Discrete choice experiments for complex health-care decisions: does hierarchical information integration offer a solution?
This paper describes an application of hierarchical information integration (HII) discrete choice experiments. We assessed theoretical and construct validity, as well as internal consistency, to investigate whether HII can be used to investigate complex multi‐faceted health‐care decisions (objective...
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| Published in | Health economics Vol. 18; no. 8; pp. 903 - 920 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Chichester, UK
John Wiley & Sons, Ltd
01.08.2009
Wiley Periodicals Inc |
| Series | Health Economics |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1057-9230 1099-1050 1099-1050 |
| DOI | 10.1002/hec.1411 |
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| Abstract | This paper describes an application of hierarchical information integration (HII) discrete choice experiments. We assessed theoretical and construct validity, as well as internal consistency, to investigate whether HII can be used to investigate complex multi‐faceted health‐care decisions (objective 1). In addition, we incorporated recent advances in mixed logit modelling (objective 2). Finally, we determined the response rate and predictive ability to study the feasibility of HII to support health‐care management (objective 3). The clinical subject was the implementation of the guideline for breast cancer surgery in day care, which is a complex process that involves changes at the organizational and management levels, as well as the level of health‐care professionals and that of patients.
We found good theoretical and construct validity and satisfactory internal consistency. The proposed mixed logit model, which included repeated measures corrections and subexperiment error scale variations, also performed well. We found a poor response, but the model had satisfactory predictive ability. Therefore, we conclude that HII can be used successfully to study complex multi‐faceted health‐care decisions (objectives 1 and 2), but that the feasibility of HII to support health‐care management, in particular in challenging implementation projects, seems less favourable (objective 3). Copyright © 2008 John Wiley & Sons, Ltd. |
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| AbstractList | This paper describes an application of hierarchical information integration (HII) discrete choice experiments. We assessed theoretical and construct validity, as well as internal consistency, to investigate whether HII can be used to investigate complex multi‐faceted health‐care decisions (objective 1). In addition, we incorporated recent advances in mixed logit modelling (objective 2). Finally, we determined the response rate and predictive ability to study the feasibility of HII to support health‐care management (objective 3). The clinical subject was the implementation of the guideline for breast cancer surgery in day care, which is a complex process that involves changes at the organizational and management levels, as well as the level of health‐care professionals and that of patients.
We found good theoretical and construct validity and satisfactory internal consistency. The proposed mixed logit model, which included repeated measures corrections and subexperiment error scale variations, also performed well. We found a poor response, but the model had satisfactory predictive ability. Therefore, we conclude that HII can be used successfully to study complex multi‐faceted health‐care decisions (objectives 1 and 2), but that the feasibility of HII to support health‐care management, in particular in challenging implementation projects, seems less favourable (objective 3). Copyright © 2008 John Wiley & Sons, Ltd. This paper describes an application of hierarchical information integration (HII) discrete choice experiments. We assessed theoretical and construct validity, as well as internal consistency, to investigate whether HII can be used to investigate complex multi-faceted health-care decisions (objective 1). In addition, we incorporated recent advances in mixed logit modelling (objective 2). Finally, we determined the response rate and predictive ability to study the feasibility of HII to support health-care management (objective 3). The clinical subject was the