profile case studies. About two thirds of the studies were performed in the last 2 years. Decreasing sample sizes and decreasing numbers of factors in BWS object case studies, as well as use of less complicated analytical methods, were observed in recent studies. The quality of the BWS studies was generally acceptable according to the PREFS checklist, except that most studies did not indicate whether the responders were similar to the non-responders.
Conclusion
Use of BWS object case and BWS profile case has drastically increased in health care, especially in the last 2 years. In contrast with previous discrete-choice experiment reviews, there is increasing use of less sophisticated analytical methods. |
doi_str_mv | 10.1007/s40273-016-0429-5 |
format | Article |
fullrecord | <record><control><sourceid>gale_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_5110583</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A714600492</galeid><sourcerecordid>A714600492</sourcerecordid><originalsourceid>FETCH-LOGICAL-c603t-9c2c008bd8b676c05859871c848e625ffbbd24fd88536c53cf5063c11938ee2f3</originalsourceid><addsrcrecordid>eNp1Uctu1TAQjRCIlsIHsEGR2LBJGduJ7WyQ2sujlSqBBBVLy3Emqatcu9i5ldjxD_whX8Kk91K1COSFrZlzzvjMKYrnDA4ZgHqda-BKVMBkBTVvq-ZBsc-YaitO9Yc3b6iUbGGveJLzJQBIofjjYo8rYoq63S_enmcfxvIY8_zrx8-vMeW5_OzstBTnWJ6Ga-r40c5Yfko4YMLgMJc-lCdop_miXNmET4tHg50yPtvdB8X5-3dfVifV2ccPp6ujs8pJEHPVOu4AdNfrTirpoNFNqxVzutYoeTMMXdfzeui1boR0jXBDQx92jLVCI_JBHBRvtrpXm26NvcMwJzuZq-TXNn030XpzvxP8hRnjtWkYo2mCBF7tBFL8tiFnZu2zw2myAeMmG6a5VByEaAj68i_oZdykQPYIJWn9vL0R3KFGO6HxYYg01y2i5kixWgLULSfU4T9QdHpcexcDDp7q9whsS3Ap5kx7v_XIwCzRm230hqI3S_Rm-fCLu8u5ZfzJmgB8C8jUCiOmO47-q_obt6-3kA</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1861002983</pqid></control><display><type>article</type><title>Using Best–Worst Scaling to Investigate Preferences in Health Care</title><source>MEDLINE</source><source>Springer Nature - Complete Springer Journals</source><creator>Cheung, Kei Long ; Wijnen, Ben F. M. ; Hollin, Ilene L. ; Janssen, Ellen M. ; Bridges, John F. ; Evers, Silvia M. A. A. ; Hiligsmann, Mickael</creator><creatorcontrib>Cheung, Kei Long ; Wijnen, Ben F. M. ; Hollin, Ilene L. ; Janssen, Ellen M. ; Bridges, John F. ; Evers, Silvia M. A. A. ; Hiligsmann, Mickael</creatorcontrib><description>Introduction
Best–worst scaling (BWS) is becoming increasingly popular to elicit preferences in health care. However, little is known about current practice and trends in the use of BWS in health care. This study aimed to identify, review and critically appraise BWS in health care, and to identify trends over time in key aspects of BWS.
Methods
A systematic review was conducted, using Medline (via Pubmed) and EMBASE to identify all English-language BWS studies published up until April 2016. Using a predefined extraction form, two reviewers independently selected articles and critically appraised the study quality, using the Purpose, Respondents, Explanation, Findings, Significance (PREFS) checklist. Trends over time periods (≤2010, 2011, 2012, 2013, 2014 and 2015) were assessed further.
Results
A total of 62 BWS studies were identified, of which 26 were BWS object case studies, 29 were BWS profile case studies and seven were BWS multi-profile case studies. About two thirds of the studies were performed in the last 2 years. Decreasing sample sizes and decreasing numbers of factors in BWS object case studies, as well as use of less complicated analytical methods, were observed in recent studies. The quality of the BWS studies was generally acceptable according to the PREFS checklist, except that most studies did not indicate whether the responders were similar to the non-responders.
