Stein, K and Dyer, M and Crabb, T and Milne, R and Round, A and Ratcliffe, J and Brazier, J (2006): An Internet “Value of Health” panel: recruitment, participation and compliance.
Download (277kB) | Preview
OBJECTIVES To recruit a panel of members of the public to provide preferences in response to the needs of economic evaluators over the course of a year.
METHODS A sample of members of the UK general public was recruited in a stratified random sample from the electoral roll and familiarised with the standard gamble method of preference elicitation using an internet based tool. Recruitment (proportion of people approached who were trained), participation (defined as the proportion of people trained who provided any preferences) and compliance (defined as the proportion of preference tasks which were completed) were described. The influence of covariates on these outcomes was investigated using univariate and multivariate analyses.
RESULTS A panel of 112 people was recruited. The eventual panel reflected national demographics to some extent, but recruitment from areas of high socioeconomic deprivation and among ethnic minority communities was low. 23% of people who were approached (n= 5,320) responded to the invitation to take part in the study, and 24% of respondents (n=1,215) were willing to participate. However, eventual recruitment rates, following training, were low (2.1% of those approached), although significantly higher in Exeter than other cities. 18 sets of health state descriptions were presented to the panel over 14 months. 74% of panel members praticipated in at least one valuation task. Socioeconomic and marital status were significantly associated with participation. Compliance varied from 3% to 100%, with the average per set of health state descriptions being 41%. Compliance was higher in retired people but otherwise no significant predictors were identified.
CONCLUSIONS It is feasible to recruit and train a panel of members of the general public to express preferences on a wide range of health states using the internet in response to the needs of analysts. In order to provide a sample which reflects the demographics of the general public, and capitalise on the increasing opportunities for the use of the internet in this field, over-sampling in areas of high socioeconomic deprivation and among ethnic minority communities is necessary.
|Item Type:||MPRA Paper|
|Original Title:||An Internet “Value of Health” panel: recruitment, participation and compliance|
|Keywords:||utility; Internet; public; survey|
|Subjects:||I - Health, Education, and Welfare > I3 - Welfare and Poverty > I31 - General Welfare
I - Health, Education, and Welfare > I1 - Health > I19 - Other
|Depositing User:||Sarah McEvoy|
|Date Deposited:||24. Mar 2011 22:00|
|Last Modified:||13. Feb 2013 09:08|
Hutton J, Brown R (2002). Use of economic evaluation in decision-making: What needs to change? Value in Health 5:65-6.
Neumann PJ (2005). Why don't Americans use cost-effectiveness analysis? American Journal of Managed Care 10:308-12.
Sonnad S, Greenberg D, Rosen A, Neumann P (2005). Diffusion of published cost-utility analyses in the field of health policy and practice. International Journal of Technology Assessment in Health Care 21(3):399-402.
Glennie J, Torrance GW, Baladi J, et al (1999). The revised Canadian Guidelines for the Economic Evaluation of Pharmaceuticals. Pharmacoeconomics 15(5):459-68.
Weinstein MC, Siegel JE, Gold MR, et al (1996). Recommendations of the panel on cost-effectiveness in health and medicine consensus statement. JAMA 276(15):1253-8.
National Institute for Clinical Excellence. Guide to the Methods of Technology Appraisal. London: National Institute for Clinical Excellence; 2003.
Best L, Stevens AJH, Colin-Jones D (1997). Rapid and responsive health technology assessment: the development and evaluation process in the South and West region of England. J Clin Effect 2(2):51-6.
Stevens AJH, Gabbay J (1995). "Qquick and clean": authoritative health technology assessment for local health care contracting. Health Trends 27(2):37-42.
Raftery J (2001). NICE: faster access to modern treatments? Analysis of guidance on health technologies. BMJ 323:1300-3.
Devlin N, Parkin D (2004). Does NICE have a cost-effectiveness threshold and what other factors influence its decisions? A binary choice analysis. Health Economics 13:437-52.
Dolan P (1999). Whose preferences count? Med Decis Making 19(4):482-6.
Brazier J, Akehurst R, Brennan A, et al (2004). Should patients have a greater role in valuing health states: whose well-being is it anyway? [04/3]. Sheffield, School of Health and Related Research, University of Sheffield. Discussion Paper Series.
Torrance G, Feeny D, Furlong W, et al (1996). Multiattribute utility functions for a comprehensive health status classification. Medical Care 34(7):702-22.
Gafni A (1991). Willingness to pay as a measure of benefits: relevant questions in the context of public decision making about health care programmes. Medical Care 29:1246-52.
De Wit GA, Busschbach JJ, De Charro FT (2000). Sensitivity and perspective in the valuation of health status: whose values count? Health Econ 9(2):109-26.
Buckingham K (1993). A note on HYE (healthy years equivalent). Health Economics 12:301-9.
Ubel P, Richardson J, Menzel P (2000). Societal value, the person trade-off, and the dilemma of whose values to measure for cost-effectiveness analysis. Health Economics 9:127-36.
Furlong W, Oldridge N, Perkins A, et al (2003). Community or patient preferences for cost-utility analyses: does it matter? International Society for Pharmacoeconomics, ISPOR Conference, Arlington, Virginia.
Stein K, Fry A, Round A, et al (2006). What value health? A review of health state values used in early technology assessments for NICE. Applied Health Economics and Policy.
Dolan P (2002). The measurement of health related quality of life for use in resource allocation in health care. In: Culyer A, Newhouse J, (eds), Handbook of Health Economics. London: Elsevier Science.
Espallargues M, Czoski-Murray C, Bansback N, et al (2006). The impact of age related macular degeneration on health state utility values. Investigative Ophthalmology and Visual Science 2006 (in press).