implementation of the guideline for breast cancer surgery in day care, which is a complex process that involves changes at the organizational and management levels, as well as the level of health-care professionals and that of patients.We found good theoretical and construct validity and satisfactory internal consistency. The proposed mixed logit model, which included repeated measures corrections and subexperiment error scale variations, also performed well. We found a poor response, but the model had satisfactory predictive ability. Therefore, we conclude that HII can be used successfully to study complex multi-faceted health-care decisions (objectives 1 and 2), but that the feasibility of HII to support health-care management, in particular in challenging implementation projects, seems less favourable (objective 3).This paper describes an application of hierarchical information integration (HII) discrete choice experiments. We assessed theoretical and construct validity, as well as internal consistency, to investigate whether HII can be used to investigate complex multi-faceted health-care decisions (objective 1). In addition, we incorporated recent advances in mixed logit modelling (objective 2). Finally, we determined the response rate and predictive ability to study the feasibility of HII to support health-care management (objective 3). The clinical subject was the implementation of the guideline for breast cancer surgery in day care, which is a complex process that involves changes at the organizational and management levels, as well as the level of health-care professionals and that of patients.We found good theoretical and construct validity and satisfactory internal consistency. The proposed mixed logit model, which included repeated measures corrections and subexperiment error scale variations, also performed well. We found a poor response, but the model had satisfactory predictive ability. Therefore, we conclude that HII can be used successfully to study complex multi-faceted health-care decisions (objectives 1 and 2), but that the feasibility of HII to support health-care management, in particular in challenging implementation projects, seems less favourable (objective 3). This paper describes an application of hierarchical information integration (HII) discrete choice experiments. We assessed theoretical and construct validity, as well as internal consistency, to investigate whether HII can be used to investigate complex multi-faceted health-care decisions (objective 1). In addition, we incorporated recent advances in mixed logit modelling (objective 2). Finally, we determined the response rate and predictive ability to study the feasibility of HII to support health-care management (objective 3). The clinical subject was the implementation of the guideline for breast cancer surgery in day care, which is a complex process that involves changes at the organizational and management levels, as well as the level of health-care professionals and that of patients.We found good theoretical and construct validity and satisfactory internal consistency. The proposed mixed logit model, which included repeated measures corrections and subexperiment error scale variations, also performed well. We found a poor response, but the model had satisfactory predictive ability. Therefore, we conclude that HII can be used successfully to study complex multi-faceted health-care decisions (objectives 1 and 2), but that the feasibility of HII to support health-care management, in particular in challenging implementation projects, seems less favourable (objective 3). This paper describes an application of hierarchical information integration (HII) discrete choice experiments. We assessed theoretical and construct validity, as well as internal consistency, to investigate whether HII can be used to investigate complex multi-faceted health-care decisions (objective 1). In addition, we incorporated recent advances in mixed logit modelling (objective 2). Finally, we determined the response rate and predictive ability to study the feasibility of HII to support health-care management (objective 3). The clinical subject was the implementation of the guideline for breast cancer surgery in day care, which is a complex process that involves changes at the organizational and management levels, as well as the level of health-care professionals