The elicitation of patient and physician preferences for calculating consumer-based composite measures on hospital report cards: results of two discrete choice experiments

Purpose The calculation of aggregated composite measures is a widely used strategy to reduce the amount of data on hospital report cards. Therefore, this study aims to elicit and compare preferences of both patients as well as referring physicians regarding publicly available hospital quality inform...
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Autor*in:	Emmert, Martin [verfasserIn] Rohrbacher, Stefan [verfasserIn] Meier, Florian [verfasserIn] Heppe, Laura [verfasserIn] Drach, Cordula [verfasserIn] Schindler, Anja [verfasserIn] Sander, Uwe [verfasserIn] Patzelt, Christiane [verfasserIn] Frömke, Cornelia [verfasserIn] Schöffski, Oliver [verfasserIn] Lauerer, Michael [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Public reporting Hospital choice Discrete choice experiment Composite measures Hospital report cards

Anmerkung:	© The Author(s) 2023

Übergeordnetes Werk:	Enthalten in: The European journal of health economics - Springer Berlin Heidelberg, 2001, 25(2023), 6 vom: 15. Dez., Seite 1071-1085
Übergeordnetes Werk:	volume:25 ; year:2023 ; number:6 ; day:15 ; month:12 ; pages:1071-1085

Links:	Volltext

DOI / URN:	10.1007/s10198-023-01650-2

Katalog-ID:	SPR056751184

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100	1		\|a Emmert, Martin \|e verfasserin \|0 (orcid)0000-0002-0154-6641 \|4 aut
245	1	0	\|a The elicitation of patient and physician preferences for calculating consumer-based composite measures on hospital report cards: results of two discrete choice experiments
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520			\|a Purpose The calculation of aggregated composite measures is a widely used strategy to reduce the amount of data on hospital report cards. Therefore, this study aims to elicit and compare preferences of both patients as well as referring physicians regarding publicly available hospital quality information Methods Based on systematic literature reviews as well as qualitative analysis, two discrete choice experiments (DCEs) were applied to elicit patients’ and referring physicians’ preferences. The DCEs were conducted using a fractional factorial design. Statistical data analysis was performed using multinomial logit models Results Apart from five identical attributes, one specific attribute was identified for each study group, respectively. Overall, 322 patients (mean age 68.99) and 187 referring physicians (mean age 53.60) were included. Our models displayed significant coefficients for all attributes (p < 0.001 each). Among patients, “Postoperative complication rate” (20.6%; level range of 1.164) was rated highest, followed by “Mobility at hospital discharge” (19.9%; level range of 1.127), and ‘‘The number of cases treated” (18.5%; level range of 1.045). In contrast, referring physicians valued most the ‘‘One-year revision surgery rate’’ (30.4%; level range of 1.989), followed by “The number of cases treated” (21.0%; level range of 1.372), and “Postoperative complication rate” (17.2%; level range of 1.123) Conclusion We determined considerable differences between both study groups when calculating the relative value of publicly available hospital quality information. This may have an impact when calculating aggregated composite measures based on consumer-based weighting.