Conclusion
Use of BWS object case and BWS profile case has drastically increased in health care, especially in the last 2 years. In contrast with previous discrete-choice experiment reviews, there is increasing use of less sophisticated analytical methods.</description><identifier>ISSN: 1170-7690</identifier><identifier>EISSN: 1179-2027</identifier><identifier>DOI: 10.1007/s40273-016-0429-5</identifier><identifier>PMID: 27402349</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Case studies ; Choice Behavior ; Conjoint analysis ; Decision Making ; Decomposition ; Delivery of Health Care - methods ; Evaluation ; Health Administration ; Health Economics ; Health technology assessment ; Humans ; Medical care ; Medicine ; Medicine & Public Health ; Methods ; Netherlands ; Patient Preference ; Patients ; Pharmacoeconomics and Health Outcomes ; Preferences ; Public Health ; Quality ; Quality of Life Research ; Rating scales ; Research Design ; Researchers ; Sample Size ; Systematic Review ; Trends</subject><ispartof>PharmacoEconomics, 2016-12, Vol.34 (12), p.1195-1209</ispartof><rights>The Author(s) 2016</rights><rights>COPYRIGHT 2016 Springer</rights><rights>Copyright Springer Science & Business Media Dec 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c603t-9c2c008bd8b676c05859871c848e625ffbbd24fd88536c53cf5063c11938ee2f3</citedby><cites>FETCH-LOGICAL-c603t-9c2c008bd8b676c05859871c848e625ffbbd24fd88536c53cf5063c11938ee2f3</cites><orcidid>0000-0001-7648-4556</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s40273-016-0429-5$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s40273-016-0429-5$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>230,314,777,781,882,27905,27906,41469,42538,51300</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27402349$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Cheung, Kei Long</creatorcontrib><creatorcontrib>Wijnen, Ben F. M.</creatorcontrib><creatorcontrib>Hollin, Ilene L.</creatorcontrib><creatorcontrib>Janssen, Ellen M.</creatorcontrib><creatorcontrib>Bridges, John F.</creatorcontrib><creatorcontrib>Evers, Silvia M. A. A.</creatorcontrib><creatorcontrib>Hiligsmann, Mickael</creatorcontrib><title>Using Best–Worst Scaling to Investigate Preferences in Health Care</title><title>PharmacoEconomics</title><addtitle>PharmacoEconomics</addtitle><addtitle>Pharmacoeconomics</addtitle><description>Introduction
Best–worst scaling (BWS) is becoming increasingly popular to elicit preferences in health care. However, little is known about current practice and trends in the use of BWS in health care. This study aimed to identify, review and critically appraise BWS in health care, and to identify trends over time in key aspects of BWS.
Methods
A systematic review was conducted, using Medline (via Pubmed) and EMBASE to identify all English-language BWS studies published up until April 2016. Using a predefined extraction form, two reviewers independently selected articles and critically appraised the study quality, using the Purpose, Respondents, Explanation, Findings, Significance (PREFS) checklist. Trends over time periods (≤2010, 2011, 2012, 2013, 2014 and 2015) were assessed further.
Results
A total of 62 BWS studies were identified, of which 26 were BWS object case studies, 29 were BWS profile case studies and seven were BWS multi-profile case studies. About two thirds of the studies were performed in the last 2 years. Decreasing sample sizes and decreasing numbers of factors in BWS object case studies, as well as use of less complicated analytical methods, were observed in recent studies. The quality of the BWS studies was generally acceptable according to the PREFS checklist, except that most studies did not indicate whether the responders were similar to the non-responders.