and that of patients. We found good theoretical and construct validity and satisfactory internal consistency. The proposed mixed logit model, which included repeated measures corrections and subexperiment error scale variations, also performed well. We found a poor response, but the model had satisfactory predictive ability. Therefore, we conclude that HII can be used successfully to study complex multi-faceted health-care decisions (objectives 1 and 2), but that the feasibility of HII to support health-care management, in particular in challenging implementation projects, seems less favourable (objective 3). [PUBLICATION ABSTRACT] This paper describes an application of hierarchical information integration (HII) discrete choice experiments. We assessed theoretical and construct validity, as well as internal consistency, to investigate whether HII can be used to investigate complex multi-faceted health-care decisions (objective 1). In addition, we incorporated recent advances in mixed logit modelling (objective 2). Finally, we determined the response rate and predictive ability to study the feasibility of HII to support health-care management (objective 3). The clinical subject was the implementation of the guideline for breast cancer surgery in day care, which is a complex process that involves changes at the organizational and management levels, as well as the level of health-care professionals and that of patients. We found good theoretical and construct validity and satisfactory internal consistency. The proposed mixed logit model, which included repeated measures corrections and subexperiment error scale variations, also performed well. We found a poor response, but the model had satisfactory predictive ability. Therefore, we conclude that HII can be used successfully to study complex multi-faceted health-care decisions (objectives 1 and 2), but that the feasibility of HII to support health-care management, in particular in challenging implementation projects, seems less favourable (objective 3). [Copyright John Wiley and Sons, Ltd.] This paper describes an application of hierarchical information integration (HII) discrete choice experiments. We assessed theoretical and construct validity, as well as internal consistency, to investigate whether HII can be used to investigate complex multi-faceted health-care decisions (objective 1). In addition, we incorporated recent advances in mixed logit modelling (objective 2). Finally, we determined the response rate and predictive ability to study the feasibility of HII to support health-care management (objective 3). The clinical subject was the implementation of the guideline for breast cancer surgery in day care, which is a complex process that involves changes at the organizational and management levels, as well as the level of health-care professionals and that of patients. We found good theoretical and construct validity and satisfactory internal consistency. The proposed mixed logit model, which included repeated measures corrections and subexperiment error scale variations, also performed well. We found a poor response, but the model had satisfactory predictive ability. Therefore, we conclude that HII can be used successfully to study complex multi-faceted health-care decisions (objectives 1 and 2), but that the feasibility of HII to support health-care management, in particular in challenging implementation projects, seems less favourable (objective 3). Copyright © 2008 John Wiley & Sons, Ltd. |
| Author | van der Weijden, Trudy Dirksen, Carmen D. von Meyenfeldt, Maarten F. van Helvoort-Postulart, Debby Dellaert, Benedict G. C. |
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| Cites_doi | 10.1080/01490409209513167 10.1016/0749-5978(90)90007-V 10.1080/000368400322165 10.1016/S0959-8049(99)00340-8 10.1111/1475-6773.01115 10.1186/1472-6963-3-22 10.2307/3172883 10.1016/S0167-2681(01)00220-7 10.1068/a220291 10.1016/S0277-9536(98)00374-8 10.2307/2529310 10.1080/00036840500427858 10.1108/02652329810228217 10.1093/fampra/cmg509 10.1007/s10198-004-0241-6 10.2307/3151949 10.1111/1467-9485.00124 10.1108/02652320010349049 10.1002/9780470148563 10.1016/S0277-9536(99)00268-3 10.1177/002224299005400402 10.1136/qhc.0100055 10.1007/s10198-005-0304-3 10.1023/A:1012539415696 10.1177/00139169921971994 10.1093/intqhc/10.4.311 10.1111/j.1538-4632.1998.tb00399.x 10.1177/002224378302000403 10.1017/CBO9780511753831 10.1186/1746-1340-13-22 10.3310/hta5050 |