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700	1		\|a Sander, Uwe \|e verfasserin \|4 aut
700	1		\|a Patzelt, Christiane \|e verfasserin \|4 aut
700	1		\|a Frömke, Cornelia \|e verfasserin \|4 aut
700	1		\|a Schöffski, Oliver \|e verfasserin \|4 aut
700	1		\|a Lauerer, Michael \|e verfasserin \|4 aut
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author_variant	m e me s r sr f m fm l h lh c d cd a s as u s us c p cp c f cf o s os m l ml
matchkey_str	article:16187601:2023----::heiiainfainadhscapeeecsocluaigosmraecmoieesrsnoptleotad
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publishDate	2023
allfields	10.1007/s10198-023-01650-2 doi (DE-627)SPR056751184 (SPR)s10198-023-01650-2-e DE-627 ger DE-627 rakwb eng 610 VZ 44.05 bkl 44.10 bkl Emmert, Martin verfasserin (orcid)0000-0002-0154-6641 aut The elicitation of patient and physician preferences for calculating consumer-based composite measures on hospital report cards: results of two discrete choice experiments 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Purpose The calculation of aggregated composite measures is a widely used strategy to reduce the amount of data on hospital report cards. Therefore, this study aims to elicit and compare preferences of both patients as well as referring physicians regarding publicly available hospital quality information Methods Based on systematic literature reviews as well as qualitative analysis, two discrete choice experiments (DCEs) were applied to elicit patients’ and referring physicians’ preferences. The DCEs were conducted using a fractional factorial design. Statistical data analysis was performed using multinomial logit models Results Apart from five identical attributes, one specific attribute was identified for each study group, respectively. Overall, 322 patients (mean age 68.99) and 187 referring physicians (mean age 53.60) were included. Our models displayed significant coefficients for all attributes (p < 0.001 each). Among patients, “Postoperative complication rate” (20.6%; level range of 1.164) was rated highest, followed by “Mobility at hospital discharge” (19.9%; level range of 1.127), and ‘‘The number of cases treated” (18.5%; level range of 1.045). In contrast, referring physicians valued most the ‘‘One-year revision surgery rate’’ (30.4%; level range of 1.989), followed by “The number of cases treated” (21.0%; level range of 1.372), and “Postoperative complication rate” (17.2%; level range of 1.123) Conclusion We determined considerable differences between both study groups when calculating the relative value of publicly available hospital quality information. This may have an impact when calculating aggregated composite measures based on consumer-based weighting. Public reporting (dpeaa)DE-He213 Hospital choice (dpeaa)DE-He213 Discrete choice experiment (dpeaa)DE-He213 Composite measures (dpeaa)DE-He213 Hospital report cards (dpeaa)DE-He213 Rohrbacher, Stefan verfasserin aut Meier, Florian verfasserin aut Heppe, Laura verfasserin aut Drach, Cordula verfasserin aut Schindler, Anja verfasserin aut Sander, Uwe verfasserin aut Patzelt, Christiane verfasserin aut Frömke, Cornelia verfasserin aut Schöffski, Oliver verfasserin aut Lauerer, Michael verfasserin aut Enthalten in The European journal of health economics Springer Berlin Heidelberg, 2001 25(2023), 6 vom: 15. Dez., Seite 1071-1085 (DE-627)320494462 (DE-600)2011428-X 1618-7601 nnns volume:25 year:2023 number:6 day:15 month:12 pages:1071-1085 https://dx.doi.org/10.1007/s10198-023-01650-2 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2110 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2129 GBV_ILN_2144 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2941 GBV_ILN_2949 GBV_ILN_2950 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4392 GBV_ILN_4393 GBV_ILN_4700 44.05 VZ 44.10 VZ AR 25 2023 6 15 12 1071-1085
spelling	10.1007/s10198-023-01650-2 doi (DE-627)SPR056751184 (SPR)s10198-023-01650-2-e DE-627 ger DE-627 rakwb eng 610 VZ 44.05 bkl 44.10 bkl Emmert, Martin verfasserin (orcid)0000-0002-0154-6641 aut The elicitation of patient and physician preferences for calculating consumer-based composite measures on hospital report cards: results of two discrete choice experiments 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Purpose The calculation of aggregated composite measures is a widely used strategy to reduce the amount of data on hospital report cards. Therefore, this study aims to elicit and compare preferences of both patients as well as referring physicians regarding publicly available hospital quality information Methods Based on systematic literature reviews as well as qualitative analysis, two discrete choice experiments (DCEs) were applied to elicit patients’ and referring physicians’ preferences. The DCEs were conducted using a fractional factorial design. Statistical data analysis was performed using multinomial logit models Results Apart from five identical attributes, one