Conclusion
Use of BWS object case and BWS profile case has drastically increased in health care, especially in the last 2 years. In contrast with previous discrete-choice experiment reviews, there is increasing use of less sophisticated analytical methods.</description><subject>Case studies</subject><subject>Choice Behavior</subject><subject>Conjoint analysis</subject><subject>Decision Making</subject><subject>Decomposition</subject><subject>Delivery of Health Care - methods</subject><subject>Evaluation</subject><subject>Health Administration</subject><subject>Health Economics</subject><subject>Health technology assessment</subject><subject>Humans</subject><subject>Medical care</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Methods</subject><subject>Netherlands</subject><subject>Patient Preference</subject><subject>Patients</subject><subject>Pharmacoeconomics and Health Outcomes</subject><subject>Preferences</subject><subject>Public Health</subject><subject>Quality</subject><subject>Quality of Life Research</subject><subject>Rating scales</subject><subject>Research Design</subject><subject>Researchers</subject><subject>Sample Size</subject><subject>Systematic Review</subject><subject>Trends</subject><issn>1170-7690</issn><issn>1179-2027</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1Uctu1TAQjRCIlsIHsEGR2LBJGduJ7WyQ2sujlSqBBBVLy3Emqatcu9i5ldjxD_whX8Kk91K1COSFrZlzzvjMKYrnDA4ZgHqda-BKVMBkBTVvq-ZBsc-YaitO9Yc3b6iUbGGveJLzJQBIofjjYo8rYoq63S_enmcfxvIY8_zrx8-vMeW5_OzstBTnWJ6Ga-r40c5Yfko4YMLgMJc-lCdop_miXNmET4tHg50yPtvdB8X5-3dfVifV2ccPp6ujs8pJEHPVOu4AdNfrTirpoNFNqxVzutYoeTMMXdfzeui1boR0jXBDQx92jLVCI_JBHBRvtrpXm26NvcMwJzuZq-TXNn030XpzvxP8hRnjtWkYo2mCBF7tBFL8tiFnZu2zw2myAeMmG6a5VByEaAj68i_oZdykQPYIJWn9vL0R3KFGO6HxYYg01y2i5kixWgLULSfU4T9QdHpcexcDDp7q9whsS3Ap5kx7v_XIwCzRm230hqI3S_Rm-fCLu8u5ZfzJmgB8C8jUCiOmO47-q_obt6-3kA</recordid><startdate>20161201</startdate><enddate>20161201</enddate><creator>Cheung, Kei Long</creator><creator>Wijnen, Ben F. M.</creator><creator>Hollin, Ilene L.</creator><creator>Janssen, Ellen M.</creator><creator>Bridges, John F.</creator><creator>Evers, Silvia M. A. A.</creator><creator>Hiligsmann, Mickael</creator><general>Springer International Publishing</general><general>Springer</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>0U~</scope><scope>1-H</scope><scope>3V.</scope><scope>4T-</scope><scope>7WY</scope><scope>7WZ</scope><scope>7X7</scope><scope>7XB</scope><scope>87Z</scope><scope>88C</scope><scope>88E</scope><scope>88G</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>FYUFA</scope><scope>F~G</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>K60</scope><scope>K6~</scope><scope>K9.</scope><scope>L.-</scope><scope>L.0</scope><scope>M0C</scope><scope>M0S</scope><scope>M0T</scope><scope>M1P</scope><scope>M2M</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-7648-4556</orcidid></search><sort><creationdate>20161201</creationdate><title>Using Best–Worst Scaling to Investigate Preferences in Health Care</title><author>Cheung, Kei Long ; Wijnen, Ben F. M. ; Hollin, Ilene L. ; Janssen, Ellen M. ; Bridges, John F. ; Evers, Silvia M. A. A. ; Hiligsmann, Mickael</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c603t-9c2c008bd8b676c05859871c848e625ffbbd24fd88536c53cf5063c11938ee2f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Case studies</topic><topic>Choice Behavior</topic><topic>Conjoint analysis</topic><topic>Decision Making</topic><topic>Decomposition</topic><topic>Delivery of Health Care - methods</topic><topic>Evaluation</topic><topic>Health Administration</topic><topic>Health Economics</topic><topic>Health technology assessment</topic><topic>Humans</topic><topic>Medical care</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Methods</topic><topic>Netherlands</topic><topic>Patient Preference</topic><topic>Patients</topic><topic>Pharmacoeconomics and Health Outcomes</topic><topic>Preferences</topic><topic>Public Health</topic><topic>Quality</topic><topic>Quality of Life Research</topic><topic>Rating scales</topic><topic>Research Design</topic><topic>Researchers</topic><topic>Sample Size</topic><topic>Systematic Review</topic><topic>Trends</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cheung, Kei Long</creatorcontrib><creatorcontrib>Wijnen, Ben F. M.