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| References | Oppewal H, Klabbers M. 2003. Compromising between information completeness and task simplicity: a comparison of self-explicated, hierarchical information integration, and full-profile conjoint methods. Advances in Consumer Research 30: 298-304. Grol R, Wensing M, Eccles M. 2005. Improving Patient Care: The Implementation of Change in Clinical Practice. Elsevier: Oxford. Sitzia J, Wood N. 1998. Response rate in patient satisfaction research: an analysis of 210 published studies. International Journal for Quality in Health Care 10: 311-317. Oppewal H, Timmermans H. 1999. Modeling consumer perception of public space in shopping centers. Environment and behaviour 31: 45-65. Ülengin B. 1998. Using hierarchical information integration to examine customer preferences in banking. International Journal of Bank Marketing 16: 202-210. Louviere JJ, Woodworth G. 1983. Design and analysis of simulated consumer choice or allocation experiments: an approach based on aggregate data. Journal of Marketing Research 20: 350-367. Swait J, Louviere J. 1993. The role of the scale parameter in the estimation and comparison of multinomial logit models. Journal of Marketing Research 30: 305-314. Street DJ, Burgess L. 2007. The Construction of Optimal Stated Choice Experiments: Theory and Methods. Wiley: Hoboken, NJ. Louviere JJ. 1984. Hierarchical information integration: a new method for the design and analysis of complex multiattribute judgment problems. Advances in Consumer Research 11: 148-155. Scott A, Vick S. 1999. Patients, doctors and contracts: an application of principal-agent theory to the doctor-patient relationship. Scottish Journal of Political Economy 46: 111-134. Ryan M, Bate A, Eastmond CJ, Ludbrook A. 2001a. Use of discrete choice experiments to elicit preferences. Quality in Health Care 10(Suppl): I55-I60. Louviere JJ, Timmermans HJP. 1992. Testing the external validity of hierarchical conjoint analysis models of recreational destination choice. Leisure Sciences 14: 179-194. Walker AE, Grimshaw J, Johnston M, Pitts N, Steen N, Eccles M. 2003. PRIME - PRocess modelling in ImpleMEntation research: selecting a theoretical basis for interventions to change clinical practice. BMC Health Services Research 3: 22. Oppewal H, Vriens M. 2000. Measuring perceived service quality using integrated conjoint experiments. International Journal of Bank Marketing 18: 154-169. Green PE, Srinivasan V. 1990. Conjoint analysis in marketing: new developments with implications for research and practice. Journal of Marketing 54: 3-19. Brown SL, Kittleson MJ. 2005. E-mail versus Web survey response rates among health education professionals. American Journal of Health Studies 20(1): 7-14. Louviere JJ, Hensher DA, Swait JD. 2000. Stated Choice Methods: Analysis and Application. Cambridge University Press: Cambridge. Louviere JJ, Timmermans HJP. 1990. Using hierarchical information integration to model consumer responses to possible planning actions: recreation destination choice illustration. Environment and Planning A 22: 291-308. Phillips KA, Maddala T, Johnson FR. 2002. Measuring preferences for health care interventions using conjoint analysis: an application to HIV testing. Health Services Research 37: 1681-1705. Bryan S, Dolan P. 2004. Discrete choice experiments in health economics: for better or for worse? European Journal of Health Economics 5: 199-202. Ryan M., Gerard K. 2003. Using discrete choice experiments to value health care programmes: current practice and future research reflections. Applied Health Economics and Health Policy 2: 55-64. Vyvere van de Y, Oppewal H, Timmermans H. 1998. The validity of hierarchical information integration choice experiments to model residential preference and choice. Geographical Analysis 30: 254-272. Oppewal H, Louviere JJ, Timmermans HJP. 1994. Modeling hierarchical conjoint processes with integrated choice experiments. Journal of Marketing Research 31: 92-105. San Miguel F, Ryan M, McIntosh E. 2000. Applying conjoint analysis in economic evaluations: an application to menorrhagia. Applied Economics 32: 823-833. Landis JR, Koch GG. 1977. The measurement of observer agreement for categorical data. Biometrics 33: 159-174. Ryan M, Scott DA, Reeves