specific attribute was identified for each study group, respectively. Overall, 322 patients (mean age 68.99) and 187 referring physicians (mean age 53.60) were included. Our models displayed significant coefficients for all attributes (p < 0.001 each). Among patients, “Postoperative complication rate” (20.6%; level range of 1.164) was rated highest, followed by “Mobility at hospital discharge” (19.9%; level range of 1.127), and ‘‘The number of cases treated” (18.5%; level range of 1.045). In contrast, referring physicians valued most the ‘‘One-year revision surgery rate’’ (30.4%; level range of 1.989), followed by “The number of cases treated” (21.0%; level range of 1.372), and “Postoperative complication rate” (17.2%; level range of 1.123) Conclusion We determined considerable differences between both study groups when calculating the relative value of publicly available hospital quality information. This may have an impact when calculating aggregated composite measures based on consumer-based weighting. Public reporting (dpeaa)DE-He213 Hospital choice (dpeaa)DE-He213 Discrete choice experiment (dpeaa)DE-He213 Composite measures (dpeaa)DE-He213 Hospital report cards (dpeaa)DE-He213 Rohrbacher, Stefan verfasserin aut Meier, Florian verfasserin aut Heppe, Laura verfasserin aut Drach, Cordula verfasserin aut Schindler, Anja verfasserin aut Sander, Uwe verfasserin aut Patzelt, Christiane verfasserin aut Frömke, Cornelia verfasserin aut Schöffski, Oliver verfasserin aut Lauerer, Michael verfasserin aut Enthalten in The European journal of health economics Springer Berlin Heidelberg, 2001 25(2023), 6 vom: 15. Dez., Seite 1071-1085 (DE-627)320494462 (DE-600)2011428-X 1618-7601 nnns volume:25 year:2023 number:6 day:15 month:12 pages:1071-1085 https://dx.doi.org/10.1007/s10198-023-01650-2 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2110 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2129 GBV_ILN_2144 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2941 GBV_ILN_2949 GBV_ILN_2950 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4392 GBV_ILN_4393 GBV_ILN_4700 44.05 VZ 44.10 VZ AR 25 2023 6 15 12 1071-1085
allfields_unstemmed	10.1007/s10198-023-01650-2 doi (DE-627)SPR056751184 (SPR)s10198-023-01650-2-e DE-627 ger DE-627 rakwb eng 610 VZ 44.05 bkl 44.10 bkl Emmert, Martin verfasserin (orcid)0000-0002-0154-6641 aut The elicitation of patient and physician preferences for calculating consumer-based composite measures on hospital report cards: results of two discrete choice experiments 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Purpose The calculation of aggregated composite measures is a widely used strategy to reduce the amount of data on hospital report cards. Therefore, this study aims to elicit and compare preferences of both patients as well as referring physicians regarding publicly available hospital quality information Methods Based on systematic literature reviews as well as qualitative analysis, two discrete choice experiments (DCEs) were applied to elicit patients’ and referring physicians’ preferences. The DCEs were conducted using a fractional factorial design. Statistical data analysis was performed using multinomial logit models Results Apart from five identical attributes, one specific attribute was identified for each study group, respectively. Overall, 322 patients (mean age 68.99) and 187 referring physicians (mean age 53.60) were included. Our models displayed significant coefficients for all attributes (p < 0.001 each). Among patients, “Postoperative complication rate” (20.6%; level range of 1.164) was rated highest, followed by “Mobility at hospital discharge” (19.9%; level range of 1.127), and ‘‘The number of cases treated” (18.5%; level range of 1.045). In contrast, referring physicians valued most the ‘‘One-year revision surgery rate’’ (30.4%; level range of 1.989), followed by “The number of cases treated” (21.0%; level range of 1.372), and “Postoperative complication rate” (17.2%; level range of 1.123) Conclusion We determined considerable differences between both study groups when calculating the relative value of publicly available hospital quality information. This may have an impact when calculating aggregated composite measures based on consumer-based weighting. Public reporting (dpeaa)DE-He213 Hospital choice (dpeaa)DE-He213 Discrete choice experiment (dpeaa)DE-He213 Composite measures (dpeaa)DE-He213 Hospital report cards (dpeaa)DE-He213 Rohrbacher, Stefan verfasserin aut Meier, Florian verfasserin aut Heppe, Laura verfasserin aut Drach, Cordula verfasserin aut Schindler, Anja verfasserin aut Sander, Uwe verfasserin aut Patzelt, Christiane verfasserin aut Frömke, Cornelia verfasserin aut Schöffski, Oliver verfasserin aut Lauerer, Michael verfasserin aut Enthalten in The European journal of health economics Springer Berlin Heidelberg, 2001 25(2023), 6 vom: 15. Dez., Seite 1071-1085 (DE-627)320494462 (DE-600)2011428-X 1618-7601 nnns volume:25 year:2023 number:6 day:15 month:12 pages:1071-1085 https://dx.doi.org/10.1007/s10198-023-01650-2 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2110 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2129 GBV_ILN_2144 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2941 GBV_ILN_2949 GBV_ILN_2950 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4392 GBV_ILN_4393 GBV_ILN_4700 44.05 VZ 44.10 VZ AR 25 2023 6 15 12 1071-1085