Barton GR, Bankart J, Davis AC, Summerfield QA (2004). Comparing utility scores before and after hearing aid provision. Applied Health Economics and Health Policy 3(2):103-5.
Schunemann H, Stahl H, Austin P, et al (2004). A comparison of narrative and table formats for presenting hypothetical health states to patients with gastrointestinal or pulmonary disease. Medical Decision Making 24:53-60.
Index Multiple Deprivation 2000. Accessed 3/9/03: www.gowm. gov.uk/regionalintelligence/deprivation, 2000.
Dolan P, Gudex C (1995). Time preference, duration and health state valuations. Health Economics 4:289-99.
von Neumann J, Morganstern O (1947). THeory of Games and Economic Behaviour (2nd ed.). Princeton: Princeton University Press.
Lenert LA, Cher DJ, Goldstein MK, et al (1998). The effect of search procedures on utility elicitations. Med Decis Making 18:76-83.
Scottish Index of Multiple Deprivation: Summary Technical Report. Edinburgh: Scottish Executive; 2004.
Noble M, Wright G, Dibben C, et al (2004). Indices of Deprivation 2004: Report to the Office of the Deputy Prime Minister. London: Neighbourhood Renewal Unit.
Dolan P, Gudex C, Kind P, Williams A (1996). The time trade-off method: results from a general population study. Health Economics 5(2):141-54.
Bartlett C, Doyal L, Ebrahim S, et al (2005). The causes and effects of sociodemographic exclusions from clinical trials. Health Technology Assessment 9(38).
Sherbourne CD, Keeler E, Unützer J, et al (1999). Relationship between age and patients' current health state preferences. The Gerontologist 39(3):271-8.
Lundberg L, Johannesson M, Isacson DGL, Borgquist L (1999). Health-state utilities in a general population in relation to age, gender and socioeconomic factors. European Journal of Public Health (9):211-7.
Kind P, Dolan P (1995). The effect of past and present illness experience on the valuations of health states. Medical Care 33(4 Suppl):AS255-63.
Brennan P, Strombom I (1998). Improving health care by understanding patient preferences. Journal of the American Medical Informatics Association 5(3):257-62.
Sumner W, Nease R, Littenberg B (1991). U-titer: a utility assessment tool. Proceedings of the Annual Symposium on Computer Application in Medical Care 701-5.
UMaker [computer program]. New Jersey: Clinical Informatics Research Group, University of Medicine and Dentistry; 1993.
Gonzalez B, Eckman G, et al (1992). Gambler: a computer workstation for patient utility assessment. Medical Decision Making 12:350.
Lenert L, Michelson D, Flowers C, Bergen M (1995). IMPACT: an object-orientated graphical environment for construction of multimedia patient interviewing software. Proceedings of the Annual Symposium on Computer Application in Medical Care 319-23.
Lenert LA, Sturley A, Watson ME (2002). iMPACT3: Internet-based development and administration of utility elicitation protocols. Med Decis Making 22:464-74.
McFarlane P, Bayoumi A, Pierratos A, Redelmeier D (2003). The quality of life and cost utility of home nocturnal and conventional in-center haemodialysis. Kidney International 64(3):1004-11.
Gerson L, Ullah N, Hastie T, et al (2005). Patient derived health state utilities for gastroesophageal reflux disease. American Journal of Gastroenterology 100(3):524-33.
Munakata J, Woolcott J, Anis A, et al (2005). Design of a prospective economic evaluation for a tri-national clinical trial in HIV patients (OPTIMA). San Francisco: Society for Medical Decision Making.
Tosteson A, Kneeland T, Nease R, Sumner W (2002). Automated current health time-trade-off assessments in women's health. Value in Health 5(2):98-105.
Schwartz A. http://araw.mede.uic.edu/cgi-bin/utility.cgi. 2005.
Lenert LA, Sturley AE (2001). Acceptability of computerized visual analog scale, time trade-off and standard gamble rating methods in patients and the public. AMI Association Proceedings 364-8.
Goldstein MK, Clarke AE, Michelson D, et al (1994). Developing and testing a multimedia presentation of a health-state description. Med Decis Making 14:336-44.
Lenert L, Sturley A, Rupnow M (2003). Toward improved methods for measurement of utility: automated repair of errors in elicitation. Medical Decision Making 23:67-75.
Damschroder L, Baron J, Hershey J, et al (2004). The validity of person tradeoff measurements: randomized trial of computer elicitation versus face-to-face interview. Medical Decision Making 24(2):170-80.
Damschroder L, Zikmund-Fisher B, Kulpa J, Ubel P (2005). Considering adaptation in preference elicitations. San Francisco: Society for Medical Decision Making Annual Conference.
Damschroder L, Muroff J, Smith D, Ubel P (2005). A reversal in the public/patient discrepancy: utility ratings for pain from pain patients are lower than from non-patients. San Francisco: Society for Medical Decision Making Annual Conference.
Damschroder L, Ubel P, Zikmund-Fisher B, et al (2005). A randomized trial of a web-based deliberation exercise: improving the quality of healthcare allocation preference surveys. San Francisco: Society for Medical Decision Making Annual Conference.
Baron J, Ubel P (2002). Types of inconsistency in health-state utility judgements. Organizational Behaviour and Human Decision Processes 89:1100-18.
Hardman & Co. YouGov: Polling for a Profit. http://www.yougov.com/corporate/pdf/analystYGFloat_1.pdf.; 2005 Mar 21.
Baker K, Curtice J, Sparrow N (2003). Internet Poll Trial: Research Report. London: ICM Research.