C, Bate A, Teijlingen van ER, Russell EM, Napper M, Robb CM. 2001b. Eliciting public preferences for health care: a systematic review of techniques. Health Technology Assessment 5(5). Braithwaite D, Emery J, de Lusignan S, Sutton S. 2003. Using the Internet to conduct surveys of health professionals: a valid alternative? Family Practice 20: 545-551. San Miguel F, Ryan M, Scott A. 2002. Are preferences stable? The case of health care. Journal of Economic Behavior and Organization 48: 1-14. Bettman JR, Johnson EJ, Payne JW. 1990. A componential analysis of cognitive effort in choice. Organizational Behavior and Human Decision Processes 45: 111-139. Farrar S, Ryan M, Ross D, Ludbrook A. 2000. Using discrete choice modelling in priority setting: an application to clinical service developments. Social Science and Medicine 50: 63-75. Molin EJE, Oppewal H, Timmermans HJP. 2001. Analyzing heterogeneity in conjoint estimates of residential preferences. Journal of Housing and the Built Environment 16: 267-284. Lancsar E, Donaldson C. 2005. Discrete choice experiments in health economics: distinguishing between the method and its application. European Journal of Health Economics 6: 314-316. Ryan M. 1999. Using conjoint analysis to take account of patient preferences and go beyond health outcomes: an application to in vitro fertilisation. Social Science and Medicine 48: 535-546. Will BP, Berthelot JM, Le Petit C, Tomiak EM, Verma S, Evans WK. 2000. Estimates of the lifetime costs of breast cancer treatment in Canada. European Journal of Cancer 36: 724-735. Stuber KJ, Grod JP, Smith DL, Powers P. 2005. An online survey of chiropractors' opinions of continuing education. Chiropractic and Osteopathy 13: 22. Telser H, Zweifel P. 2007. Validity of discrete-choice experiments evidence for health risk reduction. Applied Economics 39: 69-78. 2007; 39 1990; 54 2002; 37 2001b; 5 1999; 48 2000; 50 1999; 46 2008 2005; 20 2007 2004; 5 2005 1992; 14 2003; 30 1998; 16 2002; 48 1990; 22 2000; 18 1990; 45 2000; 36 2000 2000; 32 1984; 11 1993; 30 1983; 20 2003; 2 2003; 3 2005; 6 1977; 33 1999; 31 2001; 16 2001a; 10 1998; 30 1998; 10 2003; 20 2005; 13 1994; 31 Oppewal H (e_1_2_1_19_1) 2003; 30 Louviere JJ (e_1_2_1_13_1) 1984; 11 e_1_2_1_20_1 e_1_2_1_23_1 e_1_2_1_24_1 e_1_2_1_21_1 e_1_2_1_22_1 e_1_2_1_28_1 e_1_2_1_26_1 e_1_2_1_29_1 Brown SL (e_1_2_1_5_1) 2005; 20 e_1_2_1_7_1 Ryan M. (e_1_2_1_27_1) 2003; 2 e_1_2_1_31_1 e_1_2_1_8_1 e_1_2_1_30_1 Ryan M (e_1_2_1_25_1) 2001; 10 e_1_2_1_6_1 e_1_2_1_3_1 e_1_2_1_12_1 e_1_2_1_35_1 e_1_2_1_4_1 e_1_2_1_34_1 Grol R (e_1_2_1_10_1) 2005 e_1_2_1_33_1 e_1_2_1_2_1 e_1_2_1_11_1 e_1_2_1_32_1 e_1_2_1_16_1 e_1_2_1_39_1 e_1_2_1_17_1 e_1_2_1_38_1 e_1_2_1_14_1 e_1_2_1_37_1 e_1_2_1_15_1 e_1_2_1_36_1 e_1_2_1_9_1 e_1_2_1_18_1 |
| References_xml | – reference: Landis JR, Koch GG. 1977. The measurement of observer agreement for categorical data. Biometrics 33: 159-174. – reference: Farrar S, Ryan M, Ross D, Ludbrook A. 2000. Using discrete choice modelling in priority setting: an application to clinical service developments. Social Science and Medicine 50: 63-75. – reference: Braithwaite D, Emery J, de Lusignan S, Sutton S. 2003. Using the Internet to conduct surveys of health professionals: a valid alternative? Family Practice 20: 545-551. – reference: Ryan M. 1999. Using conjoint analysis to take account of patient preferences and go beyond health outcomes: an application to in vitro fertilisation. Social Science and Medicine 48: 535-546. – reference: Swait J, Louviere J. 1993. The role of the scale parameter in the estimation and comparison of multinomial logit models. Journal of Marketing Research 30: 305-314. – reference: Louviere JJ, Hensher DA, Swait JD. 2000. Stated Choice Methods: Analysis and Application. Cambridge University Press: Cambridge. – reference: Bryan S, Dolan P. 2004. Discrete choice experiments in health economics: for better or for worse? European Journal of Health Economics 5: 199-202. – reference: Louviere JJ, Timmermans HJP. 1990. Using hierarchical information integration to model consumer responses to possible planning actions: recreation destination choice illustration. Environment and Planning A 22: 291-308. – reference: Oppewal H, Klabbers M. 2003. Compromising between information completeness and task simplicity: a comparison of self-explicated, hierarchical information integration, and