allfieldsGer	10.1007/s10198-023-01650-2 doi (DE-627)SPR056751184 (SPR)s10198-023-01650-2-e DE-627 ger DE-627 rakwb eng 610 VZ 44.05 bkl 44.10 bkl Emmert, Martin verfasserin (orcid)0000-0002-0154-6641 aut The elicitation of patient and physician preferences for calculating consumer-based composite measures on hospital report cards: results of two discrete choice experiments 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Purpose The calculation of aggregated composite measures is a widely used strategy to reduce the amount of data on hospital report cards. Therefore, this study aims to elicit and compare preferences of both patients as well as referring physicians regarding publicly available hospital quality information Methods Based on systematic literature reviews as well as qualitative analysis, two discrete choice experiments (DCEs) were applied to elicit patients’ and referring physicians’ preferences. The DCEs were conducted using a fractional factorial design. Statistical data analysis was performed using multinomial logit models Results Apart from five identical attributes, one specific attribute was identified for each study group, respectively. Overall, 322 patients (mean age 68.99) and 187 referring physicians (mean age 53.60) were included. Our models displayed significant coefficients for all attributes (p < 0.001 each). Among patients, “Postoperative complication rate” (20.6%; level range of 1.164) was rated highest, followed by “Mobility at hospital discharge” (19.9%; level range of 1.127), and ‘‘The number of cases treated” (18.5%; level range of 1.045). In contrast, referring physicians valued most the ‘‘One-year revision surgery rate’’ (30.4%; level range of 1.989), followed by “The number of cases treated” (21.0%; level range of 1.372), and “Postoperative complication rate” (17.2%; level range of 1.123) Conclusion We determined considerable differences between both study groups when calculating the relative value of publicly available hospital quality information. This may have an impact when calculating aggregated composite measures based on consumer-based weighting. Public reporting (dpeaa)DE-He213 Hospital choice (dpeaa)DE-He213 Discrete choice experiment (dpeaa)DE-He213 Composite measures (dpeaa)DE-He213 Hospital report cards (dpeaa)DE-He213 Rohrbacher, Stefan verfasserin aut Meier, Florian verfasserin aut Heppe, Laura verfasserin aut Drach, Cordula verfasserin aut Schindler, Anja verfasserin aut Sander, Uwe verfasserin aut Patzelt, Christiane verfasserin aut Frömke, Cornelia verfasserin aut Schöffski, Oliver verfasserin aut Lauerer, Michael verfasserin aut Enthalten in The European journal of health economics Springer Berlin Heidelberg, 2001 25(2023), 6 vom: 15. Dez., Seite 1071-1085 (DE-627)320494462 (DE-600)2011428-X 1618-7601 nnns volume:25 year:2023 number:6 day:15 month:12 pages:1071-1085 https://dx.doi.org/10.1007/s10198-023-01650-2 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2110 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2129 GBV_ILN_2144 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2941 GBV_ILN_2949 GBV_ILN_2950 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4392 GBV_ILN_4393 GBV_ILN_4700 44.05 VZ 44.10 VZ AR 25 2023 6 15 12 1071-1085
allfieldsSound	10.1007/s10198-023-01650-2 doi (DE-627)SPR056751184 (SPR)s10198-023-01650-2-e DE-627 ger DE-627 rakwb eng 610 VZ 44.05 bkl 44.10 bkl Emmert, Martin verfasserin (orcid)0000-0002-0154-6641 aut The elicitation of patient and physician preferences for calculating consumer-based composite measures on hospital report cards: results of two discrete choice experiments 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Purpose The calculation of aggregated composite measures is a widely used strategy to reduce the amount of data on hospital report cards. Therefore, this study aims to elicit and compare preferences of both patients as well as referring physicians regarding publicly available hospital quality information Methods Based on systematic literature reviews as well as qualitative analysis, two discrete choice experiments (DCEs) were applied to elicit patients’ and referring physicians’ preferences. The DCEs were conducted using a fractional factorial design. Statistical data analysis was performed using multinomial logit models Results Apart from five identical attributes, one specific attribute was identified for each study group, respectively. Overall, 322 patients (mean age 68.99) and 187 referring physicians (mean age 