</creatorcontrib><creatorcontrib>Hollin, Ilene L.</creatorcontrib><creatorcontrib>Janssen, Ellen M.</creatorcontrib><creatorcontrib>Bridges, John F.</creatorcontrib><creatorcontrib>Evers, Silvia M. A. A.</creatorcontrib><creatorcontrib>Hiligsmann, Mickael</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Global News & ABI/Inform Professional</collection><collection>Trade PRO</collection><collection>ProQuest Central (Corporate)</collection><collection>Docstoc</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Healthcare Administration Database (Alumni)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>Public Health Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>Health Research Premium Collection</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Professional Standard</collection><collection>ABI/INFORM Global</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Healthcare Administration Database</collection><collection>Medical Database</collection><collection>ProQuest Psychology</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>PharmacoEconomics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cheung, Kei Long</au><au>Wijnen, Ben F. M.</au><au>Hollin, Ilene L.</au><au>Janssen, Ellen M.</au><au>Bridges, John F.</au><au>Evers, Silvia M. A. A.</au><au>Hiligsmann, Mickael</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Using Best–Worst Scaling to Investigate Preferences in Health Care</atitle><jtitle>PharmacoEconomics</jtitle><stitle>PharmacoEconomics</stitle><addtitle>Pharmacoeconomics</addtitle><date>2016-12-01</date><risdate>2016</risdate><volume>34</volume><issue>12</issue><spage>1195</spage><epage>1209</epage><pages>1195-1209</pages><issn>1170-7690</issn><eissn>1179-2027</eissn><abstract>Introduction
Best–worst scaling (BWS) is becoming increasingly popular to elicit preferences in health care. However, little is known about current practice and trends in the use of BWS in health care. This study aimed to identify, review and critically appraise BWS in health care, and to identify trends over time in key aspects of BWS.
Methods
A systematic review was conducted, using Medline (via Pubmed) and EMBASE to identify all English-language BWS studies published up until April 2016. Using a predefined extraction form, two reviewers independently selected articles and critically appraised the study quality, using the Purpose, Respondents, Explanation, Findings, Significance (PREFS) checklist. Trends over time periods (≤2010, 2011, 2012, 2013, 2014 and 2015) were assessed further.
Results
A total of 62 BWS studies were identified, of which 26 were BWS object case studies, 29 were BWS profile case studies and seven were BWS multi-profile case studies. About two thirds of the studies were performed in the last 2 years. Decreasing sample sizes and decreasing numbers of factors in BWS object case studies, as well as use of less complicated analytical methods, were observed in recent studies. The quality of the BWS studies was generally acceptable according to the PREFS checklist, except that most studies did not indicate whether the responders were similar to the non-responders.
Conclusion
Use of BWS object case and BWS profile case has drastically increased in health care, especially in the last 2 years. In contrast with previous discrete-choice experiment reviews, there is increasing use of less sophisticated analytical methods.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>27402349</pmid><doi>10.1007/s40273-016-0429-5</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0001-7648-4556</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Case studies Choice Behavior Conjoint analysis Decision Making Decomposition Delivery of Health Care - methods Evaluation Health Administration Health Economics Health technology assessment Humans Medical care Medicine Medicine & Public Health Methods Netherlands Patient Preference Patients Pharmacoeconomics and Health Outcomes Preferences Public Health Quality Quality of Life Research Rating scales Research Design Researchers Sample Size Systematic Review Trends |
title | Using Best–Worst Scaling to Investigate Preferences in Health Care |
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