full-profile conjoint methods. Advances in Consumer Research 30: 298-304. – reference: Vyvere van de Y, Oppewal H, Timmermans H. 1998. The validity of hierarchical information integration choice experiments to model residential preference and choice. Geographical Analysis 30: 254-272. – reference: Brown SL, Kittleson MJ. 2005. E-mail versus Web survey response rates among health education professionals. American Journal of Health Studies 20(1): 7-14. – reference: Bettman JR, Johnson EJ, Payne JW. 1990. A componential analysis of cognitive effort in choice. Organizational Behavior and Human Decision Processes 45: 111-139. – reference: San Miguel F, Ryan M, McIntosh E. 2000. Applying conjoint analysis in economic evaluations: an application to menorrhagia. Applied Economics 32: 823-833. – reference: Scott A, Vick S. 1999. Patients, doctors and contracts: an application of principal-agent theory to the doctor-patient relationship. Scottish Journal of Political Economy 46: 111-134. – reference: Will BP, Berthelot JM, Le Petit C, Tomiak EM, Verma S, Evans WK. 2000. Estimates of the lifetime costs of breast cancer treatment in Canada. European Journal of Cancer 36: 724-735. – reference: Ülengin B. 1998. Using hierarchical information integration to examine customer preferences in banking. International Journal of Bank Marketing 16: 202-210. – reference: Telser H, Zweifel P. 2007. Validity of discrete-choice experiments evidence for health risk reduction. Applied Economics 39: 69-78. – reference: Louviere JJ, Timmermans HJP. 1992. Testing the external validity of hierarchical conjoint analysis models of recreational destination choice. Leisure Sciences 14: 179-194. – reference: Grol R, Wensing M, Eccles M. 2005. Improving Patient Care: The Implementation of Change in Clinical Practice. Elsevier: Oxford. – reference: Phillips KA, Maddala T, Johnson FR. 2002. Measuring preferences for health care interventions using conjoint analysis: an application to HIV testing. Health Services Research 37: 1681-1705. – reference: Lancsar E, Donaldson C. 2005. Discrete choice experiments in health economics: distinguishing between the method and its application. European Journal of Health Economics 6: 314-316. – reference: Stuber KJ, Grod JP, Smith DL, Powers P. 2005. An online survey of chiropractors' opinions of continuing education. Chiropractic and Osteopathy 13: 22. – reference: Molin EJE, Oppewal H, Timmermans HJP. 2001. Analyzing heterogeneity in conjoint estimates of residential preferences. Journal of Housing and the Built Environment 16: 267-284. – reference: Walker AE, Grimshaw J, Johnston M, Pitts N, Steen N, Eccles M. 2003. PRIME - PRocess modelling in ImpleMEntation research: selecting a theoretical basis for interventions to change clinical practice. BMC Health Services Research 3: 22. – reference: Oppewal H, Louviere JJ, Timmermans HJP. 1994. Modeling hierarchical conjoint processes with integrated choice experiments. Journal of Marketing Research 31: 92-105. – reference: Sitzia J, Wood N. 1998. Response rate in patient satisfaction research: an analysis of 210 published studies. International Journal for Quality in Health Care 10: 311-317. – reference: Ryan M, Bate A, Eastmond CJ, Ludbrook A. 2001a. Use of discrete choice experiments to elicit preferences. Quality in Health Care 10(Suppl): I55-I60. – reference: Oppewal H, Vriens M. 2000. Measuring perceived service quality using integrated conjoint experiments. International Journal of Bank Marketing 18: 154-169. – reference: Street DJ, Burgess L. 2007. The Construction of Optimal Stated Choice Experiments: Theory and Methods. Wiley: Hoboken, NJ. – reference: Oppewal H, Timmermans H. 1999. Modeling consumer perception of public space in shopping centers. Environment and behaviour 31: 45-65. – reference: Green PE, Srinivasan V. 1990. Conjoint analysis in marketing: new developments with implications for research and practice. Journal of Marketing 54: 3-19. – reference: Louviere JJ. 1984. Hierarchical information integration: a new method for the design and analysis of complex multiattribute judgment problems. Advances in Consumer Research 11: 148-155. – reference: Ryan M., Gerard K. 2003. Using discrete choice experiments to value health care programmes: current practice and future research reflections. Applied Health Economics and Health Policy 2: 55-64. – reference: San Miguel F, Ryan M, Scott A. 2002. Are preferences stable? The case of health care. Journal of Economic Behavior and Organization 48: 1-14. – reference: Ryan M, Scott DA, Reeves C, Bate A, Teijlingen van ER, Russell EM, Napper M, Robb CM. 2001b. Eliciting public preferences for health care: a systematic review of techniques. Health Technology Assessment 5(5). – reference: Louviere JJ, Woodworth G. 1983. Design and analysis of simulated consumer choice or allocation experiments: an approach based on aggregate data. Journal of Marketing Research 20: 350-367. – volume: 20 start-page: 7 issue: 1 year: 2005 end-page: 14 article-title: E‐mail versus Web survey response rates among health education professionals publication-title: American Journal of Health Studies – volume: 16 start-page: 267 year: 2001 end-page: 284 article-title: Analyzing heterogeneity in conjoint estimates of residential preferences publication-title: Journal of Housing and the Built Environment – volume: 3 start-page: 22 year: 2003 article-title: PRIME – PRocess modelling in ImpleMEntation research: selecting a theoretical basis for interventions to change clinical practice publication-title: BMC Health Services Research – year: 2005 – year: 2007 – volume: 5 issue: 5 year: 2001b article-title: Eliciting public preferences for health care: a systematic review of techniques publication-title: Health Technology Assessment – year: 2000 – volume: 30 start-page: 305 year: 1993 end-page: 314 article-title: The role of the scale parameter in the estimation and comparison of multinomial logit models publication-title: Journal of Marketing Research – volume: 18 start-page: 154 year: 2000 end-page: 169 article-title: Measuring perceived service quality using integrated conjoint experiments publication-title: International Journal of Bank Marketing – volume: 5 start-page: 199 year: 2004 end-page: 202 article-title: Discrete choice experiments in health economics: for better or for worse? publication-title: European Journal of Health Economics – volume: 33 start-page: 159 year: 1977 end-page: 174 article-title: The measurement of observer agreement for categorical data publication-title: Biometrics – volume: 37 start-page: 1681 year: 2002 end-page: 1705 article-title: Measuring preferences for health care interventions using conjoint analysis: an application to HIV testing publication-title: Health Services Research – volume: 48 start-page: 535 year: 1999 end-page: 546 article-title: Using conjoint analysis to take account of patient preferences and go beyond health outcomes: an application to in vitro fertilisation publication-title: Social Science and Medicine – volume: 46 start-page: 111 year: 1999 end-page: 134 article-title: Patients, doctors and contracts: an application of principal‐agent theory to the doctor‐patient relationship publication-title: Scottish Journal of Political Economy – volume: 48 start-page: 1 year: 2002 end-page: 14 article-title: Are preferences stable? The case of health care publication-title: Journal of Economic Behavior and Organization – volume: 20 start-page: 545 year: 2003 end-page: 551 article-title: Using the Internet to conduct surveys of health professionals: a valid alternative? publication-title: Family Practice – volume: 6 start-page: 314 year: 2005 end-page: 316 article-title: Discrete choice experiments in health economics: distinguishing between the method and its application publication-title: European Journal of Health Economics – volume: 2 start-page: 55 year: 2003 end-page: 64 article-title: Using discrete choice experiments to value health care programmes: current practice and future research reflections publication-title: Applied Health Economics and Health Policy – volume: 54 start-page: 3 year: 1990 end-page: 19 article-title: Conjoint analysis in marketing: new developments with implications for research and practice publication-title: Journal of Marketing – volume: 22 start-page: 291 year: 1990 end-page: 308 article-title: Using hierarchical information integration to model consumer responses to possible planning actions: recreation destination choice illustration publication-title: Environment and Planning A – volume: 31 start-page: 45 year: 1999 end-page: 65 article-title: Modeling consumer perception of public space in shopping centers publication-title: Environment and behaviour – volume: 10 start-page: I55 issue: Suppl year: 2001a end-page: I60 article-title: Use of discrete choice experiments to elicit preferences publication-title: Quality in Health Care – volume: 16 start-page: 202 year: 1998 end-page: 210 article-title: Using hierarchical information integration to examine customer preferences in banking publication-title: International Journal of Bank Marketing – volume: 31 start-page: 92 year: 1994 end-page: 105 article-title: Modeling hierarchical conjoint processes with integrated choice experiments publication-title: Journal of Marketing Research – volume: 30 start-page: 254 year: 1998 end-page: 272 article-title: The validity of hierarchical information integration choice experiments to model residential preference and choice publication-title: Geographical Analysis – volume: 20 start-page: 350 year: 1983 end-page: 367 article-title: Design and analysis of simulated consumer choice or allocation experiments: an approach based on aggregate data publication-title: Journal of Marketing Research – volume: 10 start-page: 311 year: 1998 end-page: 317 article-title: Response rate in patient satisfaction research: an analysis of 210 published studies publication-title: International Journal for Quality in Health Care – year: 2008 – volume: 45 start-page: 111 year: 1990 end-page: 139 article-title: A componential analysis of cognitive effort in choice publication-title: Organizational Behavior and Human Decision Processes – volume: 39 start-page: 69 year: 2007 end-page: 78 article-title: Validity of discrete‐choice experiments evidence for health risk reduction publication-title: Applied Economics – volume: 50 start-page: 63 year: 2000 end-page: 75 article-title: Using discrete choice modelling in priority setting: an application to clinical service developments publication-title: Social Science and Medicine – volume: 30 start-page: 298 year: 2003 end-page: 304 article-title: Compromising between information completeness and task simplicity: a comparison of self‐explicated, hierarchical information integration, and full‐profile conjoint methods publication-title: Advances in Consumer Research – volume: 14 start-page: 179 year: 1992 end-page: 194 article-title: Testing the external validity of hierarchical conjoint analysis models of recreational destination choice publication-title: Leisure Sciences – volume: 13 start-page: 22 year: 2005 article-title: An online survey of chiropractors' opinions of continuing education publication-title: Chiropractic and Osteopathy – volume: 11 start-page: 148 year: 1984 end-page: 155 article-title: Hierarchical information integration: a new method for the design and analysis of complex multiattribute judgment problems publication-title: Advances in Consumer Research – volume: 36 start-page: 724 year: 2000 end-page: 735 article-title: Estimates of the lifetime costs of breast cancer treatment in Canada publication-title: European Journal of Cancer – volume: 32 start-page: 823 year: 2000 end-page: 833 article-title: Applying conjoint analysis in economic evaluations: an application to menorrhagia publication-title: Applied Economics – ident: e_1_2_1_16_1 doi: 10.1080/01490409209513167 – ident: e_1_2_1_3_1 doi: 10.1016/0749-5978(90)90007-V – ident: e_1_2_1_28_1 doi: 10.1080/000368400322165 – ident: e_1_2_1_39_1 doi: 10.1016/S0959-8049(99)00340-8 – ident: e_1_2_1_23_1 doi: 10.1111/1475-6773.01115 – ident: e_1_2_1_38_1 doi: 10.1186/1472-6963-3-22 – ident: e_1_2_1_34_1 doi: 10.2307/3172883 – ident: e_1_2_1_29_1 doi: 10.1016/S0167-2681(01)00220-7 – volume: 30 start-page: 298 year: 2003 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| SubjectTerms | Adult Choice Behavior Clinical guidelines Construct validity Discrete choice discrete choice experiments Economic models Feasibility Female Health care management Health economics hierarchical information integration Hospitalization Humans Information Management - organization & administration integrated choice experiments Male Medical Staff, Hospital Middle Aged multi-faceted health-care decisions Netherlands Patient Care Predictive ability Reproducibility of Results Studies Surgery Surveys and Questionnaires Validation studies Validity |
| Title | Discrete choice experiments for complex health-care decisions: does hierarchical information integration offer a solution? |
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