53.60) were included. Our models displayed significant coefficients for all attributes (p < 0.001 each). Among patients, “Postoperative complication rate” (20.6%; level range of 1.164) was rated highest, followed by “Mobility at hospital discharge” (19.9%; level range of 1.127), and ‘‘The number of cases treated” (18.5%; level range of 1.045). In contrast, referring physicians valued most the ‘‘One-year revision surgery rate’’ (30.4%; level range of 1.989), followed by “The number of cases treated” (21.0%; level range of 1.372), and “Postoperative complication rate” (17.2%; level range of 1.123) Conclusion We determined considerable differences between both study groups when calculating the relative value of publicly available hospital quality information. This may have an impact when calculating aggregated composite measures based on consumer-based weighting. Public reporting (dpeaa)DE-He213 Hospital choice (dpeaa)DE-He213 Discrete choice experiment (dpeaa)DE-He213 Composite measures (dpeaa)DE-He213 Hospital report cards (dpeaa)DE-He213 Rohrbacher, Stefan verfasserin aut Meier, Florian verfasserin aut Heppe, Laura verfasserin aut Drach, Cordula verfasserin aut Schindler, Anja verfasserin aut Sander, Uwe verfasserin aut Patzelt, Christiane verfasserin aut Frömke, Cornelia verfasserin aut Schöffski, Oliver verfasserin aut Lauerer, Michael verfasserin aut Enthalten in The European journal of health economics Springer Berlin Heidelberg, 2001 25(2023), 6 vom: 15. Dez., Seite 1071-1085 (DE-627)320494462 (DE-600)2011428-X 1618-7601 nnns volume:25 year:2023 number:6 day:15 month:12 pages:1071-1085 https://dx.doi.org/10.1007/s10198-023-01650-2 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2110 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2129 GBV_ILN_2144 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2941 GBV_ILN_2949 GBV_ILN_2950 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4392 GBV_ILN_4393 GBV_ILN_4700 44.05 VZ 44.10 VZ AR 25 2023 6 15 12 1071-1085
language	English
source	Enthalten in The European journal of health economics 25(2023), 6 vom: 15. Dez., Seite 1071-1085 volume:25 year:2023 number:6 day:15 month:12 pages:1071-1085
sourceStr	Enthalten in The European journal of health economics 25(2023), 6 vom: 15. Dez., Seite 1071-1085 volume:25 year:2023 number:6 day:15 month:12 pages:1071-1085
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Public reporting Hospital choice Discrete choice experiment Composite measures Hospital report cards
dewey-raw	610
isfreeaccess_bool	true
container_title	The European journal of health economics
authorswithroles_txt_mv	Emmert, Martin @@aut@@ Rohrbacher, Stefan @@aut@@ Meier, Florian @@aut@@ Heppe, Laura @@aut@@ Drach, Cordula @@aut@@ Schindler, Anja @@aut@@ Sander, Uwe @@aut@@ Patzelt, Christiane @@aut@@ Frömke, Cornelia @@aut@@ Schöffski, Oliver @@aut@@ Lauerer, Michael @@aut@@
publishDateDaySort_date	2023-12-15T00:00:00Z
hierarchy_top_id	320494462
dewey-sort	3610
id	SPR056751184
language_de	englisch
fullrecord	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">SPR056751184</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240728081311.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240728s2023 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10198-023-01650-2</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR056751184</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s10198-023-01650-2-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.05</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.10</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Emmert, Martin</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0002-0154-6641</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">The elicitation of patient and physician preferences for calculating consumer-based composite measures on hospital report cards: results of two discrete choice experiments</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s) 2023</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Purpose The calculation of aggregated composite measures is a widely used strategy to reduce the amount of data on hospital report cards. Therefore, this study aims to elicit and compare preferences of both patients as well as referring physicians regarding publicly available hospital quality information Methods Based on systematic literature reviews as well as qualitative analysis, two discrete choice experiments (DCEs) were applied to elicit patients’ and referring physicians’ preferences. The DCEs were conducted using a fractional factorial design. Statistical data analysis was performed using multinomial logit models Results Apart from five identical attributes, one specific attribute was identified for each study group, respectively. Overall, 322 patients (mean age 68.99) and 187 referring physicians (mean age 53.60) were included. Our models displayed significant coefficients for all attributes (p < 0.001 each). Among patients, “Postoperative complication rate” (20.6%; level range of 1.164) was rated highest, followed by “Mobility at hospital discharge” (19.9%; level range of 1.127), and ‘‘The number of cases treated” (18.5%; level range of 1.045). In contrast, referring physicians valued most the ‘‘One-year revision surgery rate’’ (30.4%; level range of 1.989), followed by “The number of cases treated” (21.0%; level range of 1.372), and “Postoperative complication rate” (17.2%; level range of 1.123) Conclusion We determined considerable differences between both study groups when calculating the relative value of publicly available hospital quality information. 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author	Emmert, Martin
spellingShingle	Emmert, Martin ddc 610 bkl 44.05 bkl 44.10 misc Public reporting misc Hospital choice misc Discrete choice experiment misc Composite measures misc Hospital report cards The elicitation of patient and physician preferences for calculating consumer-based composite measures on hospital report cards: results of two discrete choice experiments
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topic_title	610 VZ 44.05 bkl 44.10 bkl The elicitation of patient and physician preferences for calculating consumer-based composite measures on hospital report cards: results of two discrete choice experiments Public reporting (dpeaa)DE-He213 Hospital choice (dpeaa)DE-He213 Discrete choice experiment (dpeaa)DE-He213 Composite measures (dpeaa)DE-He213 Hospital report cards (dpeaa)DE-He213
topic	ddc 610 bkl 44.05 bkl 44.10 misc Public reporting misc Hospital choice misc Discrete choice experiment misc Composite measures misc Hospital report cards
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title	The elicitation of patient and physician preferences for calculating consumer-based composite measures on hospital report cards: results of two discrete choice experiments
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title_full	The elicitation of patient and physician preferences for calculating consumer-based composite measures on hospital report cards: results of two discrete choice experiments
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author_browse	Emmert, Martin Rohrbacher, Stefan Meier, Florian Heppe, Laura Drach, Cordula Schindler, Anja Sander, Uwe Patzelt, Christiane Frömke, Cornelia Schöffski, Oliver Lauerer, Michael
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title_sort	the elicitation of patient and physician preferences for calculating consumer-based composite measures on hospital report cards: results of two discrete choice experiments
title_auth	The elicitation of patient and physician preferences for calculating consumer-based composite measures on hospital report cards: results of two discrete choice experiments
abstract	Purpose The calculation of aggregated composite measures is a widely used strategy to reduce the amount of data on hospital report cards. Therefore, this study aims to elicit and compare preferences of both patients as well as referring physicians regarding publicly available hospital quality information Methods Based on systematic literature reviews as well as qualitative analysis, two discrete choice experiments (DCEs) were applied to elicit patients’ and referring physicians’ preferences. The DCEs were conducted using a fractional factorial design. Statistical data analysis was performed using multinomial logit models Results Apart from five identical attributes, one specific attribute was identified for each study group, respectively. Overall, 322 patients (mean age 68.99) and 187 referring physicians (mean age 53.60) were included. Our models displayed significant coefficients for all attributes (p < 0.001 each). Among patients, “Postoperative complication rate” (20.6%; level range of 1.164) was rated highest, followed by “Mobility at hospital discharge” (19.9%; level range of 1.127), and ‘‘The number of cases treated” (18.5%; level range of 1.045). In contrast, referring physicians valued most the ‘‘One-year revision surgery rate’’ (30.4%; level range of 1.989), followed by “The number of cases treated” (21.0%; level range of 1.372), and “Postoperative complication rate” (17.2%; level range of 1.123) Conclusion We determined considerable differences between both study groups when calculating the relative value of publicly available hospital quality information. This may have an impact when calculating aggregated composite measures based on consumer-based weighting. © The Author(s) 2023
abstractGer	Purpose The calculation of aggregated composite measures is a widely used strategy to reduce the amount of data on hospital report cards. Therefore, this study aims to elicit and compare preferences of both patients as well as referring physicians regarding publicly available hospital quality information Methods Based on systematic literature reviews as well as qualitative analysis, two discrete choice experiments (DCEs) were applied to elicit patients’ and referring physicians’ preferences. The DCEs were conducted using a fractional factorial design. Statistical data analysis was performed using multinomial logit models Results Apart from five identical attributes, one specific attribute was identified for each study group, respectively. Overall, 322 patients (mean age 68.99) and 187 referring physicians (mean age 53.60) were included. Our models displayed significant coefficients for all attributes (p < 0.001 each). Among patients, “Postoperative complication rate” (20.6%; level range of 1.164) was rated highest, followed by “Mobility at hospital discharge” (19.9%; level range of 1.127), and ‘‘The number of cases treated” (18.5%; level range of 1.045). In contrast, referring physicians valued most the ‘‘One-year revision surgery rate’’ (30.4%; level range of 1.989), followed by “The number of cases treated” (21.0%; level range of 1.372), and “Postoperative complication rate” (17.2%; level range of 1.123) Conclusion We determined considerable differences between both study groups when calculating the relative value of publicly available hospital quality information. This may have an impact when calculating aggregated composite measures based on consumer-based weighting. © The Author(s) 2023
abstract_unstemmed	Purpose The calculation of aggregated composite measures is a widely used strategy to reduce the amount of data on hospital report cards. Therefore, this study aims to elicit and compare preferences of both patients as well as referring physicians regarding publicly available hospital quality information Methods Based on systematic literature reviews as well as qualitative analysis, two discrete choice experiments (DCEs) were applied to elicit patients’ and referring physicians’ preferences. The DCEs were conducted using a fractional factorial design. Statistical data analysis was performed using multinomial logit models Results Apart from five identical attributes, one specific attribute was identified for each study group, respectively. Overall, 322 patients (mean age 68.99) and 187 referring physicians (mean age 53.60) were included. Our models displayed significant coefficients for all attributes (p < 0.001 each). Among patients, “Postoperative complication rate” (20.6%; level range of 1.164) was rated highest, followed by “Mobility at hospital discharge” (19.9%; level range of 1.127), and ‘‘The number of cases treated” (18.5%; level range of 1.045). In contrast, referring physicians valued most the ‘‘One-year revision surgery rate’’ (30.4%; level range of 1.989), followed by “The number of cases treated” (21.0%; level range of 1.372), and “Postoperative complication rate” (17.2%; level range of 1.123) Conclusion We determined considerable differences between both study groups when calculating the relative value of publicly available hospital quality information. This may have an impact when calculating aggregated composite measures based on consumer-based weighting. © The Author(s) 2023
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container_issue	6
title_short	The elicitation of patient and physician preferences for calculating consumer-based composite measures on hospital report cards: results of two discrete choice experiments
url	https://dx.doi.org/10.1007/s10198-023-01650-2
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author2	Rohrbacher, Stefan Meier, Florian Heppe, Laura Drach, Cordula Schindler, Anja Sander, Uwe Patzelt, Christiane Frömke, Cornelia Schöffski, Oliver Lauerer, Michael
author2Str	Rohrbacher, Stefan Meier, Florian Heppe, Laura Drach, Cordula Schindler, Anja Sander, Uwe Patzelt, Christiane Frömke, Cornelia Schöffski, Oliver Lauerer, Michael
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doi_str	10.1007/s10198-023-01650-2
up_date	2024-07-28T06:15:57.141Z
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Therefore, this study aims to elicit and compare preferences of both patients as well as referring physicians regarding publicly available hospital quality information Methods Based on systematic literature reviews as well as qualitative analysis, two discrete choice experiments (DCEs) were applied to elicit patients’ and referring physicians’ preferences. The DCEs were conducted using a fractional factorial design. Statistical data analysis was performed using multinomial logit models Results Apart from five identical attributes, one specific attribute was identified for each study group, respectively. Overall, 322 patients (mean age 68.99) and 187 referring physicians (mean age 53.60) were included. Our models displayed significant coefficients for all attributes (p < 0.001 each). 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The elicitation of patient and physician preferences for calculating consumer-based composite measures on hospital report cards: results of two discrete choice experiments

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